Final Report - WordPress.com...Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates Removal of

Socio-economic Impact of an Air Transport

Liberalisation Agreement in the Southern

African Development Community

Graham Muller Associates

30 August 2010

Final Report

P a g e | i

Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates

Table of Contents

Executive Summary ....................................................................................................................................... v

Introduction .............................................................................................................................................. v

Literature Review ...................................................................................................................................... v

The nine freedoms of the air ................................................................................................................ v

The Yamoussoukro Decision ............................................................................................................... vii

Assessing and forecasting the impact of air transportation liberalisation agreements ....................... x

Economic Impact of an air transport liberalisation agreement in SADC ................................................xiii

Overview of current status of the SADC Aviation Industry .................................................................xiii

Cost-Benefit Analysis Methodology .................................................................................................... xvi

Cost Benefit Analysis Results ............................................................................................................. xvii

Impact of an air transport liberalisation agreement in the Southern African Development Community

................................................................................................................................................................. xx

Impact of an air transport liberalisation agreement reflecting the investment and capital expenditure

in airport and navigational infrastructure .............................................................................................. xxi

Introduction .................................................................................................................................................. 1

1 Literature Review .................................................................................................................................. 2

1.1 Introduction .................................................................................................................................. 2

1.2 The nine freedoms of the air ........................................................................................................ 3

1.3 History of aviation agreements ..................................................................................................... 5

1.3.1 Chicago Convention 1944 ..................................................................................................... 5

1.3.2 Formation of state owned or sponsored airlines.................................................................. 6

1.3.3 Liberalisation of aviation agreements................................................................................... 7

1.4 Assessing and forecasting the impact of air transportation liberalisation agreements ............. 15

1.4.1 The case study approach .................................................................................................... 15

1.4.2 The trends model ................................................................................................................ 16

1.4.3 The gravity model ............................................................................................................... 16

P a g e | ii


1.4.4 The stimulation model ........................................................................................................ 17

1.4.5 Air transport cost analysis ................................................................................................... 17

1.5 Case Studies ................................................................................................................................ 18

1.5.1 United States – United Kingdom ......................................................................................... 18

1.5.2 The European Union ........................................................................................................... 20

1.5.3 India – United Kingdom....................................................................................................... 22

1.5.4 Impact of an international air transportation liberalisation agreement ............................ 26

1.6 Forecasted effects of air transportation liberalisation agreements ........................................... 26

1.6.1 Infrastructure, regulatory body, skills and market size limitations .................................... 27

1.6.2 Spread of development from hubs to outlying areas ......................................................... 31

1.7 Concluding Comments ................................................................................................................ 32

2 Impact of air transport liberalisation agreement in Southern African development Community ..... 34

2.1 Introduction ................................................................................................................................ 34

2.2 Overview of the Current Status of the SADC Aviation Industry .................................................. 35

2.2.1 Angola ................................................................................................................................. 35

2.2.2 Botswana ............................................................................................................................. 36

2.2.3 Democratic Republic of the Congo (DRC) ........................................................................... 39

2.2.4 Lesotho ................................................................................................................................ 40

2.2.5 Madagascar ......................................................................................................................... 41

2.2.6 Malawi ................................................................................................................................. 43

2.2.7 Mauritius ............................................................................................................................. 45

2.2.8 Mozambique ....................................................................................................................... 47

2.2.9 Namibia ............................................................................................................................... 49

2.2.10 Seychelles ............................................................................................................................ 51

2.2.11 South Africa ......................................................................................................................... 52

2.2.12 Tanzania .............................................................................................................................. 57

2.2.13 Zambia ................................................................................................................................. 60

2.2.14 Airports in SADC .................................................................................................................. 63

2.2.15 Fleet size of all SADC airlines .............................................................................................. 68

2.3 Analysis of Questionnaire Results ............................................................................................... 70

P a g e | iii


2.3.1 Airlines ................................................................................................................................ 70

2.3.2 Airports ............................................................................................................................... 74

2.3.3 Other Stakeholders in the aviation industry ....................................................................... 76

2.4 Cost-Benefit Analysis Methodology ............................................................................................ 82

2.4.1 Model .................................................................................................................................. 82

2.4.2 Direct Impacts ..................................................................................................................... 92

2.4.3 Indirect Impacts .................................................................................................................. 99

2.4.4 Airport and Navigational Infrastructure ........................................................................... 102

2.5 Cost-Benefit Analysis Results .................................................................................................... 107

2.5.1 Direct Impacts ................................................................................................................... 107

2.5.2 Benefit to airlines .............................................................................................................. 107

2.5.3 Benefits to passengers ...................................................................................................... 111

2.5.4 Indirect Impacts ................................................................................................................ 121

2.5.5 Airport and navigational infrastructure ............................................................................ 131

2.6 Impact of an air transport liberalisation agreement in the Southern African Development

Community (SADC) ................................................................................................................................ 137

2.6.1 Total Computable Benefits ............................................................................................... 137

2.6.2 Total Costs ......................................................................................................................... 139

2.6.3 Impact of an air transport liberalisation agreement in the Southern African Development

Community ........................................................................................................................................ 140

2.7 Impact of an air transport liberalisation agreement reflecting the investment and capital

expenditure in airport and navigational infrastructure ........................................................................ 142

Conclusion ................................................................................................................................................. 145

References ................................................................................................................................................ 146

List of References .............................................................................................................................. 146

Conversions are based on the following websites............................................................................ 146

List of Tables ............................................................................................................................................. 148

List of Figures ............................................................................................................................................ 151

List of Boxes .............................................................................................................................................. 156

Appendix A – Signing States of the Chicago Convention 1944 ................................................................. 157

P a g e | iv


Appendix B – United States Air transportation liberalisation Partners and status of the agreement ..... 158

Appendix C – State ownership for international flag carriers................................................................... 161

Appendix D – Spider Diagram ................................................................................................................... 166

Appendix E – Questionnaires .................................................................................................................... 167

Air transportation liberalisation Questionnaire for Southern African Airlines ..................................... 167

Air transportation liberalisation Questionnaire for Southern African Airlines ..................................... 187

Air transportation liberalisation Questionnaire for other Southern Africa Aviation Industry

Stakeholders ......................................................................................................................................... 205

Appendix F – Destinations within SADC .................................................................................................... 212

Appendix G Total impact per airport over the 50 year period less airport/navigational infrastructure

costs (R Millions) ....................................................................................................................................... 233

P a g e | v


Executive Summary

Introduction

This report has been compiled in conjunction with the South African Department of Transport. The

project measures the economic impact of implementing an air transportation liberalisation agreement

within the Southern African Development Community (SADC) region. The report is divided between a

review of literature analysing the impact of air transportation liberalisation agreements around the

world, and the forecasted impact of implementing the air transportation liberalisation agreement in the

SADC region.

Literature Review

Air transportation liberalisation is the liberalisation of aviation regulations between countries or within

geographic regions. Air transportation liberalisation agreements have largely been adopted and pursued

by developed countries. The United States has actively been involved in negotiating Air transportation

liberalisation agreements between various countries since 1972, while the European Union initiated its

internal common market or cabotage area by means of air transportation liberalisation between

member states in 1988. The Yamoussoukro Decision (YD) is the inter-African version of air transport

liberalisation Agreements and this was signed into operation by member states in 1999, however limited

progress has been made on this agreement.

The literature review has been structured in such a way that it looks at:

Analysing the various components that can be utilised when entering air transportation liberalisation agreement;

The short comings of Yamoussoukro Decision and the requirement for the establishment of a competition body to monitor airline behaviour in Africa (or SADC);

The various methods of measuring the impact of air transportation liberalisation agreements; and

The impact of air transportation liberalisation as measured by existing reports and studies.

The nine freedoms of the air

Table 1.1-1 displays the various freedoms of the air that make up aviation agreements between

countries and regions. Air freedoms 1 to 4 make up traditional aviation agreements between countries

with very restrictive aviation laws, whereas air freedoms 5 to 9 would represent a relaxing in aviation

agreements between countries. Freedoms 5 to 9 have been allowed by certain countries since 1944, but

this has largely been the case in a limited number of aviation agreements.

P a g e | vi


Table 1.1-1 Definition of air freedom rights

1st Freedom

To overfly one country en-route to another

2nd Freedom

To make a technical stop in another country

3rd Freedom

To carry freight and passengers from the home country to another country

4th Freedom

To carry freight and passengers to the home country from another country

5th Freedom

To carry freight and passengers between two countries on route (by an airline of a third (home) country) with origin / destination in its home country

6th Freedom

To carry freight and passengers between two countries by an airline of a third country on two routes connecting in its home country

7th Freedom

To carry freight and passengers between two countries by an airline of a third country on a route with no connection with its home country

8th Freedom or Cabotage

To carry freight and passengers within a country by an airline of another country on a route with origin / destination in its home country

9th Freedom or True Domestic

To carry freight and passengers within a foreign country with no connection with the home country

More recent air

transportation

liberalisation

regulations

Traditional bilateral

aviation regulations

3rd Freedom 5th Freedom

Source: ICAO Manual of Regulation (2004) and

WTO Secretariat

P a g e | vii


The Yamoussoukro Decision

Over the last three decades the African aviation market has been dominated by national flag carriers

that have benefited from government protection and free market economic logic has played little to no

role in this industry. Therefore there has been little improvement and innovation in the quality and

quantity of air services around the continent. The African tax payer is predominantly the biggest loser as

governments subsidise, recapitalise or protect national flag carriers that typically operate under dismal

financial conditions.

Table 1.1-2 below shows the international growth in the aviation market over a 17 year period. It can be

seen that while the African aviation market has grown, while this is the fastest growing market after

Latin America and Caribbean, the African market is still small when compared with the market size of

the Worlds other regions.

Table 1.1-2 Total number of domestic and international airline passengers, by region

Source: ICAO, 2007

The YD encourages co-operation between African states through aviation. YD advocates the following:

That only African owned airlines would benefit from the implementation of YD

The granting of 1st to 5th air freedom rights (as well as cabotage, the 8th air freedom rights);

Encouraging the development of new routes;

40

.8

31

8.9 5

46

.2

47

.8

74

1.8

83

.5

60

.9

66

5.5

74

3

79

.1

11

04

.9

13

4.5

11

4

98

0

13

67

11

1

15

29

27

2

0

200

400

600

800

1000

1200

1400

1600

1800

Afr

ica

Asi

aPac

ific

Euro

pe

Mid

dle

Eas

t

No

rth

A

mer

ica

Lati

n A

mer

ica

and

C

arib

bea

n

Passengers (millions)

1989

1999

2006

P a g e | viii


Removal of capacity restrictions on passenger seats, freight and flights on certain routes;

The removal of expensive and complex tariff regulations;

The elimination of all protective policies that protect national flag carriers;

The termination of regulations on carriers’ alliance;

Doing away with restriction on the conversion of revenues to hard currency and repatriation;

Agree on code sharing; and

Allow carriers to have own-ground-service abroad

P a g e | ix


History and failure to implement

The implementation of the YD was expected to be concluded by 2002, with the complete removal of

regulations and all the air freedoms being permitted. Capacity constraints would be removed and a

monitoring body would be established to enforce and monitor that countries and airlines do not partake

in anti-competitive behaviour.

The YD agreement between African states in 1999 was over flowing with optimism and good intention,

but has faced a number of obstacles which have brought implementation to a complete standstill. The

reasons for this failure were highlighted by the African Union Report (2005):

confusion in the monitoring body of the Yamoussoukro Decision;

conditions for eligibility of airlines in the Yamoussoukro Decision are inadequate. These conditions allow any airline which has “its headquarters, central administration and principal place of business physically located in the state concerned” to be eligible to benefit from the advantages set forth in the Yamoussoukro Decision. Such an airline may be totally or in most part controlled by foreign capital or interests. The European Union has put in place very restrictive conditions in terms of eligibility so as to protect the airlines of its community

YD makes no mention of economic control of eligible airlines - there should be a provision in YD requiring airlines to avail to audit boards all accounting and financial documents to ascertain their economic status. These audit boards do not exist.

competition rules as contained in the Yamoussoukro Decision are inadequate. Competition rules need to be defined further.

YD has remained mostly stagnant since its inception, except in the Western African region.

African Aviation Competition Authority

Instrumental in the success of the YD is the establishment of a competition authority to oversee the

implementation of the agreement, while also monitoring that governments, airlines and airports don’t

partake in uncompetitive behaviour. This authority must be comprised of the various member states

and not favour any member state.

The completion rules have already been stated, but are worth repeating:

Only African owned airlines should benefit from the implementation of YD

The granting of 1st to 5th air freedom rights in each member state (as well as cabotage, the 8th air freedom rights);

Encourage the development of new routes;

Ensure the removal of capacity restrictions on passenger seats, freight and flights on certain routes;

P a g e | x


Ensure the removal of expensive and complex tariff regulations;

Ensure the elimination of all protective policies that protect national flag carriers;

Ensure the termination of regulations on carriers’ alliance;

Remove restriction on the conversion of revenues to hard currency and repatriation;

Agree on code sharing;

Allow carriers to have own-ground-service abroad;

Not allow any direct or indirect state or parastatal subsidies;

Not allow private financial aid that is not consistent with generally accepted rules and regulations governing private financing;

Allow equal access of all community airlines to state or parastatal markets (travels of state or parastatal officials, tenders and pilgrimages);

Ban on airlines who abuse a dominant positions;

Clear and equitable rules for the allocation of time slots through the establishment of a time slot co-ordination body comprising airport authorities, airlines and civil aviation authorities.

Assessing and forecasting the impact of air transportation liberalisation agreements

The literature reviewed displayed various methods of estimating the impact of air transportation

liberalisation regulations. The most common methods used to estimate the impacts are: the trends

model; the gravity model; air transport costs analysis; and the case study approach.

The trends approach uses statistical regression analysis to predict future growth in the aviation market;

this method is only applicable where air transportation liberalisation agreements have been in place

over period and data is available.

The gravity model estimates total unconstrained demand between origins and destinations, by taking

into account data such as GDP per capita or population levels, while also considering the distance flown.

Equation 1 indicates the mathematical equation utilised in calculating the gravity model for each routes

flown. This method calculates weights for each specific route, the higher the weight, the higher demand

for those flights.

Equation (1) Demand = (GDP Origin * GDP Destination)/Distance

The simulation method uses historical data and shows how demand in flights changes as air fares

increase and decrease, while this is possibly the most thorough way of calculating the impact of an air

transportation liberalisation agreement it is mostly inapplicable as reliable data is unavailable, limited or

compromised.

P a g e | xi


Lastly the case study approach is the most common method of estimating the impact of air

transportation liberalisation agreements; this approach looks at the impact experienced in other

countries or regions that have already implemented air transportation liberalisation policies and

legislation. Unsurprisingly the case study approach is completely qualitative, speculative, and imprecise;

it is also the easiest form of measuring air transportation liberalisation impacts.

Case studies

Case studies showing the impact of implemented air transportation liberalisation agreements have been

conducted between the United States and the European Union, the European Union, and India and the

United Kingdom. All case studies indicating the impact of air transportation liberalisation agreements

involve developed countries, or at least one developed country, as well as countries with established

and large aviation markets. This is partly due to the developed countries being among the first states to

open their skies and liberalise their aviation legislation. The other observation is that all the case studies

are enthusiastically positive with regards to air transportation liberalisation agreements; there is no

mention of any negative side effects and impacts.

It is estimated that the air transportation liberalisation agreement between the U.S. and U.K. is

responsible for stimulating 9,197 full-time equivalent jobs in the United States and over 16,700 full-time

equivalent positions in the United Kingdom. It is also estimated that the gross domestic product of the

United States also expanded by $747 million due to the agreement and the United Kingdom by roughly

$970 million.

Liberalisation of the E.U. aviation market between 1988 and 1993 has led to an additional 44 million

passengers being carried annually, which equals a 33% increase in passenger seats. This traffic

expansion has encouraged development of both the tourism sector and other industries. Some 1.4

million full-time jobs resulted from the liberalisation, and European GDP grew by $US 85 billion. Most

importantly noted is the dramatic market growth in low cost carrier airlines and the market share

decline of national flag carriers.

Between summer 2004 and summer 2006, the number of direct flights between India and the UK rose

from 34 to 112 per week. The increase in capacity and more intense competition has resulted in a

reduction in air fares, from £882 to £736 for one-way fare paid by passengers travelling for business

class and £251 to £231 for one-way fare paid by passengers travelling economy class.

Forecasted effects of air transportation liberalisation agreements

While the case studies were overwhelmingly positive with regards to air transportation liberalisation

agreements, there were two studies that raised legitimate concerns as they forecasted and analysed the

effects of air transportation liberalisation agreements. These reports were conducted by Micco and

Serebrisky (2006) and Swan (2008).

P a g e | xii


There are two essential issues that these reports raised as they analysed their data’s results:

Firstly, does the country have adequate infrastructure, a regulatory body, available skills and sufficient market size?

And secondly, can a country afford to shift aviation activity away from a central hub airport

Answering these questions has particular relevance for Africa and more specifically for the Southern

African Development Community.

Micco et al. (2006) discovered while running a regression on all countries and airports that operate

under air transportation liberalisation legislation, that airport with insufficient infrastructure, skills and

limited market sizes could not benefit fully from the effects of air transportation liberalisation

agreements.

Swan (2008) while analysing aviation data in the Far East discovered that air transportation liberalisation

agreements over time will move flights away from major hub airports to smaller airports as flights are

added to airline routes.

P a g e | xiii


Economic Impact of an air transport liberalisation agreement in SADC

The purpose of the study is to go further than just assessing the international experience of

implementing air transportation liberalisation agreements and determine the impact of implementing

the air transportation liberalisation agreement in the SADC region. The impact has been measured on

two levels, firstly the impacts experienced within the aviation market (direct impacts); and secondly the

impacts felt by supporting industries to the aviation market (indirect impacts).

The study identified the following direct and indirect impacts:

Direct impacts:

On Airlines

On Airports

Passengers

Freight

Customs

Indirect impacts:

On Tourism

On Airport services

Aircraft manufacturers

Environment

Intermodal services

Government

Overview of current status of the SADC Aviation Industry

SADC flight departure and passenger data indicates that certain airlines in SADC service mainly domestic

routes and service very few international routes, while other airlines are largely reliant on international

business. The general trend for most airlines indicates that there has been a gradual increase in the total

number of departures over the years; however a decrease in total departures is noted during the 2007

to 2009 periods for smaller airlines, in all likelihood as a result of the downturn in the global economy

over this period. Although the September 11 2001 attacks reduced worldwide air travel significantly,

most SADC airlines were unaffected. Other major scares such as the SARS virus and Swine flu also had

little impact on most SADC based airlines. SADC airlines more commonly encountered periodic problems

due to internal issues such as financial losses, inefficiency and safety of aircraft or due to localised

external problems such as political instability in countries where the airlines operate. It is noted that

national carriers generally split departures between international and domestic while low cost carriers

mainly undertake domestic flights.

A country by country analysis reveals that most national airlines struggle financially whilst some are

greatly affected by the political situation in the country such as Air Madagascar and Air Zimbabwe. All

airlines from the Democratic Republic of Congo (DRC) and Zambezi Airlines have been banned in

European airspace as a result of substandard safety management practices. Airlines within the SADC

that have shut down over the years due to the inability to cope with operations include Air Lesotho, Air

Tanzania and Zambia airways. Airlines with a greater number of international passengers compared to

domestic include Air Mauritius and Air Namibia. The most popular airlines within SADC with total

passenger numbers greater than 500,000 annually are Air Mauritius, South African Airways (SAA), SA

Airlink and Comair.

P a g e | xiv


International airports with greater than 1,000,000 passengers annually include O R Tambo Airport, Cape

Town International, Durban International, Dar-es-Salaam Airport, Harare Airport and Sir Seewoosagur

Ramgoolam International in Mauritius. O R Tambo Airport recorded over 10 million passengers annually.

International airports with less than 1,000,000 passengers annually include Kinshasa N’Djili, Maputo

International, Zanzibar airport, Ivato International, Windhoek International and Lusaka International.

International airports that recorded the lowest number of passengers with less than 700,000 annually

are Gaborone airport, Maun, Majunga, Lilongwe, Kilimanjaro International, Mwanza and Victoria Falls.

South Africa has the largest number of airports within SADC of which 7 are domestic airports. Port

Elizabeth airport had the largest number of domestic passengers with over 800,000 annually followed by

East London and George airports with over 400,000 domestic passengers annually.

P a g e | xv


Analysis of questionnaire results

Of 106 questionnaires sent, only 16 responses from the following were received.

Category Type of Service Offered Company / Organisation Country

Airline Airline Comair Ltd South Africa

Airline Airline Federal Airlines South Africa

Airline Airline Owenair Pty Ltd South Africa

Airline Airline Air Malawi Malawi

Airport Airport ACSA South Africa

Airport Airport NAC Zambia

Other Stakeholders Aircraft leasing and charter AirQuarius Aviation South Africa

Other Stakeholders Aircraft sales, maintenance, leasing, charter and management

National Airways Corporation South Africa

Other Stakeholders Aircraft brakes and landing gear overhauls

Mistral Aviation Services South Africa

Other Stakeholders Passenger/cargo scheduled/charter flights

Phoebus Apollo Aviation South Africa

Other Stakeholders Non-profit private association representing SADC based airlines.

Airlines Association of South Africa AASA

South Africa

Other Stakeholders Tourism and incentive charters Namibia Commercial Aviation Namibia

Other Stakeholders Passenger, freight and mail services

Precision Air Services Tanzania

Other Stakeholders Ground handling and cargo services

Swissport Tanzania Tanzania

Other Stakeholders Charter operations Proflight commuter services Zambia

An overview of the fleet size of airlines in SADC shows that South African Airways has the largest fleet

within 50 aircraft, while other national airlines such as TAAG Angla, Hewa Bora Airways, Air Madagascar,

Air Mauritius, Air Seychelles, Air Botswana, LAM, Air Malawi and Air Namibia have smaller fleet varying

between 4 and 12 aircraft each. Fleet sizes of airlines operating on domestic routes vary between 1 and

32 aircraft.

P a g e | xvi


Feedback from airlines, airports and other stakeholders was generally positive regarding an air

transportation liberalisation agreement, however most respondents stated that implementation was

poor. Full implementation has been hindered due to lack of government and SADC member

commitment to YD, Corruption, poor or substandard airport infrastructure in many countries and airport

security concerns among other factors. In order to successfully implement an air transportation

liberalisation agreement, governments will have to play an active role and stakeholders should be

afforded the opportunity to participate in the decision making. Major changes to infrastructure,

improved aircrafts, up to date avionics and transparent policies are some of the compulsory factors

necessary to ensure smooth operation of the air transportation liberalisation agreement.

The following changes in status quo are expected by airlines and airports.

Airlines Airports

Frequency of flights Increase Increase on certain routes

Capacity May increase or remain static Increase

Pricing Decrease Decrease

Volume of freight business Increase Likely to increase

Number of competitors on each route Increase on higher traffic route but will decrease on marginal routes

n/a

Market share on each route Reduce n/a

Overall, airlines, airports and other stakeholders are positive about the implementation of air

transportation liberalisation agreements but are sceptical about the progress made to date on YD and

likely to be made into the future. All the stakeholders involved support the idea behind YD and are

willing to open their markets to Africa but are not certain that the current infrastructure, legislation and

policies support the rapid implementation of such a decision.

Cost-Benefit Analysis Methodology

The economic impacts have been measured using the principles of the gravity model. However, actual

economic data between origins and destinations has been used. More specifically we’ve used GDP per

capita, urban population levels per country, city population levels and distance between origins and

destinations. Equation 2 and 3 show an example of how the various sources of economic data were used

to calculate the estimated demand for each potential route in the SADC region.

Equation (2) GDP demand airport A&B = ((GDP per capita index airport A) + (GDP per capita index airport B))/2

Equation (3) Route demand = (GDP demand airport A&B x A)+(City pop demand airport A&B x B)+(Urban pop demand airport A&B x C)+(Airport infra demand airport A&B x

P a g e | xvii


D)+(Bus, Pol & Dev demand airport A&B x E)+(Tourism infra demand airport A&B x F)

where: A + B + C + D + E + F = 100%

With the estimated demand known for each route and the use of South African aviation data (such as:

actual pricing; seats numbers available on flights; quantity of flights and distance between airports)

potential seat numbers, turnover, costs to airlines, benefits to passengers, indirect costs and tourism

impacts can be estimated for each route. The impacts have been estimated over a 50 year period, and

this is determined by staggering the potential routes by initially allowing only the routes with a high

estimated demand and then every 5 years allowing routes with lower estimated demand. At the 50 year

point all routes would be included in the impact analysis.

Cost Benefit Analysis Results

Total Benefits

Total benefits include the following: potential turnover to airlines; time saved by passengers and the

direct impact of the tourism industry on GDP. All of these have been reported in 2009 Rands and

exclusively look at the aviation industry in the SADC region. Table 1.3-1 and Figure 1.3-1, display the

total benefits experienced over a 50 year period post the implementation of air transportation

liberalisation agreement in SADC. It can be seen Table 1.3-1 that the most significant benefit brought by

an air transportation liberalisation agreement being implemented in SADC is the direct impact on the

tourism industry. Tourism is a very labour intensive industry and we can expect that over the 50 year

period that approximately 101 million jobs would be created in this industry alone.

Table 1.1-3 Total Benefits incurred by the implementation of an air transport liberalisation aagreement in SADC

Years*

BENEFITS

Potential Turnover Passenger Time Saving

(Rand per KM)

Direct Impact Of Tourism Industry On GDP (2009

Rands) TOTAL BENEFITS

5 R 395,592,569.17 R 8,070,414.24 R 7,552,340,410.36 R 7,956,003,393.77

10 R 615,030,014.60 R 14,835,378.82 R 13,205,292,139.30 R 13,835,157,532.72

15 R 631,437,961.30 R 15,242,987.56 R 13,673,144,858.21 R 14,319,825,807.06

20 R 1,055,829,325.19 R 26,510,838.22 R 28,251,360,598.84 R 29,333,700,762.24

25 R 3,194,221,298.65 R 76,673,240.19 R 50,738,372,511.99 R 54,009,267,050.82

30 R 8,886,816,358.07 R 296,141,084.61 R 105,672,816,915.10 R 114,855,774,357.77

35 R 15,354,301,000.26 R 720,722,026.57 R 165,457,639,030.49 R 181,532,662,057.32

40 R 20,306,047,606.09 R 1,242,964,240.75 R 217,448,285,885.45 R 238,997,297,732.29

45 R 21,592,032,312.26 R 1,370,343,414.87 R 228,121,055,753.45 R 251,083,431,480.59

50 R 21,804,364,460.93 R 1,395,717,456.70 R 229,837,249,446.98 R 253,037,331,364.61

P a g e | xviii


Figure 1.1-1 below graphs the total benefits over the 50 year period. The s-curve graph is to be expected

as it indicates that initially benefits are limited as the market adjusts to the new aviation regulations,

and once this adjustment is made large benefits start accruing. Finally after 35 years benefits begin to

drop off as all major routes are saturated and lower demanded flights are added to flight schedules. It

can also be seen on this figure the sheer size of the benefit experience by the tourism industry and the

slight benefit experienced by time savings to passengers.

Figure 1.1-1 Breakdown of Total Benefits incurred by the implementation of an air transport liberalisation agreement in SADC

R -

R 50,000,000,000.00

R 100,000,000,000.00

R 150,000,000,000.00

R 200,000,000,000.00

R 250,000,000,000.00

R 300,000,000,000.00

5 10 15 20 25 30 35 40 45 50

Years

Total Benefits

Direct Impact On GDP (2009 Rands)

Time Saving (Rand per KM)

Potential Turnover

P a g e | xix


Total Costs

The total costs included: cost of flight cancellation; cost of flight diversions; cost of accident resulting in fatality; cost of minor injury during flight;

cost of major injury during flight; cost of pollution; cost of noise pollution; and cost of security. These costs have been shown in Table 1.3-2 and

Figure 1.1-2. These results are shown over a 50 year period in 2009 Rands.

Table 1.1-4 Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC Years Cost of flight

cancellation Cost of flight diversions

Cost of accident resulting in fatality

Cost of minor injury during flight

Cost of major injury during flight

Cost of Pollution

Cost of noise pollution

Cost of Security Navigation Route Costs (FL 145)

TOTAL COSTS

5 R 16,598,813 R 315,380 R 81,715 R 1,258 R 17,046 R 8,913,137 R 8,843,296 R 44,638,920 R 20,021,154 R 99,430,719

10 R 30,904,372 R 694,787 R 180,018 R 2,771 R 37,553 R 13,051,508 R 15,498,560 R 77,498,801 R 30,307,051 R 168,175,421

15 R 32,305,925 R 768,933 R 199,230 R 3,066 R 41,561 R 13,398,790 R 16,227,904 R 80,718,169 R 31,258,269 R 174,921,847

20 R 52,098,054 R 1,204,203 R 312,008 R 4,802 R 65,088 R 23,030,384 R 27,259,232 R 132,556,756 R 53,547,308 R 290,077,835

25 R 101,208,861 R 2,207,197 R 571,882 R 8,802 R 119,300 R 75,339,598 R 56,797,664 R 306,044,393 R 162,721,282 R 705,018,979

30 R 223,961,750 R 4,561,179 R 1,181,796 R 18,189 R 246,533 R 225,875,003 R 136,752,000 R 753,253,360 R 473,688,910 R 1,819,538,721

35 R 356,211,205 R 7,081,210 R 1,834,733 R 28,239 R 382,741 R 413,023,162 R 231,019,712 R 1,247,466,816 R 858,029,359 R 3,115,077,177

40 R 465,155,210 R 9,153,407 R 2,371,637 R 36,503 R 494,744 R 570,231,582 R 316,170,624 R 1,656,004,414 R 1,184,967,692 R 4,204,585,812

45 R 491,444,508 R 9,652,908 R 2,501,057 R 38,495 R 521,742 R 615,124,875 R 338,780,288 R 1,754,588,698 R 1,277,056,026 R 4,489,708,596

50 R 497,433,107 R 9,766,692 R 2,530,538 R 38,948 R 527,892 R 624,335,802 R 345,253,216 R 1,777,045,809 R 1,296,504,038 R 4,553,436,042

*post implementation of an air transportation liberalisation agreement in SADC

Once again the S-curve bend can be observed in Figure 1.1-1. It can also be seen that the cost of security is by far the highest cost over the 50

year period. The cancellation costs and diversion costs could increase depending on occurrence disasters like the recent volcanic eruption in

Iceland, grounding all the aircrafts and costing airlines billions of Euros.

P a g e | xx

Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham

Muller Associates

Figure 1.1-2 Breakdown of Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC

Impact of an air transport liberalisation agreement in the Southern African

Development Community

Figure 1.1-3 shows the total impact of an air transport liberalisation agreement in SADC being

implemented in the Southern African Development community. This Figure graphs both the total

benefits and the total costs. It can be seen how marginal the total costs are in relation to the overall

economic benefit in the case of an air transport liberalisation agreement being implemented in the

SADC region.

R -

R 500,000,000

R 1,000,000,000

R 1,500,000,000

R 2,000,000,000

R 2,500,000,000

R 3,000,000,000

R 3,500,000,000

R 4,000,000,000

R 4,500,000,000

R 5,000,000,000

5 10 15 20 25 30 35 40 45 50

Year

Navigation Route Costs (FL 145)

Cost of Security


Cost of Pollution




P a g e | xxi


Muller Associates

Figure 1.1-3 The total impact of an air transport liberalisation agreement being implemented in the Southern African Development community

Impact of an air transport liberalisation agreement reflecting the investment

and capital expenditure in airport and navigational infrastructure

An air transport liberalisation is unable reach the full potential of the demand indicated in the previous

section unless there is a significant upgrade and investment to both the airport and navigational

infrastructure and equipment in the SADC region. Annual airport capacities would need to be increased

to meet the anticipated passengers expected through the various airports in the region. The information

that has contributed to infrastructural costs has been provided by Airports Company South Africa (ACSA)

and Air Traffic Navigational Systems (ATNS.)

ATNS provided a list of infrastructure required per airport based on expected demand for flights and

ACSA provided the airport capacities for each of the South African airports and indicated that for an

additional 1 million passenger capacity that the infrastructure would cost R 600 million. Table 1.1-5

below lists the various infrastructural investments in the navigational equipment and cost of creating

additional passenger capacity per airport. The column ‘benefit’s less costs’ indicates the total weekly

costs and benefits per week highlighted in previous sections over the 50 year period. Once taken into

account the infrastructural costs the column ‘Total impact after infrastructure costs’ highlights the

R -

R 50,000,000,000.00

R 100,000,000,000.00

R 150,000,000,000.00

R 200,000,000,000.00

R 250,000,000,000.00

R 300,000,000,000.00

5 10 15 20 25 30 35 40 45 50

Years

TOTAL BENEFITS

TOTAL COSTS

P a g e | xxii


Muller Associates

impact per airport. It can be seen that only 5 airports cannot meet the infrastructural costs incurred

over the 50 year period, but in total the benefits of air transport liberalisation are overwhelming and

cross subsidisation of these airport that incur negative impacts could easily make them feasiable.

Table 1.1-5 impact over 50 years after infrastructure costs are taken into account per airport Location Benefits less costs Airport

infrastructure Airport navigational systems

Total impact after infrastructure costs

Cabinda R 13,135,594,876 R 30,762,646,164 R 105,500,000 R -17,732,551,288

Catumbela R 15,135,950,379 R 21,704,608,871 R 105,500,000 R -6,674,158,492

Dundo R - R - R - R -

Huambo R 18,968,271,072 R 32,799,705,108 R 21,666,667 R -13,853,100,703

Kuito R 18,689,215,470 R 31,326,914,031 R 21,666,667 R -12,659,365,227

Luanda R 35,312,114,184 R 14,454,353,583 R 521,500,000 R 20,336,260,601

Lubango R 32,307,418,877 R 31,374,951,739 R 21,666,667 R 910,800,471

Luena R 37,396,632,803 R 27,386,961,412 R 21,666,667 R 9,988,004,724

Malanje R 33,419,030,001 R 31,857,532,089 R 21,666,667 R 1,539,831,245

Menongue R 42,194,390,670 R 30,677,820,412 R 21,666,667 R 11,494,903,591

Namibe R 52,565,917,229 R 31,967,122,412 R 21,666,667 R 20,577,128,150

Ondjiva R 55,206,012,572 R 29,117,281,210 R 21,666,667 R 26,067,064,695

Saurimo R 66,112,557,006 R 30,955,943,213 R 21,666,667 R 35,134,947,126

Soyo R 73,599,566,822 R 29,976,647,084 R 21,666,667 R 43,601,253,072

Uíge R 60,701,876,855 R 30,352,589,998 R 17,333,333 R 30,331,953,524

Francistown R 112,435,059,703 R 35,135,585,164 R 105,500,000 R 77,193,974,539

Gaborone R 126,747,019,578 R 11,489,436,347 R 521,500,000 R 114,736,083,231

Kasane R 87,449,683,593 R 27,894,701,088 R 21,666,667 R 59,533,315,838

Maun R 104,737,840,516 R 26,245,742,034 R 105,500,000 R 78,386,598,482

Bukavu R 91,974,793,085 R 20,836,679,463 R 13,000,000 R 71,125,113,622

Buta-Zega R 90,872,827,828 R 18,670,970,711 R 13,000,000 R 72,188,857,118

Gbadolite R 97,660,364,082 R 19,005,255,956 R 21,666,667 R 78,633,441,459

Gemena R 102,803,308,089 R 21,174,304,236 R 13,000,000 R 81,616,003,852

Goma R 108,712,929,432 R 21,571,107,575 R 13,000,000 R 87,128,821,857

Isiro-Matari R 120,400,614,619 R 21,672,433,831 R 13,000,000 R 98,715,180,789

Kananga R 97,178,167,198 R 23,874,821,943 R 13,000,000 R 73,290,345,255

Kindu R 102,167,901,405 R 21,663,633,278 R 13,000,000 R 80,491,268,127

Kinshasa R 146,328,475,939 R 8,183,067,357 R 521,500,000 R 137,623,908,582

Kisangani R 131,214,272,888 R 17,332,241,664 R 105,500,000 R 113,776,531,224

Lubumbashi R 155,406,013,907 R 19,548,909,955 R 105,500,000 R 135,751,603,952

Mbandaka R 127,269,799,143 R 22,957,803,412 R 13,000,000 R 104,298,995,731

Mbuji-Mayi R 125,232,224,584 R 24,753,794,341 R 21,666,667 R 100,456,763,576

Maseru R 167,101,320,224 R 15,845,658,240 R 105,500,000 R 151,150,161,984

P a g e | xxiii


Muller Associates

Antanànarìvo R 309,736,207,278 R 8,121,960,886 R 521,500,000 R 301,092,746,392

Mahajanga R 231,990,742,240 R 16,996,112,279 R 105,500,000 R 214,889,129,962

Nosy Be R 225,102,887,915 R 21,804,839,914 R 13,000,000 R 203,285,048,001

Toamasina R 295,708,091,889 R 19,094,988,396 R 105,500,000 R 276,507,603,493

Toliara R 239,258,253,432 R 22,937,552,850 R 21,666,667 R 216,299,033,915

Blantyre R 190,228,104,292 R 17,641,591,388 R 105,500,000 R 172,481,012,904

Lilongwe R 181,331,634,287 R 6,055,562,817 R 521,500,000 R 174,754,571,469

Port Louis R 606,131,604,552 R 12,345,883,086 R 521,500,000 R 593,264,221,466

Beira R 217,136,053,533 R 20,113,697,085 R 105,500,000 R 196,916,856,448

Chimoio R 170,895,781,172 R 23,705,642,728 R 15,166,667 R 147,174,971,776

Cuamba R 159,194,864,421 R 21,423,216,316 R 13,000,000 R 137,758,648,105

Lichinga R 177,744,106,905 R 23,590,797,889 R 105,500,000 R 154,047,809,016

Maputo R 285,106,971,134 R 7,783,416,063 R 521,500,000 R 276,802,055,071

Moçimboa da Praia

R 202,459,822,345 R 19,933,260,259 R 105,500,000 R 182,421,062,085

Mueda R 187,439,099,382 R 19,705,744,750 R 13,000,000 R 167,720,354,631

Nampula R 269,697,762,029 R 20,528,698,094 R 105,500,000 R 249,063,563,935

Tete R 195,888,132,266 R 23,765,714,787 R 21,666,667 R 172,100,750,812

Grootfontein R 248,492,530,242 R 21,432,237,428 R 84,400,000 R 226,975,892,814

Karabib R 221,958,472,576 R 24,282,126,981 R 15,166,667 R 197,661,178,929

Katima Mulilo R 229,639,103,367 R 28,014,954,576 R 17,333,333 R 201,606,815,458

Keetmanshoop R 309,841,858,605 R 28,306,690,157 R 17,333,333 R 281,517,835,115

Mariental R 269,882,924,036 R 27,107,878,848 R 15,166,667 R 242,759,878,521

Ondangwa R 258,900,704,039 R 27,454,733,326 R 17,333,333 R 231,428,637,379

Rundu R 257,454,998,068 R 29,184,572,233 R 17,333,333 R 228,253,092,501

Windhoek R 396,517,070,883 R 9,559,680,305 R 521,500,000 R 386,435,890,578

Seychelles R 703,501,657,625 R 8,749,277,162 R 521,500,000 R 694,230,880,462

Bisho R 554,445,228,667 R 38,724,314,820 R 105,500,000 R 515,615,413,847

Bloemfontein R 518,236,753,001 R 42,568,700,235 R 105,500,000 R 475,562,552,766

Cape Town R 850,893,805,391 R 19,395,099,853 R 521,500,000 R 830,977,205,539

Durban R 680,019,685,523 R 38,705,155,564 R 521,500,000 R 640,793,029,959

George R - R - R - R -

Lanseria R 623,425,486,875 R 50,916,414,646 R 105,500,000 R 572,403,572,229

Johannesburg R 599,808,390,969 R - R 521,500,000 R 599,286,890,969

Kimberley R 520,597,571,517 R 44,083,043,709 R 105,500,000 R 476,409,027,808

Mafikeng R 456,878,656,267 R 40,811,869,973 R 21,666,667 R 416,045,119,627

Nelspruit R 511,508,260,400 R 42,677,327,211 R 105,500,000 R 468,725,433,189

Polokwane R 459,727,696,484 R 42,265,713,353 R 21,666,667 R 417,440,316,465

Port Elizabeth R 757,947,901,871 R 41,889,245,560 R 105,500,000 R 715,953,156,311

Pilanesberg R 458,020,497,838 R 40,046,339,331 R 19,500,000 R 417,954,658,507

Umtata R 589,451,162,905 R 40,306,034,452 R 21,666,667 R 549,123,461,786

P a g e | xxiv


Muller Associates

Upington R 564,438,760,296 R 42,797,693,603 R 105,500,000 R 521,535,566,693

Welkom R 539,261,292,507 R 42,529,814,313 R 19,500,000 R 496,711,978,194

Manzini R 337,187,877,496 R 17,821,283,568 R 105,500,000 R 319,261,093,927

Dar-Es-Salaam R 640,241,051,391 R 8,424,782,414 R 521,500,000 R 631,294,768,976

Dodoma R 460,907,809,563 R 24,775,748,996 R 105,500,000 R 436,026,560,566

Kilimanjaro R 601,328,818,794 R 21,088,863,923 R 105,500,000 R 580,134,454,871

Mtwara R 463,076,216,765 R 24,211,283,510 R 21,666,667 R 438,843,266,588

Mwanza R 599,323,031,470 R 27,957,419,377 R 21,666,667 R 571,343,945,426

Zanzibar R 575,823,890,548 R 27,027,185,021 R 521,500,000 R 548,275,205,528

Kitwe R -770,778,388 R - R - R -770,778,388

Livingstone R 370,996,780,292 R 18,800,111,355 R 105,500,000 R 352,091,168,937

Lusaka R 456,850,384,931 R 8,921,260,504 R 521,500,000 R 447,407,624,427

Mfuwe R 95,333,266,016 R 8,502,307,049 R 8,666,667 R 86,822,292,300

Ndola R 430,933,005,132 R 27,766,951,019 R 21,666,667 R 403,144,387,446

Bulawayo R 307,810,325,118 R 23,414,456,928 R 105,500,000 R 284,290,368,191

Harare R 382,745,641,210 R 6,518,897,873 R 521,500,000 R 375,705,243,338

Hwange R 238,906,513,453 R 17,155,638,949 R 21,666,667 R 221,729,207,837

Victoria Falls R 228,987,817,785 R 10,761,251,323 R 105,500,000 R 218,121,066,462

TOTAL R 24,566,019,405,225 R 2,133,076,262,959 R 12,076,400,000 R 22,420,866,742,266

Conclusion

The literature review and impact analysis have both overwhelmingly demonstrated the positive effects

of implementing an air transportation liberalisation in the SADC region. However, there are a few issues

that need to be considered before implementing an air transportation liberalisation agreement:

The establishment of a competition authority, with the power to penalise countries and airlines acting in ways that are un-competitive.

The inevitable market share decline of national flag carriers and in some cases the closing of unprofitable nation flag carriers. This will, in all likelihood save taxes.

The emergences of privately owned low cost carriers as the dominant airlines within the region.

The shifting of connector flights away from historical hub airports.

Substantial new investment in airports within SADC and in additional infrastructure, skills and capacity (including aircraft) to take advantage of an air transportation liberalisation.

P a g e | 1


Muller Associates

Introduction

This report has been prepared for the South African Department of Transport.

The report summarises the methodology and findings of an investigation into the impacts of

implementing air transportation liberalisation legislation in the form of implementation of an air

transport liberalisation agreement throughout the Southern African Development Community (SADC)

region.

The report has been divided into two parts:

1) The first part (Section 1) investigates the current literature regarding air transportation

liberalisation and the effects and impacts experienced in other countries and regions around the

world;

2) The second part (Section 2) of the report takes some of the lessons learnt from the first section

and applies these in an analytical and modelling study to forecast the impact of air

transportation liberalisation legislation being introduced in the SADC region in the form of

implementation of an air transport liberalisation agreement throughout the Southern African

Development Community (SADC) region.

P a g e | 2


Muller Associates

1 Literature Review

1.1 Introduction

Air transportation liberalisation agreements are concerned with the liberalisation of aviation regulations

and agreements between countries. This report comprises a review of the current literature regarding

the economic impacts of air transportation liberalisation agreements and of the consequences and

potential risks of adopting air transportation liberalisation agreements. This report is primarily

concerned with setting the back drop to assessing the impact of an air transportation liberalisation

agreement on Africa in the Southern African Development Community (SADC).

Key to this study is the African air transportation liberalisation initiative known as the Yamoussoukro

Decision (YD) launched in 1999. Although this initiative is now more than a decade old, little of it has

been implemented and the aviation market within Africa remains largely closed, regulated and

dominated by national flag carriers. There has been limited political will in implementing YD in the

various African regions and the wider continent. YD relates to the liberalisation of access to the aviation

market in Africa and seeks to achieve:

Unrestricted access to all air routes;

Elimination of restriction on capacity, frequency on any route and in operation in any international markets;

Elimination of restriction on charters;

Liberalization of air cargo rules;

Doing away with restrictions on the conversion of revenues to hard currency and repatriation of revenues;

Agreement on code sharing;

Permitting carriers to have their own ground service abroad; and

Termination of regulations on carriers’ alliance.

At the time of writing this report literature available on air transportation liberalisation agreements and

the Yamoussoukro decision was limited and lacking in economic quality. Furthermore, most of the air

transportation liberalisation literature is focussed on developed countries (the United States, the

European Union and the United Kingdom) and thus the analysis is more applicable to highly developed

countries and regions. The emphasis on developed country studies is somewhat to be expected,

however aviation markets of these regions are double the size of those in the rest of the world. More

specifically, the African aviation market is only 7.45% of the size of the North American aviation market

and 8.34% of the size of the European aviation market, as seen in Figure 1.3-3. Therefore, the

anticipated impact of an air transport liberalisation agreement in SADC would be a fraction of that

experienced in developed regions where air transportation liberalisation has been adopted.

P a g e | 3


Muller Associates

The report is structured as follows:

Section 1.2 examines the nine ‘freedoms of the air’ that make up a typical air transportation

liberalisation agreement.

Section 1.3 looks briefly at the history of aviation and the history of aviation agreements,

starting with the Chicago Convention of 1944 and concluding with an in depth analysis of the

Yamoussoukro Decision of 1999 (Africa’s air transportation liberalisation initiative).

Section 1.4 reviews five methods that can be used to assess or forecast the impacts of aviation

agreements.

Section 1.5 reviews three case studies that detail the impacts of implementing air transportation

liberalisation agreements. These case studies review the United States and the United Kingdom;

the European Union; and India and the United Kingdom. Included is research conducted by

InterVISTA-ga2 in 2006, which attempts to determine the global impact of every country

liberalising their aviation regulations.

Section 1.6 discusses two significant research reports which highlight some important

considerations regarding the economic impact of air transportation liberalisation agreements.

Finally section 1.7 concludes the analysis by highlighting the implications of the report for

Southern Africa.

1.2 The nine freedoms of the air

As a point of departure it is important that the nine freedoms of the air are clearly defined, as they will

be referred to throughout the remainder of this study. Aviation agreements between countries and

within regions can consist of up to nine freedoms of the air. Table 1.2-1 overleaf explains each of the

nine air freedom rights in a typical aviation agreement between two nations or a region.

Freedom Rights 1 - 4 are known as traditional bilateral aviation regulations that have been in place since

the Chicago Convention of 1944 (discussed overleaf), whereas Freedom Rights 5 - 9 are the more recent

air transportation liberalisation regulations being pursued by a number of countries and regions.

Freedoms 5 – 9 are far more liberal and give airlines and airports far more flexibility and possibilities.

For a complete list of countries with air transportation liberalisation agreements with the United States

in place please refer to Appendix B.

P a g e | 4


Muller Associates

Table 1.2-1 Definition of air freedom rights

1st Freedom

To overfly one country en-route to another

2nd Freedom

To make a technical stop in another country

3rd Freedom

To carry freight and passengers from the home country to another country

4th Freedom

To carry freight and passengers to the home country from another country

5th Freedom

To carry freight and passengers between two countries on route (by an airline of a third (home) country) with origin / destination in its home country

6th Freedom

To carry freight and passengers between two countries by an airline of a third country on two routes connecting in its home country

7th Freedom

To carry freight and passengers between two countries by an airline of a third country on a route with no connection with its home country

8th Freedom or Cabotage

To carry freight and passengers within a country by an airline of another country on a route with origin / destination in its home country

9th Freedom or True Domestic

To carry freight and passengers within a foreign country with no connection with the home country

More recent air

transportation

liberalisation

regulations

Traditional bilateral

aviation regulations

3rd Freedom 5th Freedom

Source: ICAO Manual of Regulation (2004) and

WTO Secretariat

P a g e | 5


Muller Associates

1.3 History of aviation agreements

Aviation as a mode of transport has grown increasingly in importance over the last century, ever since

the Wright brothers took their first controlled flight on 17 December 1903. Less than a decade later

aircraft were being used in World War I for reconnaissance and attacks against both ground positions

and enemy aircraft. The first aircraft to start transporting people and cargo over long distances were

known as Zeppelin blimps or airships. This short lived technology came to an end in 1937, when the

Hindenburg Zeppelin blimp crashed killing 36 people (Bryan, L.A, Taylor, M.S, 2006).

The 1920’s and 1930’s saw great advances within the aviation industry, such as the first transatlantic

flight in 1927 and the first transpacific flight a year later. By the start of the World War II many towns

and cities had built airports, and there were many qualified pilots. World War II brought about a number

of advances in the aviation industry, such as the first jet aircraft and the first liquid fuelled aircraft.

During World War II the importance of modern aviation was recognised and a conference was convened

to agree on aviation regulations. This conference, known as the Chicago Convention of 1944, resulted in

regulations that have governed international aviation law and bilateral agreements between countries

for the second half of last century (Bryan, et al, 2006).

1.3.1 Chicago Convention 1944

The Chicago Convention of 1944 was attended by 54 states (see Appendix A for a list of countries that

attended the Chicago Convention) but ended in 52 states signing the Convention on International Civil

Aviation. The signed convention was a list of international aviation regulations, standards and

procedures decided on by participating nations.

The regulations, standards and procedures dealt with included: communications systems and air

navigation; airport characteristics; rules of the air and airport traffic control; air worthiness of aircrafts;

licensing and operation and mechanical personnel; aeronautical maps and charts; log books; and

measures to facilitate air navigation (Bryan, L.A., et al; 2006).

Most importantly, the convention affirmed that every nation has sovereignty over the airspace above its

territory and that “every civil aircraft must be registered, carry the nationality of the country of

registration, and bear appropriate identification markings” (Bryan, L.A., et al; 2006). However, the

convention also granted transit rights and permitted non-scheduled, charter, and private flights. Transit

rights refer to the right to fly over another nation’s territory and to the right to land for non-traffic

purposes, such as refuelling (1st to 4th freedoms of the air, see Section 2, above.)

The Chicago Conference agreed that a regulatory body should be established to ensure that the

contracting states implement and abide by the regulations, standards and procedures decided upon at

the convention. This was the initial formation of the ‘International Civil Aviation Organisation’ (ICAO).

The ICAO was formally established in 1947 as an agency of the United Nations linked to the Economic

and Social Council (ECOSOC). The Chicago Conference set forth the purpose of ICAO as:

P a g e | 6


Muller Associates

"The future development of international civil aviation can greatly help to create and preserve friendship

and understanding among the nations and peoples of the world, yet its abuse can become a threat to the

general security; and it is desirable to avoid friction and to promote that co-operation between nations

and peoples upon which the peace of the world depends; therefore, the undersigned governments having

agreed on certain principles and arrangements in order that international civil aviation may be

developed in a safe and orderly manner and that international air transport services may be established

on the basis of equality of opportunity and operated soundly and economically.”

(Preamble to the Convention on International Civil Aviation - Chicago, 7th December 1944)

The ICAO’s primary mandate was to foster development and promote co-operation in international civil

aviation. The major success of the convention was that it greatly advanced aviation safety and standards

as well as helping to foster bilateral aviation agreements between participating states.

1.3.2 Formation of state owned or sponsored airlines

The formation of state owned or sponsored flag carrier airlines (such as South African Airways)

operating out of a hub airport (such as O.R. Tambo Airport), is a result of the regulations set out by the

Chicago Convention. Traditional aviation agreements between countries help protect flag carrier airlines

by defining the landing rights allowed, restricting the number of flights on a particular route, restricting

the amount of freight or passenger seats available and restricting foreign airlines to specific airports.

Therefore, flights are directed through a specific airport, as illustrated in figure 1.3-1, below. As can be

seen in this figure an overwhelming majority of South African Airways flights are directed through O.R.

Tambo International Airport in Johannesburg.

Figure 1.3-1 South African Airways International Route Map

Source: http://www.airlineroutemaps.com/Africa/South_African_Airways.shtml, accessed October 2009

http://www.airlineroutemaps.com/Africa/South_African_Airways.shtml

P a g e | 7


Muller Associates

Illustrated in Figure 1.3-1, airlines have traditionally operated out of a central hub airport to various

destinations around the world. Therefore, if a person wants to travel from Windhoek (Namibia) to

Lusaka (Zambia) on South African Airways, they would need to fly first to Johannesburg before

transferring to a flight to Lusaka. The trip to Johannesburg not only adds unnecessary time to the

journey, but adds significant cost in airport taxes and flight costs.

State sponsorship or ownership of international flag carrier airlines is still very prevalent in Africa and a

list of flag carriers and level of state ownership can be found in Appendix C. More than 50% of national

flag carriers listed in Appendix C are still owned or funded by the state.

1.3.3 Liberalisation of aviation agreements

Since the Chicago Convention of 1944, aviation technology has accelerated rapidly. Today modern

aircraft are far more efficient in terms of speed, service and safety than in the past. However, due to

aviation regulations between countries not modernizing in tandem with technology and increased levels

of globalisation, these improvements in the aviation industry have had a somewhat limited impact on

the commercial aviation market. The InterVISTA-ga2 report highlights this in the following passage:

“Commercial aviation still faces a challenge common to many of the newer and technically advanced

areas of our society. Our social and political institutions have not kept pace with the evolution of

technology or the needs of the public. Commercial aviation remains encumbered by well-meaning but

outmoded and arcane rules, principles and institutions. They often prevent fit, willing and able airlines

from fully serving passengers and shippers who are completely willing and able to pay. They also impose

protective machinery that frustrates innovation and directs the evolution of the industry into a contrived

and artificial structure. By sheltering airlines from market forces, they reduce the incentives to pass on to

passengers, shippers and investors the benefits of improved technologies.”

When aviation regulations were created in the first half of last century, aircraft technology, speed and

safety were limited and expensive. This encouraged formation of national flag carrier airlines that were

either state-owned or state-subsidised. Airlines were treated and run as pure monopolies (within nation

states) and cartels internationally, requiring state assistance and regulation to survive. However, as

technologies and efficiencies in the aviation industry have improved and become accessible, the overall

costs of operating airlines have decreased.

The airline market can best be explained by Figure 1.3-2 overleaf, which shows the demand curve for a

pure monopoly and a monopoly.

P a g e | 8


Muller Associates

Figure 1.3-2 Demand Curve for both a Pure and Normal Monopoly

When aircraft technology was expensive and airline efficiency was severely limited compared with

today, airlines were treated as pure monopolies or members of cartels that needed to be protected and

subsidised or owned by government. Thus Part A of Figure 1.3-2 shows that the average cost of an

airline, characterised as a pure monopoly, is higher than the price, resulting in economic losses. This is

due to inefficient technologies which were too costly for commercial viability. To ensure the survival of

an industry or company operating under conditions of pure monopoly, it is essential that it is subsidised

by the difference of P2 and P1. Therefore, in order for countries to access the global market, it was

essential for governments to meet this short fall in the operating costs of national flag carrier airlines.

In today’s world where aviation technology is more advanced and accessible, average costs have

decreased and the market can better be described as a monopoly. It can be argued that the average

costs of the airline industry have decreased to levels where average costs are now lower than price.

National flag carrier airlines operating as monopolies seek to maximise profit through offering a sub-

optimal quantity of seats. This profit can be seen in Part B of 1.3-2, namely the difference of P1 and P2. In

an open and competitive market, national flag carrier airlines would be forced to operate at competitive

equilibrium (where the marginal cost line, average cost line and average revenue/demand line

intersect). As can be seen in the figure, competitive market forces would determine equilibrium at price

PE (lower than that of the price set by a monopoly) and quantity of seats QE (higher than the quantity set

by a monopoly), directly benefiting consumers of air transport and freight.

Airlines have not only functioned as monopolies in the last 15 years, but also as oligopolies on routes

that are shared with competing airlines. Airlines collaborate with each other to reduce competition and

keep prices high on certain routes, thus increasing the profit made. In an open competitive market, both

P a g e | 9


Muller Associates

airlines would undercut each other prices and improve their services and capacity on those routes,

thereby making air travel more accessible.

Thus, the focus of the international aviation community over the last 15 years has been on liberalising

aviation agreements between countries and opening up the airways, to eliminate this market

inefficiency that is ultimately being paid for by the consumer.

1.3.3.1 Air Transportation Liberalisation Agreements

The United States started pursuing the first air transportation liberalisation agreement in 1972. By 1983

the country had signed 23 bilateral air service agreements. European states followed suite in the 1990s

by opening up their airspaces to other European nations (discussed in Section 1.5.2 further on). In 1992

a massive step was taken towards liberalising air regulations when the US signed an air transportation

liberalisation agreement with the Netherlands. This agreement gave each country unrestricted landing

rights.

Air transportation liberalisation has been more vigorously pursued by the international community over

the past 15 years, particularly at a regional level. Prior to 1994 there were just two regional air

transportation liberalisation agreements, namely the European Union that included 15 member states,

and the Andean Pact that comprised of five South American states (ICAO, 2005). Since 1995, eight more

regional arrangements have emerged:

The Caribbean Community (CARICOM) Air Service Agreement amongst 15 States in the

Caribbean (1996, entry into force in 1998 for nine States);

The Fortaleza Agreement amongst six states in South America (1997);

The Banjul Accord amongst six states in Western Africa (1997, a separate more liberal

multilateral agreement was signed among seven States in 2004);

The CLMV Agreement by Cambodia, Lao People’s Democratic Republic, Myanmar and Viet Nam

(1998, a formal multilateral agreement was signed in 2003);

The Intra-Arab Freedoms of the Air Programme amongst 16 States of the Arab Civil Aviation

Commission (ACAC) in the Middle East and Northern Africa (1999);

MALIAT – Multilateral Agreement on the Liberalisation of International Air Transportation

(MALIAT) between Brunei, Chile, New Zealand, Singapore and the United States

An agreement amongst the six States of the Economic and Monetary Community of Central

Africa (CEMAC) (1999);

An agreement amongst the 20 States of the Common Market for Eastern and Southern Africa

(COMESA) (1999); and

The Yamoussoukro II Ministerial Decision amongst 53 African Union States (1999, entry into

force in 2000).

Of the eleven agreements listed above, eight have been fully implemented or are in the process of a

gradual implementation. The last three in the above list require further discussion or decisions made by

P a g e | 10


Muller Associates

the various governments, one of these being the air transportation liberalisation initiative for Africa the

Yamoussoukro Decision. An attempt has been made to find more information on these regional air

transportation liberalisation agreements; however the literature available is either in a foreign language

or does not give the detail required for analysis. There is no literature available for the Africa air

transportation liberalisation agreements.

1.3.3.2 The Yamoussoukro Decision

The structure of the aviation market in Africa over the last three decades has been shaped by protective

bilateral agreements between states, where free market economic logic has played an limited role. The

majority of African states have moved towards bilateral aviation agreements and regulations that

ensure the protection of national flag airline carriers (Economic Commission for Africa, 2001). There has

been a limitation on the agreement of 3rd and 4th air freedoms (air freedoms are explained in Section

1.2) and reluctance to authorise technical landing for flights continuing to other destinations. The

majority of African countries designated flag carriers enjoy exclusive monopolistic rights in these

markets. The consequence of this has been a limited improvement in the quality and quantity of air

services throughout the continent. In addition, the vast majority of African airlines either have

government as a majority or full shareholder. This has been demonstrated in the table provided in

Appendix C, listing every airline in the world and whether these airlines are owned, partly owned or

subsidised by their governments.

Figure 1.3-3 overleaf shows the total number of domestic and international airline passengers, by

region. As can be seen from the figure, Africa has significantly smaller volumes of passenger seats being

purchased, at 114 million seats in 2006, than the developed regions of North America, Europe and Asia -

at 1529 million, 1367 million and 980 million passenger seats respectively. Latin America and the

Caribbean is almost double the size of Africa, at 272 million passenger seats, with only the Middle East

showing similar market size at 111 million seats in the year 2006.

African ministers took significant steps forward in liberalisation of the African airspace when they signed

the Yamoussoukro Decision (YD) in 1999. The intention was that YD would be achieved by gradual

liberalization of scheduled and non-scheduled intra African air transport services, thus leading to the

emergence of a viable and quality African air transport that meets the imperatives of the consumers of

air services (African Union, 2005).

The general aim of YD is to encourage co-operation among African states through air transportation

policies that encourage deregulation of the aviation industry, promoting competition on routes and

reduced airfares between African destinations. YD promotes fundamental changes in the nature and

operation of airlines, in national economies, in tourism and in relationships between African states

(SSamula B. & Venter C., 2005). YD gave the Economic Commission for Africa (ECA) and the ICAO the

responsibility of implementing the agreement between the various African states.

P a g e | 11


Muller Associates

Figure 1.3-3 Total number of domestic and international airline passengers, by region

Source: ICAO, 2007

YD advocates the following:

That only African owned airlines would benefit from the implementation of YD

The granting of 1st to 5th air freedom rights (as well as cabotage, the 8th air freedom rights);




The elimination of all protective policies that protect national flag carriers;





The ECA and ICAO are not the only institutions that are interested in the liberalisation of the African

skies. Figure 1.3-4 overleaf highlights the relationship of the various organisations and structures that

are responsible for the implementation of YD

40

.8

31

8.9 5

46

.2

47

.8

74

1.8

83

.5

60

.9

66

5.5

74

3

79

.1

11

04

.9

13

4.5

11

4

98

0

13

67

11

1

15

29

27

2

0

200

400

600

800

1000

1200

1400

1600

1800

Afr

ica

Asi

aPac

ific

Euro

pe

Mid

dle

Eas

t

No

rth

A

mer

ica

Lati

n A

mer

ica

and

C

arib

bea

n

Passengers (millions)

1989

1999

2006

D e p a r t m e n t o f T r a n s p o r t P a g e | 12

Impact of the Yamoussoukro Decision: 6th April 2010 - report prepared by Graham Muller Associates

Figure 1.3-4 Break down of the Yamoussoukro Decision implementation organs

Source: SSamula B. & Venter C., 2005



Full aviation liberalisation proposed by YD was expected to be completed by 2002 with a total removal

of restrictions on traffic rights (including 5th air freedoms), as well as removal of capacity constraints

between origins and destinations, non-regulation of tariffs by government, multiple designations, and

complete liberalisation of cargo and non-scheduled air services (Economic Commission for Africa, 2001).

Also by 2002 a monitoring body would have been formed to oversee and enforce the various YD

agreements.

All in all YD had a number of very good intentions for the African continent; however it has faced

significant obstacles in realising the potential gains and implementation has largely failed. The reasons

for this failure are highlighted in an African Union Report (2005):

Confusion in the monitoring body of the Yamoussoukro Decision

o The African Union (AU) is named as chair of the monitoring body, but has been given

equal status to the other specialised African institutions such as the African Airlines

Association (AFRAA), the African Civil Aviation Commission (AFCAC) and Regional Trade

Organisations (RTOs).

o The roles of these specialised African institutions are unclear and they are cited only as

members, resulting in confusion as to responsibilities.

o Furthermore the RTOs are mentioned as back-up to the AU, which is not practical as

these bodies would primarily be responsible for ensuring the implementation of YD at a

regional level.

Conditions for eligibility of airlines in the Yamoussoukro Decision are inadequate. These

conditions allow any airline which has “its headquarters, central administration and principal

place of business physically located in the state concerned” to be eligible to benefit from the

advantages set forth in the Yamoussoukro Decision. Such an airline may be totally or in most

part controlled by foreign capital or interests. The European Union has put in place very

restrictive conditions in terms of eligibility so as to protect the airlines of its community.

YD makes no mention of economic control of eligible airlines - there should be a provision in YD

requiring airlines to avail to audit boards all accounting and financial documents to ascertain

their economic status. These audit boards do not exist.

Competition rules as contained in the Yamoussoukro Decision are inadequate. Competition

rules need to be defined further and the following prohibitions need to be made:

o No direct or indirect state or parastatal subsidies.

o No private financial aid that is not consistent with generally accepted rules and

regulations governing private financing.

o Equal access of all community airlines to state or parastatal markets (travels of state or

parastatal officials, tenders and pilgrimages)

o Ban on abuse of dominant positions.

o Clear and equitable rules for the allocation of time slots through the establishment of a

time slot co-ordination body comprising airport authorities, airlines and civil aviation

authorities.

P a g e | 14


Muller Associates

o Establishment of an African Union level body to ensure implementation and compliance.

o Authorities responsible for the implementation of the Yamoussoukro Decision lack

resources and co-ordination for the attainment of the objectives set in the short term -

The monitoring body requires adequate financial resources and political support to

enable it to fully play its role.

For the most part of the last decade the implementation of YD has moved at slower pace than expected

and is still far from being implemented in most regions of Africa and the continent itself. Progress has

been made amongst many of the West African countries and domestically within South Africa.

Furthermore, a number of countries have opened their skies to the United States; among these are

Morocco, Nigeria, Ghana, Senegal, Tanzania, Namibia, Burkina Faso, Gambia and Benin (see Appendix B)

Both Ethiopia and Kenya have entered into air transportation liberalisation negotiations with the United

States.

1.3.3.3 African Aviation Competition Authority

For a successful implementation of an air transport liberalisation agreement, a proper competition

authority is required to monitor that no airline acts in an uncompetitive, monopolistic or oligopolistic

manor. Without a monitoring body national flag carriers who have dominated the aviation market in

Africa could uncompetitive restrict the access of new low cost carriers. Dominant airlines in the region

(such as South African Airways) could also exert unnecessary pressure on smaller airlines.

It is necessary that a competition authority be setup by the regional political body such as the South

African Development Community. The competition authority should comprise of employees/members

from the various members states of the agreement, if this is not possible each state must be in full

agreement with the staff/member complement of the competition authority. It is absolutely essential

that the competition authority be given full political support of each member state and the power to

prosecute airlines that act in an uncompetitive manor. Without any of these commitments establishing

an aviation competition authority is pointless.

The completion rules have already been stated, but are worth repeating:

o Only airlines operating in SADC should benefit from the implementation of air transport liberalisation agreement in SADC

o The granting of 1st to 5th air freedom rights in each member state (as well as cabotage, the 8th air freedom rights);

o Encourage the development of new routes;

o Ensure the removal of capacity restrictions on passenger seats, freight and flights on certain routes;

o Ensure the removal of expensive and complex tariff regulations;

o Ensure the elimination of all protective policies that protect national flag carriers;

P a g e | 15


Muller Associates

o Ensure the termination of regulations on carriers’ alliance;

o Remove restriction on the conversion of revenues to hard currency and repatriation;

o Agree on code sharing;

o Allow carriers to have own-ground-service abroad;

o Not allow any direct or indirect state or parastatal subsidies;

o Not allow private financial aid that is not consistent with generally accepted rules and regulations governing private financing;

o Allow equal access of all community airlines to state or parastatal markets (travels of state or parastatal officials, tenders and pilgrimages);

o Ban on airlines who abuse a dominant positions;

o Clear and equitable rules for the allocation of time slots through the establishment of a time slot co-ordination body comprising airport authorities, airlines and civil aviation authorities.

1.4 Assessing and forecasting the impact of air transportation liberalisation

agreements

There are various methods that have been used to evaluate and forecast the impact of air

transportation liberalisation agreements on aviation markets. Methods include: the case study

approach; the trends model; gravity models; stimulation models and air transportation cost analysis

(Swan, 2008). These methods predict or analyse the growth in aviation markets if regulations were

liberalised, thereby making it possible to understand how growth is being restricted in regulated airline

markets. Each method has its limitations and takes into account different aspects predicting the effects

of air transportation liberalisation agreements. The various approaches that can be used are discussed in

detail in this section. Graham Muller Associates incorporated various aspects of these methods when

predicting the impact of air transportation liberalisation agreements in SADC region.

1.4.1 The case study approach

The case study approach is relatively simple and looks at actual data. Of all the existing methods, it is the

only method that does not forecast or predict future growth. The case study approach analyses

passenger seats, freight by tonnage and air fares before and after air transportation liberalisation

agreements have been implemented. This is a crude analysis of air transportation liberalisation

agreements as it does not fully take into account the market size, distances between countries, level of

airport infrastructure and the proportion of the urban population with access to airports. This analysis

has a limited applicability to nations considering air transportation liberalisation agreements, as country

conditions often differ drastically. This method tends to be the most common analysis used in the

literature reviewed. Various case studies are discussed in Section 1.5 further on.

P a g e | 16


Muller Associates

1.4.2 The trends model

The trends model uses statistical regression analysis to isolate the effects of travel against an economic

activity such as GDP. This model uses historic travel, flight and GDP data to forecast future aviation

industry growth. Therefore the model does not recognize changing conditions like air transportation

liberalisation agreements that increase the amount of passenger seats and freight tonnage as shown in

the case studies reviewed below. GDP is used to explain growth in air travel, there is no dependence on

other causal activities, such as price, service, trade, distance, regulations or airport infrastructure. Thus

results using this method are often unreliable and if a country is still operating under regulated aviation

agreements the method will not account automatically for the growth brought about by deregulation.

(Swan, 2008). This can always be catered for in a more complex model.

1.4.3 The gravity model

While the trends model constrains the forecast by not being able to account for regulation changes, the

gravity model is an unconstrained forecast that determines total demand in a deregulated air market.

The gravity model uses the size of the origin (city or country) times the size of the destination as an

indication of the demand for flights between them. This model assumes that the bigger the population

size of the origin and the population size of the destination, the bigger the attraction and demand for

flights. Sizes of the origin and destination are measured in population, GDP or number of

passengers/freight traveling by air.

The model does not account for distance and therefore ignores the impact expected when the origin

and destination are further apart and the flights demanded diminish. Therefore in some instances the

distance between the origin and destination can be used to further calculate the estimated demand of

flights on a particular route (number of flights or airline operating on routes is not taken into account.)

Equation (1) shows the most classical form of the gravity model calculation.

Equation (1) Demand = (Pop Origin * Pop Destination)/Distance

The problem with this model is that it tends to overstate or understate demand on certain routes. This

model also assumes that bigger populations consume more air travel, which is only a valid assumption

provided that the majority of the population is earning a salary that permits them to consume air travel.

Figure 1.4-1 overleaf shows the ratio between the gravity model’s forecasted amount of air travel

consumed and the actual amount of air travel consumed in the European region. For this to be an

accurate method of forecasting the majority of the points should be located around the horizontal line

at 1.0. Instead, for the majority of these routes there was far more air travel consumed than forecasted

(Swan, 2008).

P a g e | 17


Muller Associates

Figure 1.4-1 Gravity forecast fails to fit actual data, European Region

Source: Swan, W. 2008

1.4.4 The stimulation model

The stimulation model estimates the increase in air traffic arising from changes in fares and service

levels. This model requires good data on how the volume of air tickets purchased changes as the price of

these tickets changes. The model could have problems in forecasting air traffic levels where the base

data is taken from an airport or airline running at full capacity. Generally the type of data required for

this analysis is not available or there is inadequate historical data on how price changes have affected air

traffic (Swan, 2008).

1.4.5 Air transport cost analysis

There has only been one study to date that uses various sources of historic data to run regressions

analysing the main contributors to air transportation costs. This is not a reflection of the merit of the

approach, but is likely to be a result of the extensive data requirements of a fully comprehensive cost

analysis. This approach is discussed in detail in Section 1.6.1 further on. Cost analysis is able to take into

account distance, total volume, value per unit weight of cargo, foreign airport infrastructure, regulatory

quality, as well as whether or not an air transportation liberalisation agreements existed between the

countries involved and to what extent air freedoms were allowed in this agreement.

P a g e | 18


Muller Associates

1.5 Case Studies

This section examines three case studies with respect to the impact that air transportation liberalisation

agreements have had on each country. These case studies look at the United States and the United

Kingdom, the European Union, and finally India and the United Kingdom. It is important to note from the

outset of this section that all the case studies discussed below instituted 1st to 5th air freedoms, as well

as allowing cabotage the 8th air freedom, when liberalising their aviation markets.

1.5.1 United States – United Kingdom

The United States (U.S.) and United Kingdom (U.K.) aviation agreement is complex and somewhat

contentious. While this agreement is liberal in some aspects it is still restrictive by limiting access to

Heathrow and Gatwick airport. In the years leading up to the 1990’s U.K. – U.S. air traffic represented

one third of all U.S. – E.U. traffic. During the 1990’s, the U.S. and the U.K. liberalized the traditional

agreement that had been in place since 1978. As part of that agreement, the U.S. - U.K. market was

deregulated, with the exception of Heathrow and Gatwick airports. Otherwise, carriers could operate

any city pairs, and at pricing that was commercially determined. Both the U.S. and the U.K. have globally

dominant aviation markets and large economies, which tends to make aviation agreements involving

these two counties fairly problematical. Both states attempted to sway the agreement in their favour

and maintain or grow their market share.

The liberalisation of the air market between the U.K. and the U.S. led to capacity growth on then trans-

Atlantic route at a compound annual rate of 7.8%. The market share in passenger seats over the Atlantic

shifted over a ten year period from 48% U.S. flag carriers in 1990 to 58% U.S. flag carrier in 2000. At the

end of 2005, the U.S. had lost a slight portion of this gain with market share over the transatlantic falling

back to 56%. Figure 1.5-1, overleaf, demonstrates graphically the number of passenger seats for both

U.S. and U.K. carriers between the periods 1990-2005. A decrease in passenger seats between 2001 and

2002 can be attributed to the 11 September 2001 attacks in the U.S. and the outbreak of the Severe

Acute Respiratory Syndrome (SARS) virus in 2002.

It is estimated that the air transportation liberalisation agreement between the U.S. and U.K. is

responsible for stimulating 9,197 full-time equivalent jobs in the United States and over 16,700 full-time

equivalent positions in the United Kingdom. It is also estimated that the gross domestic product of the

United States also expanded by $747 million due to the agreement and the United Kingdom by roughly

$970 million. InterVISTA-ga2, 2006, estimated that a full air transportation liberalisation agreement

between the U.S. and the E.U. would result in a 29% increase in traffic, due to increased passenger

volumes between the U.S. and Heathrow and Gatwick airports. The economic benefits of a complete air

transportation liberalisation agreement would also mean that “117,000 full-time equivalent positions

would be created and the GDP of the two countries would grow by roughly $7.8 billion” in 2006

(InterVISTA-ga2, 2006.) Subsequent to the InterVISTA-ga2, 2006 report, the U.S. negotiated an air

transportation liberalisation agreement with the E.U. that has paved the way for the U.S. to enter into a

complete air transportation liberalisation agreement with the U.K.

http://en.wikipedia.org/wiki/Severe_acute_respiratory_syndrome

http://en.wikipedia.org/wiki/Severe_acute_respiratory_syndrome

P a g e | 19


Muller Associates

Figure 1.5-1 Air market share between U.S. carriers and U.K. carriers

Source: adapted, InterVISTA-ga2, 2006

1.5.1.1 A limited air transportation liberalisation agreement with the U.S.

The E.U. air transportation liberalisation agreement with the U.S. has been criticised due to E.U.

companies being restricted such that they cannot obtain more than 25% of voting rights in US aviation

companies. On the other hand U.S. companies can acquire more than 50% of any E.U. aviation company

or airline (www.wharton.universia.net, 2009).

E.U. airlines are allowed to fly from any European Airport to any U.S. Airport, but cabotage within the

U.S. is completely restricted. On the other hand U.S. airlines are not only allowed to fly from any U.S.

Airport to any E.U. Airport, but cabotage within the E.U. is permitted.

British Airways has indicated that under an air transportation liberalisation agreement with the US it has

the most to lose, as 40% of transatlantic flights from Europe depart from Heathrow Airport which has

been deregulated. E.U. leaders (in particular the U.K. leaders) believe they can push the U.S. to review

the limitations of the agreement in 2010 when the air transportation liberalisation agreement is

revisited.

These restrictions are destroying competition and already DHL (a European based freight company)

cannot compete against U.S. freight companies. In this regard, DHL has closed down its U.S. branch,

0

2000

4000

6000

8000

10000

120001

99

0

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

Nu

mb

er o

f Se

ats

(00

0s)

US Flag Capacity Total US-UK Capacity

http://www.wharton.universia.net/

P a g e | 20


Muller Associates

which means that some 8000 U.S. jobs have been lost. Furthermore it has now outsourced its aviation

services to ABX Air & ASTAR (both of these are US based freight companies) (Brown, 2008).

1.5.2 The European Union

The European Union signed an internal air transportation liberalisation agreement in 1992, called the

‘Single Aviation Market’; this was signed by the 12 member states at the time. The InterVISTA-ga2, 2006

report looked at the impact of this deregulation on the European Community market as a whole and the

impact of this deregulation on a number of selected air routes from Germany.

The process of liberalising aviation regulations was spread between 1987 and 1992, as it was resisted by

various member states and the entire aviation industry. The 1992 legislation was the third of three

packages. The first two (1987 and 1990) retained the bilateral system. Table 1.5-2 shows a summary of

the Intra-EU transport packages, the three air legislation agreements (1987, 1990 and 1992) and the

various aspects of this agreement.

The three stages of liberalisation in the E.U. aviation market and the dates that these agreements came

into force have been displayed in the three columns on Table 1.5-2, overleaf. The columns display how

over a 4 year period:

The regulations of airfares (fares) were relaxed,

More route designations could be added regardless of smaller demand,

Capacity share between states was eventually abolished, and

Air freedoms were increased

Table 1.5-3, overleaf, is a good indication of how a phased implementation of an air transportation

liberalisation agreement could be structured, thereby giving states, airports and airlines time to adjust

and improve aviation efficiencies.

Table 1.5-1, overleaf, shows the capacity and traffic growth for all of Europe, between the periods of

1990 – 2002. The results shown only take into account the change between the first and the last year in

the four year period. This removes some of the explainable short term fluctuations such as the 11

September 2001 attacks in the U.S. As can be seen, the growth in passengers carried by all European

airlines between 1998 - 2002 more than doubles that between 1990 - 1994.

P a g e | 21


Muller Associates

Table 1.5-1 Capacity and Traffic Growth for All Europe, 1990-2002

Increase in passengers carried

Market 1990-1994

1994-1998

1998-2002

Total Europe

20.40% 37.80% 40.90%

Source: InterVISTA-ga2, 2006

One of the significant findings of the liberalisation process in the E.U. has been the gain in market share

by low cost carriers. Before liberalisation low cost carriers were restricted to certain

Table 1.5-2 Summary of Intra-EU transport packages

Source: InterVISTA-ga2, 2006

P a g e | 22


Muller Associates

routes and booking slots. They also competed against subsidised national flag carriers. Table 1.5-3

below shows how the low cost carrier airlines have grown their market share in the aviation industry,

from 1996 to 2003. These low cost carriers have moved from a 1.4% market share to more than a fifth of

the share in the aviation market.

Table 1.5-3 : Capacity Shares of Low Cost Carriers

Year Low-Cost Operators’ Share of Capacity

1996 1.40%

1997 2.80%

1998 3.70%

1999 4.20%

2000 6.00%

2001 6.40%

2002 11.10%

2003 20.20% Source: InterVISTA-ga2, 2006

Liberalisation of the E.U. aviation market between 1988 and 1993 has led to an additional 44 million

passengers being carried annually, which equals a 33% increase in passenger seats. This traffic

expansion has encouraged development of both the tourism sector and other industries. Some 1.4

million full-time jobs resulted from the liberalisation, and European GDP grew by $US 85 billion.

1.5.3 India – United Kingdom

The aviation regulations between India and the United Kingdom (UK) were liberalised in late 2004 to mid

2005. The United Kingdom Civil Aviation Authority put together a case study of pre- and post- lair

transportation liberalisation agreements between India and the UK. The Civil Aviation Authority focuses

primarily on the effects that this agreement has had to date on aviation in the UK. They laid out the

report in four sections: impact on consumers; impact on the airlines; impact on the airports; and impact

on the wider economy.

1.5.3.1 Impact on consumers

Consumers were the biggest beneficiaries of the air transportation liberalisation agreement between

India and the UK, due to the increased number and choice of services, destinations and airlines

operating between these two countries. Between summer 2004 and summer 2006, the number of

direct flights between India and the UK rose from 34 to 112 per week. This can be seen in Figure 1.5-2

overleaf, which shows growth in U.K. – India direct services between 2000 and 2006.

P a g e | 23


Muller Associates

Figure 1.5-2 Growth in UK-India direct services 2000-2006

Source: United Kingdom Civil Aviation Authority, 2006

The majority of the new flights are operating between the main airports of India and the UK– London

Heathrow (an increase of 77 services per week), Delhi (an increase of 23 services per week) and Mumbai

(an increase of 38 services per week). However, new flight origins and destinations have been added in

both the UK and in India– Birmingham, Amritsar and Bangalore. This increase in services has been

provided by a combination of airlines which were already serving the market (British Airways, Virgin and

Air India) and new entrant airlines (JetAirways, bmi and Air Sahara.) Figure 1.5-3, overleaf, shows the

added airports and airlines serving the market.

Furthermore, the increase in capacity and more intense competition has resulted in a reduction in air

fares, from £882 to £736 for one-way fare paid by passengers travelling for business class and £251 to

£231 for one-way fare paid by passengers travelling economy class. Airlines have had to discount fares

to compete for customers.

P a g e | 24


Muller Associates

Figure 1.5-3 Breakdown of direct services to India in summer 2004 and 2006


1.5.3.2 Impact on Airlines

The impact of air transportation liberalisation agreements on airlines is both positive and negative. The

increased competition reduces profits, whilst the new commercial freedoms enabled previously

excluded carriers to enter the market, offering services for the first time. The frequency market shares

for the carriers before and after liberalisation can be seen in Table 1.5-4 below. This shows that the

liberalisation of the aviation market led to more competition and reduced the oligopolistic and

uncompetitive nature of this previously regulated market.

Civil Aviation Authorities modelling shows that while UK airlines benefited from an increase in revenue

of £30 million between 2004 and 2005, reductions in fares reduced profits by £46 million.

Table 1.5-4 Frequency market shares at the beginning of IATA Summer 2004 and 2006 seasons

Airline Summer

2004 Summer

2006

British Airways 56% 37% Virgin Atlantic 9% 12% bmi 0% 6% Air India 35% 22% Jet Airways 0% 20% Air Sahara 0% 3%

Total 100% 100% Source: United Kingdom Civil Aviation Authority, 2006

P a g e | 25


Muller Associates

1.5.3.3 Impact on Airports

The benefit to airports from air transportation liberalisation agreements is the added revenue brought

about by the increase in services from the added number of flights. Civil Aviation Authorities modelling

suggests a net benefit to UK airports of around £12 million of additional profits from increased revenues

of £65 million. The paper did not quantify the impact on Indian Airports. Airports such as Amritsar and

Bangalore, which were previously not served, now accommodate international flights to and from the

UK. Figure 1.5-4 below shows the growth of point-to-point markets from the UK to India. As can be

seen, the air transportation liberalisation agreement benefited the existing airports as well as new

airports accepting international flights.

Figure 1.5-4 Growth of direct point-to-point markets from the UK to India


1.5.3.4 Impact on the wider economy

The impact on the wider economy is mostly made up of circumstantial evidence in the report. Trade

levels between the UK and India increased by approximately 25% from 2005 to 2006. Foreign direct

investment by Indian companies into the UK grew by 110 % in the same period. While it is difficult to

demonstrate that the air transportation liberalisation agreement was responsible for this, the results

suggest that the agreement was certainly a contributor. The Civil Aviation Authority stated that “this

point is supported by survey data for the latest available years (2004 to 2005) which shows that direct

P a g e | 26


Muller Associates

business traffic has grown at a similar rate to leisure traffic in the year 2004 to 2005 (37 per cent

compared to 48 per cent), suggesting that aviation liberalisation is facilitating greater business activity

between the two countries.” Added to this circumstantial evidence is the fact that India’s strong

economic growth is being partly driven by a move into higher-value, more export-orientated sectors

such as IT and pharmaceuticals, which have a requirement for air transportation. The growth in the

frequency and capacity of direct UK-India flights is likely to have a further effect on the development of

these businesses. It is also important not to forget that there has been substantial growth in tourism

between these two countries.

1.5.4 Impact of an international air transportation liberalisation agreement

The InterVISTA-ga2 report attempts to measure the impact of a global liberalisation of aviation

agreements. The impacts were measured in

Passenger seats,

Air freight traffic,

Employment,

Gross domestic product,

Tourism and

Catalytic investment impacts

for any country-pair. Most of the base data used in the models came from various case studies that

analysed the various changes in the measurements when aviation regulations were liberalised. Time

series and cross sectional models were then used to assess the impact of air transportation

liberalisation.

The findings of the United Kingdom Civil Aviation Authority, 2006, report estimated that if 320 pair

country markets, currently not in an air transportation liberalisation mode, liberalise their air service

agreements air traffic would grow by 63%, significantly higher than recent world traffic growth of

around 6 - 8% per annum. This growth could potentially create 24.1 million full-time jobs and generate

an additional $490 billion in GDP, which is the equivalent of an economy the size of Brazil.

1.6 Forecasted effects of air transportation liberalisation agreements

The case study approach in Section 1.5 paints air transportation liberalisation agreements in a very

positive light and suggests that only benefits accrue to countries that open up their airspaces and

airports. However, air transportation liberalisation agreements do not always have the impact hoped by

countries entering negotiations, as shown in studies conducted by Micco and Serebrisky (2006) and

Swan (2008).

P a g e | 27


Muller Associates

There are two essential issues discussed by Micco, et al, (2006) and Swan (2008) that should be

considered before a country enters into an air transportation liberalisation agreement:

Firstly, does the country have adequate infrastructure, a regulatory body, available skills and sufficient market size?

And secondly, can a country afford to shift aviation activity away from a central hub airport as shown in Figure 1.3-1.

These two questions have particular relevance for Africa and more specifically for the Southern African

Development Community. In this section we will discuss and highlight the outcomes and

recommendations of Micco, et al, (2006) and Swan (2008).

1.6.1 Infrastructure, regulatory body, skills and market size limitations

The first study undertaken by Micco, et al, (2006), made use of regression analysis to estimate the effect

that air transportation liberalisation agreements had on transport costs. They primarily used data on air

transport costs from the US Imports of Merchandise Database. The data covered the period 1990 to

2003, where the US entered into a number of air transportation liberalisation agreements with various

countries. This period provides ample time to analyse these agreements and assess their effects in

totality.

Further data used in the regression included:

The distance between the freights origin and its destination in the US. This is an important consideration as distances between origins and destinations do not change when air transportation liberalisation agreements are concluded, and the price of jet fuel price is unaffected by these agreements.

GDP and GDP per capita in US dollars for both the origin of the freight and its destination in the US.

The percentage of the population which resides in urban areas, as it was assumed that the vast majority of air freight is generated from urban and peri-urban areas.

Certain data on airports and cities; these geographic coordinates, population of major urban cities, number of paved runways, as well as runway lengths and widths.

An infrastructure skills index.

The econometric model used in Micco, et al, (2006), is shown in equation (2) overleaf. The coefficients

are shown in Table 1.6-1 overleaf. The results display the cross sectional analysis of regression on

transport costs. It can be seen in Table 1.6-1 that the product unit value (which is the value per unit

weight of cargo at 4-digit SITC) and distance per port of entry (which is the distance between the origin

of the air freight and the destination in the US) have the highest positive coefficients, meaning that total

transport cost increases most significantly for each additional km travelled or value per unit weight of

freight transported. Improved foreign airport infrastructure reduces transport costs by the greatest

P a g e | 28


Muller Associates

amount, whilst the benefit of an air transportation liberalisation agreement has a much smaller impact

on transport costs than expected.

The figures in brackets in Table 1.6-1 show the standard error, and it can be seen that the standard error

for certain coefficients is so slight that we can assume these to be close to correct. However, the

standard error for Total Volume, Imbalance and Open Sky Agreement vary quite significantly. It is also

reported on Table 1.6-1 that Distance per port of entry, Product unit value, Foreign airport

infrastructure index and the implied effect infrastructure index are all significant at 1%, this tells us that

we are 99% confident that these variables have an effect on transportation costs. These results tell us

that the distance of an airport, the value of the product being shipped and the infrastructure of the

foreign airport have the largest significant effect on transportation costs.

Table 1.6-1 Section analysis of regression on transport costs

Distance per port of entry (ln) 0.244

S.E. (0.04) significant at 1%

Total volume (ln) 0.001

S.E. (0.02)

Product unit value (ln) 0.476


Imbalance -0.079

S.E. (0.072)

Air transportation liberalisation agreement -0.04

S.E. (0.046)

Foreign airport infrastructure index II (FAII1) -0.39


Regulatory quality -0.15

S.E. (0.04)

Implied effect infrastructure index -0.183 significant at 1%

Sample All countries

R-squared 0.335 Source: Micco, et al, (2006)

Equation (2): Transport cost origin-destination = dummy variable + distance origin-destination + total volume origin-destination + product unit value origin-destination + trade imbalance origin-destination + foreign airport infrastructure origin + regulatory quality origin + air transportation liberalisation agreements + error term

Further analysis was conducted on the air transportation liberalisation agreement coefficient in this

study but more noteworthy are the results shown in Figure 1.6-1 overleaf. As seen in Figure 1.6-1, the

coefficient on air transportation liberalisation agreements increases in size with each year, indicating

that air transportation liberalisation agreements have more of an impact on reducing transport costs the

longer the time period elapsed since implementation. This is to be expected as air markets need time to

adjust to the new regulations when significant changes take place. Micco, et al, (2006) primarily focused

P a g e | 29


Muller Associates

on air freight transport. They eventually estimated that over a period of five or more years, an air

transportation liberalisation agreement could potentially reduce air freight transport costs by roughly

9% and increase foreign trade by 12%.

P a g e | 30


Muller Associates

Figure 1.6-1 The effect of air transportation liberalisation agreements on air transport costs over time

Source: Micco, A. et al 2006

The most important finding in this paper is that air transportation liberalisation agreements do not have

the same effects in all countries. For instance air transportation liberalisation agreements in developed

and upper-middle- income developing countries reduce air transport costs, but for low-income

developing countries air transportation liberalisation agreements are not associated with a fall in freight

rates. This is understood as an indication that low-income developing countries cannot take full

advantage of air transportation liberalisation agreements because of other barriers to competition or

because of their limited market size. Micco, et al, (2006) also find that countries with better access to

airports, well trained airport staff, adequate airport infrastructure and better regulatory quality, have

lower air transport costs.

Therefore, if air transportation liberalisation agreements are to be maximised to their full potential

these issues need to be dealt with first:

Sufficient airport infrastructure needs to be in place .i.e. Appropriate runway lengths and widths, modern air traffic control systems etc.

Staff needs to be skilled in the various areas required to run an efficient air service.

Regulatory structures need to be in place to monitor the air market.

The market size of the country needs to be assessed and increased. Cargos and manufactured products (such as certain agricultural products, as well as electronic and highly technological goods) that are transported by air freight need to be assisted and initiated.

Other barriers to competition could range from political unrest and corruption to restrictive government policies. All of these need to be addressed in order for air transportation liberalisation to be successful in a country.

P a g e | 31


Muller Associates

1.6.2 Spread of development from hubs to outlying areas

The second study by Swan (2008) investigates how regulated markets have constrained travel within the

region. Swan (2008) lists techniques for forecasting air transportation levels in deregulated air markets,

highlighted in Section 1.5 above (the ‘Aviation forecasting models’). The paper moves on to review

forecasts by Boeing and Airbus for regional growth in air travel and air freight, by comparing these to

recent trends in growth and forecasts conducted by the author.

Table 1.6-2 below shows the forecasted growth in air travel between North-East Asia and North America

predicted by Airbus, Boeing and Swan. As can be seen these growth levels fluctuate between 5% - 6.5%

over 10 and 20 year periods.

Table 1.6-2 Forecasts in North-East Asian travel to North America

Swan 10yr

Boeing 20yr

Boeing Airbus 20yr

China 5.1% 6.4% 6.4%

Japan 5.3% 5.1% 5.0% 4.2%

Korea 5.9% 5.1% 5.6% 5.9% Source: adapted Swan, W. 2008

Figure 1.6-2 Actual air travel between North-East Asia and North America

Source: Swan, W. 2008

The report reveals how accurate these growth levels are by comparing them to the actual trends in air

travel growth to North America for the periods of 2007 and 2008. The actual air travel between these

two regions can be seen in Figure 1.6-2 above

P a g e | 32


Muller Associates

. Air travel between Japan and North America decreased during this period, while air travel grew at a

much higher rate than expected in China and Korea. Swan (2006) explains such differences between the

actual figures and the forecasts by stating: “the lesson here is that useful regional forecasts need to start

with good regional data, and they need to recognize changes in routes, fares, and political constraints

specific to the markets.”

The models used to forecast air travel growth are unable to account for changes in routes and route

development, and this tended to be the main reason the forecasts differed so much from the actual

data in air travel. Swan (2008) found that actual growth levels in air travel were similar to GDP growth

levels for each of the countries concerned.

One of Swan’s (2008) major findings in this report was that air services dramatically increased travel to

cities outside the existing list of major gateways, allowing them to participate to a much greater degree

in international trade. This is an important point for the Southern African Development Community to

take into account, as air travel and services may shift away from O.R. Tambo Airport in South Africa, to

outer lying airports in the region. Hence it is these smaller airports which may stand to benefit the most

from an air transportation liberalisation agreement and this may be at the expense of larger airports.

Over time an air transportation liberalisation agreement could help small regional and airports develop

by attracting more air traffic and economic activity into these regions, but at the same time O.R. Tambo

may lose air traffic and potential revenue.

1.7 Concluding Comments

From the literature reviewed we can conclude that air transportation liberalisation initiatives that have

been pursued are mostly successful in regions where implemented, provided that there is adequate

airport and tourism infrastructure. The literature would seem to suggest strongly that the deregulation

of the air space over Africa and the Southern African Development Community would bring about

significant changes to the structure and makeup of the current air market in Africa, and add value to the

economies of Africa. The level of change would depend on the how many freedoms of the air would be

permitted.

A number of African national flag carrier airlines would be the most vulnerable to these changes, as it

was reported in European region that low cost carrier airlines were the most likely to benefit from air

transportation liberalisation legislation. National flag carrier airlines would need to cut costs and move

towards efficient practices (similar to those of low cost carriers); they would also lose out on potential

revenue and market share as low cost airlines compete for passengers around Africa and the Southern

African Development Community. African tourism and business relationships would stand to gain the

most from an air transportation liberalisation agreement.

Crucial to the success of an air transport liberalisation agreement being implemented in the SADC region

and ultimately the African continent as a whole is the establishment of a competition authority. The

primary role of this authority would to discourage anti-competitive behaviour, allow easy access for new

P a g e | 33


Muller Associates

African airlines wishing to enter the market and ensure that no airline abuses a position of market

dominance. Furthermore this regulator could ensure that African governments remove aviation

regulations in the time frames agreed upon. It is therefore necessary that African member states to this

agreement give this body ultimate authority and the power to enforce the terms of the agreement

among reluctant states, airlines and airports.

The literature reviewed also shows that air freedoms 1 – 5, along with air freedom 8 encompasses the

standard package for an air transportation liberalisation agreement. Furthermore the literature

forecasts that if there were a global liberalisation of aviation markets, then air traffic would grow

significantly. This growth in air traffic would be create large amounts of additional full time employment,

as well as contributing hundreds of billions of additional dollars to global GDP (this extra GDP was

estimated to be equivalent to that of total Brazilian GDP.) The impact of air transport liberalisation

agreement being implemented in SADC is discussed and forecasted in the sections to follow.

An important consideration raised by the literature is that in order to take advantage of air

transportation liberalisation agreements, appropriate aviation infrastructure and skills are required,

namely– airport infrastructure, airline and airport efficiencies, regulatory controls, market size, the

population’s ease of access to airports and aviation markets, and political and business stability. Without

these conditions, countries will not be able to take advantage of these liberalised regulations.

Furthermore, the literature recognised that air transportation liberalisation would divert flights away

from hub airports, as passengers would demand more direct flights. It is necessary to assess whether

the current hub airports in SADC could sustain themselves in the future as further use is made of

alternative airports within the region.

Whilst the following sections will only estimate the impact of an air transportation liberalisation

agreement on the SADC region, it would be advisable for the Department of Transport to further

investigate the functions and make up of a regulatory body that would be necessary to assist in

implementing the air transportation liberalisation agreement for the entire region.

P a g e | 34


Muller Associates

2 Impact of air transport liberalisation agreement in Southern African

development Community

2.1 Introduction

This study sets out to determine the impact of implementing an air transport liberalisation agreement in

SADC. The following measures of liberalisation have been taken into account throughout the remained

of this section:

Only airlines operating in SADC should benefit from the implementation of air transport liberalisation agreement in SADC;

The granting of up to 5th air freedom rights plus cabotage, the 8th air freedom right;




The elimination of all protective policies in favour of national flag carriers;





After considering the above agenda and the general experience with air transportation liberalisation

initiatives elsewhere in the world, the research team determined that if an air transport liberalisation

agreement were to be implemented within the SADC region, two results can be expected:

a) That there will be impacts within the aviation market; and

b) There will be impacts felt within supporting industries to the aviation market. The impacts that

will be felt within the aviation market are termed as direct impacts and the impacts experienced

within the supporting industries are termed as indirect impacts.

An assessment of both the direct and indirect impacts will be used to determine the costs and benefits

of implementing the an air transport liberalisation agreement within the SADC region. This method is

known as cost-benefit analysis (CBA).

P a g e | 35


Muller Associates

The study identified the following direct and indirect impacts:

Direct impacts:

On Airlines

On Airports

Passengers

Freight

Customs

Indirect impacts:

On Tourism

On Airport services

Aircraft manufacturers

Environment

Intermodal services

Government

Based on available data, direct and indirect impacts are calculated and utilised in the cost benefit

analysis. Data used includes feedback from stakeholders via the questionnaire and other sources..

A diagram that illustrates the various components of the cost benefit analysis can be viewed in the

Appendix D.

It is observed that the quantifiable benefits of implementing an air transport liberalisation agreement in

SADC far outweighs the quantifiable costs of such an implementation over the 50 year period.



Muller Associates

2.2 Overview of the Current Status of the SADC Aviation Industry

SADC flight departure data indicates that certain airlines in SADC service mainly domestic routes and

service very few international routes, while other airlines are largely reliant on international business.

The following analysis focuses on the number of domestic and international departures for major

airlines in the SADC region. The general trend for most airlines indicates that there has been a gradual

increase in the total number of departures over the years; however a decrease in total departures is

noted during the 2007 to 2009 periods for smaller airlines, in all likelihood as a result of the downturn in

the global economy over this period. Although the September 11 attacks reduced worldwide air travel

significantly, most SADC airlines were unaffected. Other major scares such as the SARS virus and Swine

flu also had little impact on most SADC based airlines. SADC airlines more commonly encountered

periodic problems due to internal issues such as financial losses, inefficiency and safety of aircraft or due

to localised external problems such as political instability in countries where the airlines operate. It is

noted that national carriers generally split departures between international and domestic while low

cost carriers mainly undertake domestic flights.

A country by country analysis follows.

2.2.1 Angola

There are currently 9 airlines operating in Angola. Non-availability of data for these airlines prevents

analysis of the current and past trend in departures and passenger numbers. Fleet sizes for the airlines

were available and are illustrated in Figure 2.2-1 overleaf.

The largest fleet belongs to SonAir with 32 aircraft. SonAir is a privately owned airline that specialises in

transporting passengers to and from offshore and onshore oil industry facilities. The airline also

provides services to other businesses, single entities, charter services within Africa, and private and

government businesses. It operates from 7 regional airports within Angola and internationally to

Houston with the aid of World Airways. SonAir also provides helicopter services to businesses.

The national operator TAAG Angola Airlines has 12 aircraft and flies to Cameroon, Cape Verde, Central

African Republic, DRC, Congo, Mozambique, Namibia, Sao Tome and Principe, South Africa, Zambia,

Zimbabwe, Cuba, Brazil, China, United Arab Emirates and Portugal internationally. It operates from 16

airports within Angola. TAAG has code share agreements with Air France, Brussels Airlines, British

Airways and Lufthansa.

Diexim Expresso operates regional flights, VIP flights and charter flights between Angola and Namibia. It

operates from 5 destinations within Angola. Air 26 also provides domestic services within Angola and

operates from 7 airports within Angola. Alada provides passenger and cargo charter services throughout

Angola and to other parts of Africa. Air Gemini is a cargo airline mainly servicing the diamond mines and

undertaking humanitarian missions. Aeronautica provides charter freight and passenger services.



Muller Associates

Angola Air Charter is a charter airline specialising in charters within Africa and to Europe, particularly to

Belgium and the Netherlands. Transafrik is a cargo airline.

Figure 2.2-1 Fleet size – Airlines in Angola

2.2.2 Botswana

Air Botswana is the national airline of Botswana. The airline was faced with numerous financial

problems since 1988 as can be seen on Figure 2.2-2 overleaf. In 1994, the government had to write off

losses of over 50 million Pula as the airline was unable to cope with the financial demands being made

upon it. The airline began to pick up after the losses were written off and both domestic and

international departures began to increase. The airline recorded a net profit for the years 1998 and

1999, but expenses exceeded revenues in 2000 resulting in a drop in net profit for that year. The airline

was hard hit when a pilot on a suicide mission crashed into two other planes at the airport. The airline

had to lease an aircraft after the incident in order to resume operations.

2

75

31

8

32

12

8



Muller Associates

Figure 2.2-2 Air Botswana Financial data

Departures increased over the years as the government attempted to privatise the airline due to

recurring losses. Negotiations to privatise failed and the airline resumed operating at a loss. Although

the airline is faced with many challenges, international and domestic departures continued to increase

over the years indicating that there is demand for travel into and out of Botswana regardless of the

financial turmoil of the airline. Departures data can be seen on Figure 2.2-3 overleaf. Air Botswana has

a greater number of international departures than domestic departures; this would indicate that

Gabarone Airport is the primary destination for businessman and tourist entering Botswana. It must

also be considered that Botswana is considered one of the stronger economies of southern Africa with

lucrative diamond exports due to the presence of the world’s largest and richest diamond mine

attracting thereby attracting flights and passengers.

-15

-10

-5

0

5

10

15

20

25

30

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

US

$ (

Mill

ion

)

Operating Revenues Operating Expenses Net Profit



Muller Associates

Figure 2.2-3 Air Botswana Domestic and International departures

While the airline has struggled financially over the years, statistics show that passenger numbers have

not suffered. Air Botswana experienced an increase in both domestic and international passengers over

the years. Air Botswana flies to 4 airports within Botswana and internationally to South Africa and

Zimbabwe. Air Botswana has a greater number of international passengers than domestic passengers

indicating that travel within Botswana is not as popular as international travel. Both International and

domestic passenger volumes have been increasing over the years as can be seen on Figure 2.2-4 below.

Figure 2.2-4 Air Botswana Domestic and International passengers

Air Botswana has 6 aircraft in its fleet. The airline has three ATR 42-500s, two ATR 72-500s and one

Boeing 737-200 aircraft. The fleet size is illustrated in Figure 2.2-5 overleaf.

0

1000

2000

3000

4000

5000

6000

7000

8000

1992 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Domestic International

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

AirBotswana Domestic AirBotswana International



Muller Associates

Figure 2.2-5 Air Botswana Fleet

2.2.3 Democratic Republic of the Congo (DRC)

There are 7 airlines currently operating in the DRC. Hewa Bora Airways is the largest airline in DRC and

operates regional and domestic routes. It operates from 8 airports within DRC and also flies to the

Republic of the Congo and to South Africa. Filair operates within DRC and flies to 5 airports within the

DRC. Air Tropiques provides domestic, regional and charter flight services. Air Kasai operates charter

services within Africa. Business Aviation provides domestic and international air services. It flies within

the DRC and internationally to Brazzaville and Pointe-Noire. Comapgnie Africaine d’Aviation operates

domestic routes within the DRC to 8 airports. Wimbi Dira is a charter, passenger and cargo airline flying

to the main cities in the DRC. All the airlines based in the DRC are prohibited from entering European

airspace due to sub-standard safety management practices. Fleet sizes of the above airlines can be seen

on Figure 2.2-6 overleaf.

3

2

1

ATR 42-500 ATR 72-500 Boeing 737-200



Muller Associates

Figure 2.2-6 Fleet size – DRC Airlines

2.2.4 Lesotho

Air Lesotho was a government owned national airline and operated on both domestic and international

routes. The airline ceased international operations in 1996 due to the inability to satisfy the minimum

requirements specified by the Department of Civil Aviation. As can be seen on Figure 2.2-7 below,

domestic and international departures decreased drastically over the years until it stopped operations in

1996. At the end of 1996, the airline was financially insolvent and ceased to operate.

Figure 2.2-7 Air Lesotho Domestic and International Departures

5 5

2

3

6

9

2

Air Kasai Air Tropiques

Business Aviation

Compagnie Africaine D

Aviation

Filair Hewa Bora Airways

Wimbi Dira Airways

0

1000

2000

3000

4000

5000

1990 1991 1992 1995 1996




Muller Associates

2.2.5 Madagascar

In Madagascar an average of 15,000 departures were recorded between 1990 and 1998. Most of these

were domestic departures with a small portion of international departures. In the late 1990s the

country was recovering from years of political instability. In the 1998 elections, President Ratsiraka was

re-elected, restoring some confidence in the country. Both domestic and international departures

increased. Domestic departures rose from 14,472 to 19,771 in 1999 while international departures

increased from 1,885 to 2,260. The country enjoyed a few years of growth and stability but confidence

was quickly lost when the country held new elections in December 2001 which led to sporadic violence

due to ethnic clashes and the political crisis ensued until July 2002.

Departures recovered from the sharp drop in 2002 and returned to average departures by 2003.

Madagascar recorded its highest ever tourist numbers in 2007. This can be seen on Figure 2.2-8 below

where both domestic and international departures more than doubled from 2006. Domestic departures

increased by 145% from 11,115 to 27,238 departures, while international departures increased by 220%

from 3,168 to 10,168 departures in 2007.

In 2008, departures dropped drastically from the previous record high of 2007 due to the onset of a

global economic recession and renewed political instability in the country. The majority of tourists flying

to Madagascar are from France and, as a result, the global recession had a significant impact on tourism

to Madagascar. In 2009, a coup to overthrow the government led to political riots indicating that the

country was politically unstable. The swine flu pandemic further fuelled fears for international travellers

as many countries around the world proved vulnerable, mainly in South America and Africa, due to

perceived limited resources for curbing a potential epidemic.

Figure 2.2-8 Air Madagascar Domestic and International departures

0

5000

10000

15000

20000

25000

30000

35000

40000

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09




Muller Associates

Passenger numbers for Air Madagascar are reflected in the figure below. As is seen in the departures

Figure 2.2-8 on the previous page, Air Madagascar experienced a sharp decline in the number of

domestic and international passengers in 2002 and again in 2009 due to political instability and a global

recession visible on Figure 2.2-9 below. The national government owned airline is directly affected by

instability in the country. The political situation in Madagascar has damaged the economy.

Figure 2.2-9 Air Madagascar Domestic and International passenger numbers

Air Madagascar recorded the largest number of domestic and international passengers in 2001 and 2007

while the lowest number of passengers was experienced in 2002 and 2009.

Although Madagascar has been plagued with years of political unrest, the airline has managed to break

even over the years barely covering expenses with revenues as seen on Figure 2.2-10 overleaf. The

decline in the economy in 2001 and 2002 affected the airline’s revenues resulting in losses in the years

2001 and 2002. The airline recovered in 2003 and managed to record a profit. By 2008 the airline once

again recorded a loss as the country was once again impacted with fresh political turmoil.

0

100000

200000

300000

400000

500000

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

AirMadagascar Domestic AirMadagascar International



Muller Associates

Figure 2.2-10 Air Madagascar Financial Data

There are two Madagascar based airlines operating in Madagascar, Air Madagascar and Tiko Air. Tiko

Air provides charter services within Madagascar. Figure 2.2-11 below shows the fleet size of both

airlines.

Figure 2.2-11 Fleet size – Madagascar airlines

2.2.6 Malawi

Air Malawi is the national airline of Malawi. The airline mainly services domestic routes and has a few

flights on international routes. It operates from 2 airports in Malawi and flies to South Africa, Tanzania,

Zambia and Zimbabwe, internationally. Data is only available for the years 1990 to 1993 seen on Figure

2.2-12 overleaf. Domestic departures make up a larger portion of total departures while international

departures have remained constant at about 1,100 annually. The government has since attempted to

-40

-20

0

20

40

60

80

100

120

140

160

US

$ (

Mill

ion

)

Operating Revenue Operating Expenses Net Profit

11

1

Air Madagascar Tiko Air



Muller Associates

privatise the airline however all negotiations have been unsuccessful. The airline has generally operated

at a loss over the years; however, the airline posted a profit for the year 2007.

Figure 2.2-12 Air Malawi domestic and international departures

As can be seen on Figure 2.2-13 below, both domestic and international passengers patronising Air

Malawi remained fairly constant for the years 1990 and 1991 but an increase of 11% and 8% for

domestic and international passengers respectively was recorded in 1993.

Figure 2.2-13 Air Malawi Domestic and International Passengers

0

500

1000

1500

2000

2500

3000

3500

4000

4500

1990 1991 1992 1993

Air Malawi Domestic Air Malawi International

52000

54000

56000

58000

60000

62000

64000

66000

68000

70000

1990 1991 1992 1993




Muller Associates

Air Malawi has 4 aircraft in its fleet. The airline has 1 ATR 42-320 and 3 Boeing 737-200s illustrated in

Figure 2.2-14 below.

Figure 2.2-14 Air Malawi Fleet

2.2.7 Mauritius

Air Mauritius mainly services the international market as Mauritius is regarded as one of the world’s

best holiday destinations. Over the years, Mauritius has become very popular for its sandy beaches and

friendly hospitality as well as its 5 star resorts. Mauritius is also a very stable country, politically. It

boasts a rich cultural heritage, superior diving and fishing spots, great food and tropical weather

conditions. Departures to the only domestic destination, Rodrigues (Sir Gaetan Duval Airport) are very

few in number as can be seen in the figure overleaf.

Air Mauritius flies to over 30 destinations around the world. In Africa, Air Mauritius operates to South

Africa, Kenya, Madagascar and Reunion. Departures for Air Mauritius were highest in 2004 and 2005

but have since dropped to lower levels. A drop in departures in 2008 and 2009 in Figure 2.2-15 overleaf

can be attributed to the global recession as many foreign travellers opted not to travel. The country

depends heavily on tourism. A drop in departures is also attributed to a change and upgrade in the

airline’s fleet.

Air Mauritius reduced the operation of two older aircraft in 2007 while awaiting delivery of new aircraft

to permit an increase in operations to major destinations such as India, Malaysia, Singapore and Perth.

1

3

ATR 42-320 Boeing 737-200



Muller Associates

Figure 2.2-15 Air Mauritius Domestic and International departures

The main focus of the airline is its international clientele. Over the years the number of international

passengers has grown steadily reaching a peak in 2007. Although the global recession has resulted in a

decrease in international travel, the number of international passengers serviced in 2009 was still quite

high at over 100,000 as illustrated in Figure 2.2-16 below.

Figure 2.2-16 Air Mauritius Domestic and International passengers

Air Mauritius has 12 aircraft in its fleet. The fleet comprises of 2 Airbus A319-100s, 2 Airbus A330-200s, 6

Airbus A340-300 and 2 ATR 72-500s as seen in Figure 2.2-17 overleaf.

0

2000

4000

6000

8000

10000

12000

14000

16000

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

Air Mauritius Domestic Air Mauritius International

0

200000

400000

600000

800000

1000000

1200000

1400000

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

Air Mauritius Domestic Air Mauritius International



Muller Associates

Figure 2.2-17 Air Mauritius Fleet

2.2.8 Mozambique

Linhas Aereas de Moçambique (LAM) is the national airline of Mozambique. Between 1977 and 1992,

Mozambique suffered an intense civil war. President Chissano worked hard to reform the country and

the civil war ended in October 1992. Over 1.5 million Mozambicans fled the country to neighbouring

states but began to return by mid 1995. The country suffered severely and this is visible in Figure 2.2-18

overleaf where both international and domestic departures dropped significantly up to the 1992 to 1994

period.

By 1996, the country began to recover stability, leading to an improvement in the local economy.

Elections held in December 1999 were peaceful and thus had little impact on tourism. Both domestic

and international departures began to increase gradually over the years and have peaked for the

moment in 2009. Mozambique is popular for its beaches and diving resorts, attracting mostly tourists

from neighbouring states. The global recession in 2008 has therefore had little impact on departures as

tourists opt to choose destinations closer to their home countries to contain costs.

Since Mozambique’s main tourist market is within southern Africa, an increase in total departures

indicates that the Mozambique tourism industry has not been impacted as adversely as many

international holiday destinations.

2 2

6

2

Airbus A319-100 Airbus A330-200 Airbus A340-300 ATR 72-500



Muller Associates

Figure 2.2-18 LAM Domestic and International Departures

Figure 2.2-19 below shows that both domestic and international passengers on LAM have increased

over the years indicating that the country has recovered from its previously adverse political situation.

Domestic passengers are much higher as LAM flies to 10 domestic destinations within Mozambique

while international routes operated include Angola, Kenya, Portugal, South Africa and Tanzania.

Figure 2.2-19 LAM Domestic and International Passengers

LAM has 6 aircraft in its fleet as seen on Figure 2.2-20 overleaf. Its fleet consists of one Antonov An-26,

three Boeing 737-200s and two Embraer E-190 LR/ARs.

0

2000

4000

6000

8000

10000

12000

1990 1991 1992 1993 1994 1996 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

LAM Domestic LAM International

0

50000

100000

150000

200000

250000

300000

350000

400000

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

LAM Domestic LAM International



Muller Associates

Figure 2.2-20 LAM Fleet

2.2.9 Namibia

Air Namibia is the national airline of Namibia. In 1994, majority of Air Namibia’s operations were

domestic; however domestic departures have decreased over the years and had halved between 1994

and 2000. International departures have increased over the years to almost double the 1994 level in

2000. Departures figures for the years 1994, 1996 and 200 are illustrated in Figure 2.2-21 below. Air

Namibia has been upgrading aircraft over the years and has 2 Airbus A340-312s which has enabled the

airline to cut costs and increase efficiency. Air Namibia currently flies to Angola, Zimbabwe, Botswana,

South Africa and Germany on its international routes and operates from 7 airports within Namibia.

Figure 2.2-21 Air Namibia Domestic and International Departures

1

3

2

Antonov An-26 Boeing 737-200 Embraer E-190 LR/AR

0

2000

4000

6000

8000

1994 1996 2000

Air Namibia Domestic Air Namibia International



Muller Associates

Air Namibia has a relatively large number of international passengers compared to domestic passengers

as can be seen in Figure 2.2-22 below. Both international and domestic passenger numbers have

increased over the years 1994 to 2000. The airline suspended flights to Switzerland and UK in 2009 but

still flies to Germany in Europe.

Figure 2.2-22 Air Namibia Domestic and International Passengers

The Air Namibia fleet comprises of two Airbus A340-300s, one Boeing 737-200, two Boeing 737-500s,

one Boeing 737-800 and two Raytheon Aircraft Beechcraft 1900D Airliners seen in Figure 2.2-23 below.

Figure 2.2-23 Air Namibia Fleet

0

50000

100000

150000

200000

250000

1994 1995 1996 1997 1998 1999 2000


2

1

2

1

2

Airbus A340-300 Boeing 737-200 Boeing 737-500 Boeing 737-800 Raytheon Aircraft



Muller Associates

2.2.10 Seychelles

Air Seychelles is the national airline of Seychelles and is wholly owned by the Seychelles Government.

Seychelles is a popular holiday destination offering a spectacular beach holiday. The airline has been

operating successfully over the years with both domestic and international departures increasing over

the years as seen in Figure 2.2-24 below. The airline offers domestic flights as well as international

flights. It operates from 3 airports within the Seychelles and also flies to Mauritius, South Africa,

Singapore, France, Italy and the United Kingdom, internationally.

Figure 2.2-24 Air Seychelles Domestic and International Departures

Many passengers fly into the main airport in Mahe and take flights internally to the Praslin and Bird

Island airports. As can be seen on Figure 2.2-25 overleaf, domestic and international passengers have

been increasing over the years. International passengers decreased in 1998 and 1999 as many routes

previously serviced were discontinued. The airline stopped flying to Kenya, Israel, Spain and Manchester

in 1998 and discontinued operations to India, the Maldives, Thailand, United Arab Emirates, Frankfurt

and Munich in Germany, Russia and Switzerland between 2000 and 2010.

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

1990 1993 1996 1997 1998 1999




Muller Associates

Figure 2.2-25 Air Seychelles Domestic and International passengers

Air Seychelles has 9 aircraft in its fleet as seen in Figure 2.2-26 below. Its fleet comprises of 1 Boeing

767-200, 1 Boeing 767-200ER, 3 Boeing 767-300ERs, 3 DHC-6 Twin Otter Series 300s and 1 Shorts 360-

300.

Figure 2.2-26 Air Seychelles Fleet

2.2.11 South Africa

South Africa is served by 18 locally based airlines providing services to both the domestic and the

international markets. Some of the larger airlines are South African Airways (SAA), SA Airlink, Comair,

0

50000

100000

150000

200000

250000

300000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999

Air Seychelles Domestic Air Seychelles International

1 1

3 3

1

Boeing 767-200 Boeing 767-200ER

Boeing 767-300ER

DHC-6 Twin Otter Series 300

Shorts 360-300



Muller Associates

Mango Airlines and 1time Airlines. Smaller airlines provide charter and air cargo services and specialise

in providing services to private businesses and VIP customers.

South African Airways (SAA) is the national carrier for South Africa. It has been operating for more than

seventy years and is a member of the Star Alliance global network. It has code share agreements with

United Airlines, Air New Zealand, Lufthansa and other Star Alliance partners. SAA flies to 5 domestic

destinations and 32 international destinations worldwide.

SAA recorded very low international and domestic departures in 1990 and 1991 as the country was

emerging from apartheid rule and the country faced international sanctions that prohibited travel into

and out of South Africa. By 1993, the government began to prepare for democratic elections and

sanctions against South Africa were dropped allowing for freer travel to and from South Africa. A surge

in domestic and international departures followed in 1993 and 1994 as confidence in South Africa was

slowly restored as seen in Figure 2.2-27 below. Lack of data between 1995 and 2001 does not allow for

analysis of air travel into and out of South Africa, however from 2002 to 2009, there has been a

consistent increase in international departures while SAA domestic departures have decreased over

these years due to the introduction of many low cost airlines into South Africa. SAA began to lose its

majority share in the domestic market as more airlines began offering seats on competing routes at

lower prices. The global recession appears to have had a very small impact, resulting in a small decrease

in total departures in 2009.

Figure 2.2-27 South African Airways Domestic and International departures

Passengers travelling on both domestic and international routes on SAA have consistently increased

over the past 7 years as illustrated on Figure 2.2-28 overleaf. Domestic passengers have shown a slight

decline since 2007 because many passengers opted to travel on other airlines within South Africa due to

affordability and flexibility.

0

10000

20000

30000

40000

50000

60000

70000

80000

1990 1991 1993 1994 2002 2003 2004 2005 2006 2007 2008 2009




Muller Associates

Figure 2.2-28 South African Airways Domestic and International passengers

SA Airlink has been an alliance partner with South African Airways and South African Express since 1997.

SA Airlink operates on domestic routes within South Africa and flies to Bulawayo, Harare, Tete, Beira,

Antananarivo, Pemba, Livingstone, Lusaka, Maseru, Manzini and Ndola. Domestic departures for SA

Airlink varied between 20,000 and 30,000 over the 6 year period as seen in Figure 2.2-29 below.

International departures have increased in 2007 and 2008 as SA Airlink changed its name and corporate

identity and began to offer flights to smaller and regional centres throughout Southern Africa.

Figure 2.2-29 SA Airlink Domestic and International departures

A change in brand image led to an increase in both domestic and international passengers on SA Airlink

in 2007. International passengers remained constant from 2002 to 2006 but an increase in the number

of routes offered within southern Africa increased the number of international passengers departing on

SA Airlink. Domestic routes are very popular and about 65,000 passengers fly on SA Airlink monthly. A

0

1000000

2000000

3000000

4000000

5000000

2002 2003 2004 2005 2006 2007 2008 2009

SAA Domestic SAA International

0

5000

10000

15000

20000

25000

30000

35000

40000

2002 2003 2004 2005 2006 2007 2008




Muller Associates

decrease in 2005 in domestic passengers due to increased competition within the South African

domestic airline industry caused SA Airlink to modify its strategy which was implemented in early 2006.

The airline has since, once again, achieved an increase in both domestic and international passengers as

demonstrated in Figure 2.2-30 below.

Figure 2.2-30 SA Airlink Domestic and International passengers

Comair Ltd started operating its low cost airline Kulula.com in 2002. Since then, South Africa has seen

the growth of low cost airlines with the introduction of Mango, 1Time and Nationwide Airlines. Comair

successfully launched its low cost airline in 2002 allowing many travellers the option to fly economically.

Comair also operates British Airways domestic flights within South Africa and regionally within SADC.

The airline market in South Africa was previously dominated by South African Airways which was costly,

thus deterring many travellers from flying and causing potential customers to seek alternative cheaper

options for travel. Comair introduced its low cost airline with flexibility and cheaper prices and became

instantly popular.

Departures have constantly increased over the 7 years Kulula.com has been in operation. Comair mainly

services the domestic market but offers flights to the African cities of Windhoek, Harare, Lusaka, Ndola

and Mauritius. Domestic departures have almost doubled since Comair started operation in 2002 and

serviced about 31,000 domestic and 3,100 international departures in 2009 as seen in Figure 2.2-31

overleaf. The global recession hit South Africa in early 2009; however it did not affect low cost airlines

as adversely because, in unfavourable economic times, more customers choose to travel on low cost

airlines.

0

100000

200000

300000

400000

500000

600000

2002 2003 2004 2005 2006 2007 2008

SA Airlink Domestic SA Airlink International



Muller Associates

Figure 2.2-31 Comair Domestic and International departures

Passenger numbers for Comair have increased consistently over the 7 years from 100,000 passengers to

330,000 passengers as seen in Figure 2.2-31 below. International passenger numbers have remained

constant over the same period of time. Comair currently flies to Harare, Windhoek, Lusaka daily, flies to

Ndola five times a week and once a week to Mauritius. As the international flights are not as frequent

as domestic flights, the number of passengers carried on international flights is much lower.

Figure 2.2-32 Comair Domestic and International passenger numbers

The fleet size of the various airlines within South Africa is illustrated in Figure 2.2-33 overleaf. SAA has

the largest fleet in South Africa with 50 aircraft. SA Airlink and SA express both have over 20 aircraft

0

5000

10000

15000

20000

25000

30000

35000

40000

2002 2003 2004 2005 2006 2007 2008 2009


0

500000

1000000

1500000

2000000

2500000

3000000

3500000

2002 2003 2004 2005 2006 2007 2008 2009

Comair Domestic Comair International



Muller Associates

while low cost carriers Comair, Kulula.com and 1time Airlines have more than 10 aircraft each. National

Airways Corporation (NAC) is a private charter company with a large fleet of 18 aircraft. While Mango

Airlines is a large player in the low cost airline market, it only has 4 aircraft. Other South African airline

companies have less than 10 aircraft each and mainly service domestic charter and cargo markets.

Figure 2.2-33 Fleet size – South African Airlines

2.2.12 Tanzania

Air Tanzania temporarily suspended operations in December 2008 and has not resumed operations as

yet. Air Tanzania was government owned until 2002 when it sold 49% stake to South African Airways.

This partnership lasted till September 2006 when the government of Tanzania bought back SAA’s stake

in the business. The partnership between SAA and Air Tanzania was regarded as unsuccessful and the

government stated that the airline was more successful before undertaking the abortive partnership.

Air Tanzania was revamped in 2007 and began using electronic ticketing, a new trademark and cleared

outstanding debt in order to start afresh. As can be seen on Figure 2.2-34 overleaf, international and

domestic departures were high in 1991 but began to fall in 1993. The airline maintained a fairly constant

level of departures until 1998 but the airline began to experience a decline in business by 1999 and the

number of departures fell. During the privatisation process, the airline experienced poor trading

conditions with the lowest level of departures noted in 2001 and 2002. The airline failed to operate

successfully after the revamp and suspended operations in 2008.

13

26

3

1512

2 3

10

4

18

6 4

22

4

11

50

41



Muller Associates

Figure 2.2-34 Air Tanzania Domestic and International departures

While domestic passengers on Air Tanzania have been falling since 1990, international passengers have

remained constant over the years. The lowest number of passengers was recorded in 2002 and this can

be attributed to change in ownership and privatization. After SAA took over operations, domestic

passengers increased between 2002 and 2005 as more flights were introduced. However, by 2006, the

airline was struggling again and both domestic and international passengers numbers began to decrease

as can be seen on Figure 2.2-35 below.

Figure 2.2-35 Air Tanzania Domestic and International Passengers

Air Tanzania has not operated successfully over the years and maintained a net loss for the 3 years to

1993. The airline managed to operate profitably between 1993 and 1996; however by 1998 the airline

was again suffering financially and began to make losses as seen on Figure 2.2-36 overleaf. Expenses

exceeded revenues and the airline struggled to break even. Due to its unfavourable financial position,

the government decided to privatise the airline so as to cut its losses however this was also

unsuccessful, finally leading to liquidation.

0

2000

4000

6000

8000

10000


0

50000

100000

150000

200000

250000

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

Air Tanzania Domestic Air Tanzania International



Muller Associates

Figure 2.2-36 Air Tanzania Financial data

Besides Air Tanzania, there are 3 other airlines operating in Tanzania. Eagle Air and Regional Air Services

are domestic airlines operating flights within Tanzania and charter flights in eastern and southern Africa.

Regional Air Services is a subsidiary of Air Kenya. Precision Air is a low cost airline operating from 10

airports within Tanzania and also operated flights to Kenya and Uganda.

The fleet size of the above airlines is illustrated in Figure 2.2-37 overleaf. Precision Air has the largest

fleet and is currently the largest airline in Tanzania since Air Tanzania ceased operations. Regional Air

Services has 5 aircraft while Eagle Air only has 2 aircraft.

-30

-20

-10

0

10

20

30

40

50

60

70

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

US

$ (

Mill

ion

)




Muller Associates

Figure 2.2-37 Fleet size – Tanzania airlines

2.2.13 Zambia

Zambia Airways was the national airline of Zambia. The airline was liquidated in 1995 as it was unable to

cope with operations domestically and internationally. The government of Zambia could not assist the

airline and indicated that it had to cover its own debts and expenses from revenues. The airline was not

able to cover costs in a worsening economic climate and shut down operations in early 1995. Departures

data for Zambia Airways’ last few years in operation are illustrated in Figure 2.2-38 below.

Figure 2.2-38 Zambia Airways Domestic and International departures

2

8

5

Eagle Air Precisionair Regional Air Services

0

500

1000

1500

2000

2500

3000

3500

4000

1990 1991 1992 1993 1994




Muller Associates

Zambezi Airlines is a privately owned airline operating in Zambia. It operates at 2 airports within Zambia

and flies to South Africa and Tanzania internationally. It has 3 aircraft in its fleet, 2 Boeing 737-500s

which were acquired in mid 2009 seen in Figure 2.2-39 below. The airline is currently banned from

entering European Airspace due to substandard safety standards.

Figure 2.2-39 Zambezi Airlines Fleet

2.2.13.1 Zimbabwe

Air Zimbabwe is the national airline of Zimbabwe. Negative publicity, politics and the economic

situation in Zimbabwe has had an adverse effect on the national airline. The volatile political situation in

Zimbabwe has led to the general decline of the tourism industry as well as an economic crisis. As seen

in Figure 2.2-40 overleaf, the highest number of departures was recorded in 1992 but the airline

experienced a large decrease in both domestic and international departures in 1993 and 1994 attributed

to clashes between the government and trade unions, resulting in general unrest in the country. The

airline recovered in 1995 but land redistribution and the eviction of white farmers in 1999 led to a

general decline of economic conditions in the country. Zimbabwe began to attract negative publicity

and widespread international condemnation of the situation in the country followed. Departures began

to fall in 1999 and the airline began to suffer financially due to the economic and political situation. In

2003 the airline announced that it was struggling financially and ceased operations temporarily and

departures fell to less than 1,000 that year. Operations have since resumed.

2

1

Boeing 737-500 Embraer EMB-120 Brasilia



Muller Associates

Figure 2.2-40 Air Zimbabwe Domestic and International Departures

Air Zimbabwe has had a somewhat tumultuous history as the number of domestic passengers began to

drop between the years 1996 and 2003. International passengers also decreased over the same period.

The drop in domestic passenger numbers was, however, far greater than that of international passenger

numbers as seen in Figure 2.2-41 below.

Figure 2.2-41 Air Zimbabwe Domestic and International passengers

Air Zimbabwe has been operating at a loss for most of the past two decades. In 1992, the airline was

able to realise a profit however, by 1993 the airline was once again making losses. The decline in the

political situation and the economy of Zimbabwe has had an adverse impact on the viability of the

airline. The airline was losing customers and was unable to cover its operating costs with the revenue

0

50000

100000

150000

200000

250000

300000

350000

400000

450000

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Air Zimbabwe Domestic Air Zimbabwe International

0

2000

4000

6000

8000

10000

12000

14000

1990 1992 1993 1994 1995 1996 1997 1998 1999 2000 2002 2003




Muller Associates

received from sales, excess baggage and freight. The financial situation of Air Zimbabwe is illustrated in

Figure 2.2-42 below.

Figure 2.2-42 Air Zimbabwe Financial Data

2.2.14 Airports in SADC

The table overleaf reflects the total number of passengers recorded arriving or departing at airports in

the SADC region. Airports that served more than 1,000,000 passengers in 2009 are defined as airports

with high frequency, airports with mid to high frequency serve between 200,000 to 1,000,000

passengers and airports with low frequency serve less than 200,000 passengers in 2009.

-40

-20

0

20

40

60

80

100

120

140

1990 1991 1992 1993 1994 1995 1996 1997 1998

US

$ (

Mill

ion

)



Socio-Economic Impact of the Air transportation liberalisation Yamoussoukro Decision: 6th April 2010 - report prepared by Graham Muller Associates

Table 2.2-1 Airports in SADC – Total Passengers

Airport Country 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Gaborone - Sir Seretse Khama

InternationalBotswana 188,925 224,488 240,526 225,392 473,794 285,708 355,727 518,284 346,411 386,313

Maun Botswana 137,056 139,571 163,307 142,737 154,092 193,067 205,078 239,368 272,010

Kinshasa N'Djili DRC 267,175 273,563 298,019 358,833 437,882 516,345 599,845 586,870 677,865 663,354

Antananarivo - Ivato International Madagascar 581,965 611,423 678,366 707,304 713,566 336,711 552,138 611,973 709,034 714,488 812,151 828,162 611,175

Majunga Madagascar 89,054 87,897 82,437 84,244 77,505 28,206 43,820 59,849 57,037 52,405 58,443 62,400 46,746

Lilongwe Malawi 208,356 207,157 198,924 202,618 193,446 173,521 176,703 196,140 186,363 173,829 282,529 303,210 296,190

Mauritius - Sir Seewoosagur

Ramgoolam InternationalMauritius 1,484,263 1,524,738 1,600,155 1,763,143 1,819,136 1,896,307 1,982,855 2,058,944 2,167,468 2,217,167 2,562,830 2,606,813 2,381,810

Maputo International Mozambique 308,500 330,969 390,882 436,849 419,327 437,832 445,383 478,115 558,979 624,540 693,618 669,372 668,706

Windhoek International Namibia 429,811 470,534 490,325 481,419 379,327 404,759 506,077 527,085 530,675 637,247 693,671 712,242 681,324

Bloemfontein South Africa 233,121 221,205 219,607 211,490 210,359 215,643 225,636 242,315 305,578 424,223 411,726 399,826

Cape Town International South Africa 3,998,316 4,306,716 4,614,931 4,654,107 4,210,792 5,019,283 5,329,534 6,018,044 6,738,020 7,224,587 8,400,569 8,150,611 7,725,223

Durban Louis Botha International South Africa 2,386,247 2,488,370 2,523,899 2,501,999 2,405,726 2,580,323 2,773,133 3,105,269 3,592,501 4,029,074 4,799,702 4,458,223 4,310,095

East London South Africa 369,445 363,262 352,012 318,793 365,069 380,771 422,672 560,419 664,292 744,455 714,427 674,680

George South Africa 111,892 132,401 227,591 245,052 285,464 335,813 438,747 579,017 589,854 651,563 630,385 527,026

Johannesburg O.R. Tambo

InternationalSouth Africa 9,722,758 10,870,104 11,339,920 11,680,598 11,789,814 12,743,545 13,506,495 15,340,670 15,769,094 17,344,669 19,439,083 18,636,251 17,607,255

Kimberley South Africa 84,444 83,903 82,703 91,100 93,193 89,676 97,442 102,841 129,136 147,277 155,507 130,644

Port Elizabeth South Africa 812,601 822,343 869,523 860,691 836,324 866,955 950,622 1,050,552 1,163,218 1,409,609 1,491,800 1,468,176 1,357,696

Upington South Africa 28,225 29,242 25,730 29,553 32,842 33,681 30,546 32,856 37,009 47,666 50,378 42,519

Kruger Mpumalanga 177,498 215,353 241,533 247,573 208,751

Dar-es-Salaam Tanzania 572,447 582,166 621,513 652,008 703,483 816,263 1,011,392 1,124,235 1,249,419 1,450,138 1,542,778 1,422,846

Kilimanjaro International Tanzania 310,469 134,407 207,256 221,108 192,204 184,652 294,750 363,512 480,053 566,579 521,915 426,600

Mwanza Tanzania 93,311 204,915 111,282 137,767 161,213 186,590 203,087 234,301 229,496 224,207

Zanzibar Tanzania 196,816 236,148 248,554 203,586 307,765 317,308 418,980 549,408 534,466 593,482 571,416 575,504

Lusaka International Zambia 328,132 339,944 341,361 466,533 433,521 392,285 390,505 432,712 447,141 603,107 734,442 837,901 663,223

Victoria Falls Zambia 178,376 168,849 194,938 181,167 210,464 185,859 137,552

Harare International Zimbabwe 629,549 554,370 592,437 629,979 610,221 731,340 674,281 612,208



Muller Associates

Airports in SADC – Total Passengers

Figure 2.2-43 Airports with highest frequency:

Airports with highest frequency are O R Tambo Airport Johannesburg, Cape Town International, Durban

International, Dar-es-Salaam Airport, Harare Airport and Sir Seewoosagur Ramgoolam International in

Mauritius. O.R Tambo Airport in South Africa has had a total of over 10 million passengers a year. Total

passengers at these airports have been increasing over the years and peaked in 2007 after which

passenger numbers began to decline. The global recession has had some effect on air travel and total

passengers declined in 2008 and 2009. All the above airports are international airports and serve both

domestic and international flights and passengers. Dar es Salaam, Harare and Mauritius airports have

recorded over 1.5 million passengers annually. These 6 airports illustrated in Figure 2.2-43 above are

the most frequented airports in the SADC region.

2.2.14.1 Airports with mid- to high frequency:

Airports with mid- to high frequency include airports in Madagascar, the DRC, Mozambique, Zanzibar,

Zambia and Namibia illustrated in Figure 2.2-44 overleaf. These airports recorded between 200,000 and

900,000 passengers annually. Most of the airports noted show an upward trend in the total number of

passengers embarking over the years. A dip in total passengers in 2002 and 2009 for Madagascar

occurred due to the political unrest experienced in the country during those years. All the airports that

recorded mid to high number of passengers are international airports except for East London airport

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Johannesburg O.R. Tambo International Cape Town International

Durban International Mauritius - Sir Seewoosagur Ramgoolam International

Dar-es-Salaam Harare International



Muller Associates

which only serves domestic flights. Air travel numbers were generally low in 2002 due to the aftermath

of the September 11 attacks, fuelling fears of terrorist attacks amongst passengers and deterring air

travel. The attacks did not have a large impact on African destinations; however there was global decline

in air travel during the period following the attacks in the US.

Figure 2.2-44 Airports with mid to high frequency:

2.2.14.2 Airports with low frequency:

Airports with low frequency are the airports serving the lowest number of total passengers annually –

defined as airports with fewer than 700,000 passengers annually. In general, passenger numbers at low

frequency airports gradually increase and peak in 2007. A decline is experienced in 2002 due to the

September 11 attacks and again in 2008 and 2009, which can be attributed to the global downturn in

the economy. International airports illustrated in Figure 2.2-45 overleaf that recorded low numbers of

passengers include Gaborone airport, Maun, Majunga, Lilongwe, Kilimanjaro International, Mwanza and

Victoria Falls. Kilimanjaro International and Gaborone recorded the largest increase in total passengers,

while Majunga, Lilongwe, Victoria Falls, Mwanza and Maun had constant number of passengers over the

years. Kilimanjaro international recorded the largest increase in total passengers over the years.

0

100000

200000

300000

400000

500000

600000

700000

800000

900000

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Kinshasa N'Djili Antananarivo - Ivato International

Maputo International Windhoek International

Zanzibar Lusaka International



Muller Associates

Figure 2.2-45 International Airports with low frequency:

Domestic airports illustrated in Figure 2.2-46 below with low numbers of passengers include Port

Elizabeth, East London, Bloemfontein, George, Kimberley, Upington and Kruger Mpumalanga. Upington

and Kimberley airports reflect a fairly constant level of total passengers over the years, while the rest of

the domestic airports demonstrated an increase in total passengers.

Figure 2.2-46 Domestic Airports with low frequency:

0

100,000

200,000

300,000

400,000

500,000

600,000

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Gaborone - Sir Seretse Khama International Maun

Majunga Lilongwe

Kilimanjaro International Mwanza

Victoria Falls

0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Bloemfontein East London George Kimberley

Port Elizabeth Upington Kruger Mpumalanga



Muller Associates

2.2.15 Fleet size of all SADC airlines

An overview of the fleet size of all airlines within SADC in 2007 is provided in Figure 2.2-47 overleaf.

Fleet size between airlines fluctuates enormously. The fleet size between airlines operating

internationally and domestically varies greatly compared to low cost airlines that only operate to

domestic destinations. National carrier South African Airways has the largest fleet within SADC, while

other national airlines such as TAAG Angla, Hewa Bora Airways, Air Madagascar, Air Mauritius, Air

Seychelles, Air Botswana, LAM, Air Malawi and Air Namibia have smaller fleet varying between 4 and 12

aircraft each..

Privately owned airlines in Angola, DRC, South Africa, Tanzania and Zambia own smaller fleets mainly

serving the domestic market. SonAir has the largest fleet of 32 aircraft while popular operators such as

Diexim Expresso, Transafrik, 1time, Mango, Comair and Precision Air have less than 10 aircraft each.

Specialized charter companies in South Africa, Angola and DRC have a variety of small aircraft. National

Airways Corporation of South Africa has a large fleet of 18 small aircraft.

The figure overleaf shows the fleet size of the larger SADC based airlines. Each country has been

differentiated by means of a colour coded system and the key appears below the figure.



Figure 2.2-47 Fleet Size (2007)

Angola Malawi South Africa

Botswana Mauritius Tanzania DRC Mozambique Zambia

Madagascar Namibia Zimbabwe

Seychelles

27 5 3 1

8

32

128 6 5 5

2 36

9

2

11

14

12

6 8 913

26

3

1512

2 3

10

4

18

6 4

22

4

11

50

41 2

85 3 5

Aer

on

auti

ca

Air

26

Air

Gem

ini

Ala

da

An

gola

Air

Ch

arte

r

Die

xim

Exp

ress

o

Son

Air

TAA

G A

ngo

la A

irlin

es

Tran

safr

ik

Air

Bo

tsw

ana

Air

Kas

ai

Air

Tro

piq

ues

Bu

sin

ess

Avi

atio

n

Co

mp

agn

ie A

fric

ain

e D

Avi

atio

n

Fila

ir

Hew

a B

ora

Air

way

s

Wim

bi D

ira

Air

way

s

Air

Mad

agas

car

Tiko

Air

Air

Mal

awi

Air

Mau

riti

us

Lin

has

Aer

eas

de

Mo

çam

biq

ue

LAM

Air

Nam

ibia

Air

Sey

chel

les

1Ti

me

Air

lines

Air

link

Air

Qu

ariu

s A

viat

ion

Co

mai

r

Fed

eral

Air

Imp

eria

l Air

Car

go

Inte

rair

kulu

la.c

om

Man

go

Nat

ion

al A

irw

ays

Co

rpo

rati

on

(N

AC

)

Nat

ure

link

Ch

arte

rs

No

rse

Air

SA E

xpre

ss

SAA

Car

go

Safa

ir

Sou

th A

fric

an A

irw

ays

Star

Air

Car

go

Tram

on

Air

Eagl

e A

ir

Pre

cisi

on

air

Reg

ion

al A

ir S

ervi

ces

Zam

bez

i Air

lines

Air

Zim

bab

we



Muller Associates

2.3 Analysis of Questionnaire Results

Between August 2009 and January 2010, 106 airlines, 3 airport authorities and 14 SADC transport

ministries were contacted and sent questionnaires regarding progress with the implementation of an air

transport liberalisation agreement in SADC related to the adoption of air transportation liberalisation

policies in Africa (the questionnaires can be found in Appendix E.) Of the 68 questionnaires sent out,

only 16 were returned completed. Analysis of the answers to the returned and completed

questionnaires follows.

2.3.1 Airlines

Feedback was received from five airlines within the SADC namely Federal Airlines, Owenair Pty Ltd,

South African Airways and Comair Limited of South Africa and Air Malawi of Malawi. Each airline is

unique servicing a different market or market segment. However the five airlines share similar views on

the impact of implementing an air transportation liberalisation agreement in the SADC region. The

profiles of the responding airlines are summarised in Table 2.3-1 below:

Table 2.3-1 Airlines Data Company / Organisation

Country of Operation

Type of Airline Annual Turnover

Ownership Owners

Federal Airlines South Africa High end domestic and international

Did not disclose

Private company

100% domestic private ownership

Air Malawi Malawi National flag carrier Did not disclose

Government owned

100% domestic government ownership

Comair limited South Africa Domestic low cost carrier, high end domestic and international, charter carrier, British Airways franchise, code sharing and alliance

R 3 billion Privately owned company

88% domestic private ownership,

12% foreign private ownership

Owenair (Pty) Ltd

South Africa Chartered carrier R 6 million Private company


South African Airways

South Africa National flag carrier Did not disclose

Government owned


The responding airlines stated in general, that the air transportation liberalisation aviation agreement

reached between African states, namely the Yamoussoukro Decision (YD,) was a poor and a weak

agreement as there has been no evidence of any multilateral implementation. This is due to lack of

arbitration procedures being agreed to progress deadlocked negotiations and lack of regulation by

means of competition laws. A phased in approach whereby each airline could have been engaged with

individually taking into account the differing passenger route densities on the routes that each airline

operates was recommended. There was no deadline set and the agreement was reached without prior

consultation with airlines. African states have not implemented YD due to lack of political commitment,

anti-transformation, resistance from weak state owned airlines, based on fear of the consequences of

more open commercial competition, lack of infrastructure development, limited fleet size in less



Muller Associates

developed countries and lack of consensus on a clear way forward. YD does not consider the strengths

and weaknesses of countries airlines, nor of the state of airport and aviation infrastructure in the various

regions of the African continent. The likely impact of implementing such an agreement on specific

countries has also not been determined.

Airlines cited the following as reasons why full implementation of the YD has been hindered:

Lack of individual government commitment to YD;

Lack of SADC member commitment to YD;

National flag carriers disapproval of YD due to perceived threats to existing privileged positions of aviation industry dominance;

Lack of effective competition law in individual countries and regionally;

Corruption;

Poor or non-existent legislation;

Political instability in certain African countries;

Poor / substandard airport infrastructure in many countries;

Airport security concerns;

Risks regarding the handling of higher flight frequencies at some airports; and

Resistance from stakeholders trying to protect monopoly or privileged positions of market dominance.

Airlines recommend that in order to successfully implement YD, governments will be required to play an

active role in ensuring that airlines are informed about intended progress (to a declared timetable)

towards implementation of YD in Africa. Bottlenecks need to be addressed; national airlines need to be

supplied with avionics so as to compete effectively; regulations need to be standardised and amended

to cover aspects such as competition law and arbitration procedures to speedily resolve disputes; and

stakeholders should be afforded the opportunity to buy into the implementation plan and be party to

discussions and planning of implementation. Lastly, African governments should focus on African

carriers which must be developed to compete globally rather than focusing on non-African airlines.

The airlines have differing views on the likely impact on countries that would implement YD. While some

airlines are sceptical and feel that most African airlines will not survive, others feel that a number of

small airlines will be sacrificed initially but the long term overall consequences will be positive.

Implementation will see an increase in tourism and business travel leading to increased traffic on dense

and lucrative routes resulting in lower fares, more competition and therefore more participants in the

airline industry. Airlines will benefit from offering reliable and efficient services at pricing levels that will

stimulate demand and therefore profitability - which will have widespread benefits for SADC economies.

Many national flag carriers and smaller, less efficient airlines will be unable to compete if they are not

recapitalised with competitive equipment and many may not survive.



Muller Associates

Impact of the YD on airlines will result in the following changes in the current status quo:

Frequency of flights – increase

Capacity (number of seats on offer) – may increase or remain static

Pricing – decrease due to increased competition

Volume of freight business – increase

Number of competitors on each route – increase on higher traffic routes but will decrease on more marginal routes

Market share of airline on each route – will reduce but as part of a rapidly growing industry

With the implementation of YD, airlines will be able to fly to destinations previously inaccessible. Airlines

will tend to increase the frequency of flights on the more lucrative routes so as to reap maximum

benefits. Depending on the demand for seats of the more popular routes, airlines will have to either

reduce flights on less popular routes and divert flights to the more popular routes or increase their fleet

to accommodate the demand. This will result in either an increase in overall capacity if more aircraft are

introduced or the overall capacity will remain static with airlines diverting aircraft to more popular

routes.

An increase in competition in the form of an increase in number of flights on routes within the SADC will

lead to a decrease in the average price of air tickets as airlines compete to maximise their market share.

This decrease in price will likely benefit passengers directly and may boost the number of passengers

travelling within the region, thereby greatly extending access by the general public to air travel. Not only

will this boost tourism and business travel around SADC and Africa, but will also benefit airlines, airports,

hotels, car hire companies, restaurants and other direct and indirect stakeholders in the aviation

industry. Similarly, freight business will be stimulated through cheaper tariffs leading to an increase in

the volumes of freight being imported and exported throughout SADC and the African continent.

As airlines strive to maximize market share, an increase in the number of competitors will lead to a

decrease in the market share of individual airlines. Airlines will need to emphasise aspects of service

such as reliability, safety and the level of service provided in order to mitigate against market share

losses. Although airlines will experience a fall in market share due to an increase in the number of

players in the market, the overall size of the market is expected to grow rapidly, which will result in

individual airlines, in the main continuing to grow despite falling market share.

Airlines that will benefit the most from implementing the YD are typically strong network and alliance

carriers, while small charters and weak state owned carriers may not survive. Strong network alliance

carriers will survive the intense competition which may result in a decrease in fares as these carriers

have financial muscle and easy access to capital for rapid expansion. Large airlines will feel intimidated

as new airline start serving the same routes and will feel threatened by the increase of operators, but

airlines with a large market share will be better off than small airlines which may not be able to compete



Muller Associates

as efficiently. Weak state owned airlines are characterised by old out-dated aircraft fleets that, together

with reluctance to embrace change, will limit expansion possibilities.

The state of airport infrastructure will have a significant influence in determining the effect of

implementing an air transportation liberalisation agreement. If YD is implemented, infrastructure

constraints will restrict transformation of the aviation industry as current infrastructure will not be

sufficient to cope with the resulting growth of air traffic volumes. Implementation of YD will result in an

increase in flight frequencies around Africa and infrastructure investment will need to be facilitated to

ensure that capacity is enhanced to cater for these demands. Currently, air traffic control, airport

runway capacity, airport runway length, baggage handling, security and even freight logistics capacity is

in the hands of government departments that will be incapable of responding to the increased demand.

There is insufficient capacity to accommodate increased number of flights in terms of limited airport

runway slots, restricted manpower and expertise in air traffic control, airport runway lengths at some

airports, not enough capacity to handle large numbers of passengers and baggage and a strained and

inadequate security at most airports. These constraints will have to be addressed before YD is

implemented and failure to do so will result in dire consequences such as flight delays, loss of baggage,

security threats and safety concerns. Airports will have to ensure that facilities comply with minimum

standard requirements. Customs facilities, information technology infrastructure and effective airport

security are some of the issues that will need to be revised and addressed in order to successfully

benefit from the YD agreement. Privatisation of many of these services is probably a necessary reform

for successful implementation of YD.

If SADC undertakes a comprehensive implementation of an air transportation liberalisation agreement,

airlines feel that it would open up the opportunity to review the mix of aircraft types, assessing the need

for both bigger and smaller types of aircraft on certain routes, existing and new. Implementing YD will

create additional job opportunities on both existing and new routes, creating the opportunity to expand

network reach and frequency leading to additional and increasing competition , lowering of prices for air

tickets and ultimately to an increase in market size, revenue and profits. Airlines will be willing to

operate on new routes as well change some of the current routes so as to avoid stopovers and hub

transfers by introducing direct flights to more destinations. In relative terms YD will disadvantage small

local airlines because they are less likely to have access to investment funding for expansion which

larger, mainly international airlines will be able to access more readily. All airlines will, nevertheless,

have the potential to benefit from YD if management embraces the business opportunities that will be

on offer.



Muller Associates

2.3.2 Airports

If YD is implemented in the SADC region, then an increase in the number of flights to both current and

new airport destinations can be expected. Therefore, airports that are currently being utilised (as hubs

or as international gateways) will experience an increase in inbound and outbound flights, while some

airports (with adequate infrastructure, not receiving international flights) that are underutilised will also

experience an increase in inbound and outbound flights.

Receiving only two responses from major airport companies may not clearly indicate the impact on

airports of implementing the YD but feedback does provide a basic idea about the implications that the

YD will have on airports. Feedback was received from two airport companies profiled in Table 2.3-2

below:

Table 2.3-2 Airports Data

Company / Organisation


Annual Turnover

Main sources of income Ownership Owners

Airports Company of South Africa

(ACSA)

South Africa R 3.17 billion

Aeronautical revenue, landing fees, passenger service charges, aircraft parking, commercial revenue, advertising, retail, parking, car hire, property rental, premiums received

Partly owned by government

74.6% domestic government ownership,

25.4% domestic private ownership

National Airports Corporation Limited

Zambia US $ 26.7 Million

Aviation - landing, passenger service charge, parking, ground handling, air navigation charges and Non-aviation - rentals, car parks, concessions, advertisements

Fully owned by government


The main sources of income reported by airports include aviation business - landing, passenger service

charge, parking, ground handling, air navigation charges and non-aviation business - rentals, car parks,

concessions and advertisements. Major airports within the SADC are either fully or partly owned by the

government thus any commercial benefit to the airport will have an impact on the country’s economic

conditions, directly and indirectly.

While airports authorities agree with airline operators that the YD agreement is good in principle, they

also feel that implementation has been poor. The YD agreement will improve revenue generation as

more airlines will operate from various airports, in turn, positively impacting the profitability of airports.

Thus, an introduction of the fifth freedom will lead to a removal of restrictions, allowing more airlines to

operate freely on numerous routes previously forbidden. YD will also stimulate traffic growth and make

travel more affordable by introducing more intense market competition. Lack of progress with

implementation has resulted in constrained aviation industry conditions prevailing in the past and while

much consideration needs to be given as to how to pave the way forward, airports authorities state that



Muller Associates

a huge transformation in airport operation will need to occur and this will have to be done with many

parties involved, including private sector investment and management.

Bottlenecks identified by airport authorities are identical to those mentioned above and include:

Lack of government commitment to YD

Lack of SADC commitment to YD

National flag carriers resistance to YD

In order to successfully implement YD, governments will need to remove bottlenecks that hinder the

free flow of private sector investment and participation in the air transport industry. This can be done by

granting the fifth freedom and at the same time helping local air transport businesses to partner with

international or local large participants in the industry to form alliances to ensure that they will survive

under the intense competition that is characteristic of a successful implementation of an air

transportation liberalisation agreement. This will result not only in rapid growth as lower prices

stimulate economic activity, but will also encourage quality in the aviation industry through providing

consumers with choice and providing local airlines the opportunity to participate in this growth through

the introduction of innovative approaches to service provision.

The impact of YD on airports will be:

Frequency of flights – increase on certain routes

Capacity – increase

Pricing – decrease

Volume of freight business – likely to increase, dependent on demand and pricing structure (affordability)

Airports expect an increase in frequency of flights on certain more popular routes which would lead to

an overall increase in frequency of flights at many airports. Increase in flight frequencies will lead to an

increase in capacity as more flights to more varied destinations will become available. Ticket prices will

decrease due to increased competition. Although no indication of the trend of airport charges has been

mentioned, increased choice and economies of scale should drive airport charges down as well. Volume

of freight business will be dependent on demand and pricing and if pricing decreases, there will be an

increase in the volume of freight into and out of airports thus relieving other modes of transport

especially road .

Increased aviation activities will certainly have a positive effect on the commercial standing of all

airports within SADC, however airports enjoying the highest demand will benefit at a larger scale than

those enjoying less demand. Implementation of YD will create a climate characterised by an increase in

demand for aviation services in general, however the decision itself will not convert into automatic

demand for more flights at any individual airport. Airports will be afforded the opportunity to grow

their business if there is a pro-active move on the part of individual airport management teams to



Muller Associates

attract business in the more open and flexible environment that will accompany implementation of YD.

As more flights are introduced, revenues will rise, encouraging airports to further expand capacity in

order to facilitate continually increasing levels of aviation activities.

Potential infrastructure constraints such as airport runway capacity, airport runway length and baggage

handling facilities will need to be addressed as these will cause bottlenecks and may lead to delays and

inefficiencies in service support, which will discourage rather than encourage new business.

Infrastructure constraints are likely to significantly restrict the potential benefits associated with

implementation of YD if airspace and airport capacity is limited by inadequate infrastructure investment.

Not all airports have the facilities and infrastructure to accommodate all sizes of aircraft and large

increases in air traffic volumes. Airport planners will need to ensure that facilities are of adequate

capacity to meet increased levels of demand and are compliant with minimum standards in order to

fully benefit from the implementation of YD.

Airlines will be free to develop routes more easily and open up new markets for travellers, the overall

the impact of air transportation liberalisation on airports will be to increase potential revenues which

will, in turn, justify investments in upgraded airport infrastructure and facilities.

2.3.3 Other Stakeholders in the aviation industry

Other stakeholders in the aviation industry include small charter operators, aircraft leasing companies,

aircraft sales and maintenance businesses, cargo and freight service operators and mail services.

Currently these are typically small operations that service a niche market and offer specialised services

such as package tours, domestic charter or scheduled flights. Stakeholders in this category that

provided feedback are listed in the schedule overleaf.

Most of the above named stakeholders are small charter operators with the exception of Mistral

Aviation, which specialises in landing gear overhauls and aircraft brake maintenance, Airline Association

of South Africa (AASA), which is a non-profit organisation providing guidance to SADC airlines and

Swissport Tanzania, which is a ground handling and cargo services company.

More than half the stakeholders stated that the agreement reached at YD was positive for the industry

because it provided greater opportunity for start up airlines to compete with established airlines and

level the playing field by allowing competitive operators freer access to potentially lucrative markets.

Implementation of YD will also allow established airlines to serve a broader market without

encountering rigid barriers that have previously restricted their operations. Some stakeholders feel that

the YD agreement has been poorly received because it was adopted out of the recognition that the

restrictive and protectionist intra-African regulatory regime based primarily on bilateral air services

agreements (BASAs) has historically hampered expansion and improvement of air transportation on the

African continent. As such, existing vested interests, which often rely on old, poorly maintained aircraft

operating out of poorly managed airports, feel threatened and have consequently successfully resisted

multi-lateral implementation of YD.



Muller Associates

Other Stakeholders that responded are profiled in Table 2.3-3 below:

Table 2.3-3 Stakeholders Data

Company / Organisation


Annual Turnover

Main sources of income Ownership Owners

AirQuarius Aviation

South Africa R 101 million

Aircraft leasing and charter Private

company

Private ownership

NAC South Africa R1,9 billion Aircraft sales, aircraft maintenance, aircraft leasing, aircraft (rotor and fixed wing) charter, aircraft management

Privately owned company


Airline Association of Southern Africa (AASA)

South Africa n/a Membership subscriptions and management fees

Non-profit privately owned company

Private ownership

Mistral Aviation Services

South Africa R10 - R12 million

Aircraft brakes and landing gear overhauls

Private

company

Private ownership

Namibia Commercial Aviation

Namibia $ 7 million Namibian

Tourism and incentive charters Private

company

Private ownership

Phoebus Apollo Aviation

South Africa Passenger/ cargo scheduled/ charter flights and wet-leasing of aircraft

Sole proprietorship

Private ownership

Precision Air services Ltd

Tanzania $65 million US

Provision of scheduled passenger, freight and mail services

Private

Partnership

51% domestic private, 49% foreign private

Proflight commuter services

Zambia $ 8 million US

Charter operations Private

Partnership


Swissport Tanzania

Tanzania T Shs 18.528 million

Ground handling, cargo services Private

Partnership


One of the vital principles of YD is market liberalisation, which is viewed as a means to stimulate the

development of air services in Africa and attract the flow of private capital into the industry. In essence

the agreement reached is solid and the theory makes sense for Africa and for airline industry

stakeholders. In practice, however, YD made assumptions regarding compliance by individual countries

that have not been realised. The heads of state came to an agreement, but at “grassroots level” many of

the stakeholders (and individual managers in stakeholder entities) have not been committed to YD and

may have actively resisted implementation of the agreement. Implementation of YD has thus been very

limited and stakeholders believe that national governments have resisted implementation with the

result that no meaningful progress has been made since the agreement was reached.

The Yamoussoukro Decision, which came into force in 2000, evolved from the Yamoussoukro

Declaration of 1988. However, throughout the intervening years, the full potential of YD to unlock

commercial opportunities for African airlines has not been realised and implementation has been

virtually non-existent. A sub-committee on air transport established by this decision and monitored by a



Muller Associates

body comprised of representatives from Economic Commission for Africa (ECA), African Union (AU),

African Civil Aviation Commission (AFCAC) and African Airlines Association (AFRAA) then overseen by an

executing agency has not carried out the duties set out in the declaration even though a large fund was

set aside for implementation. The explicit roles of these organisations were unclear thus no action was

taken due to the confusion. Only a few countries practise true “air transportation liberalisation”. These

are mainly countries which have implemented bilateral agreements instead of letting airline companies

get on with freely operating the routes and frequencies that they want to as envisaged by YD.

The following factors have been identified by stakeholders as hindering the full implementation of YD:

Lack of individual national government commitment to YD

Lack of SADC commitment to YD

National flag carriers resistance to implementation of YD

A lack of laws promoting free competition regionally

A lack of laws promoting free competition within individual countries

Corruption

Poor legislation

Political instability in some African countries

Poor/substandard airport infrastructure in Africa

Airport security concerns

Lack of start up capital for would be operators

European Union blacklisting of African airlines

Lack of clarity regarding the roles of the various sub-committees and monitoring bodies

Lack of commitment and action by ministry officials

Lack of incorporation of the principles of YD, as appropriate and necessary, into national legislation

Lack of infrastructure (no effective executing agency and other monitoring structures)

Government protection of airlines from competition (preserving of state monopolies)

The above have been identified as factors which hinder the successful implementation of the YD and will

need to be addressed before any progress can be made. Governments need to amend aviation policies

and legislation accordingly. Before implementation, a plan needs to be formulated to include all

stakeholders in a participative process to evaluate options and develop a well rounded policy that will

benefit all stakeholders including the governments involved. It is important that the appropriate officials

are mandated to implement the YD within a specified time frame. Existing bilateral government

agreements should be amended to remove limits on frequency and capacity.



Muller Associates

A possible approach would be to involve a larger authority in decision making. The African Union (AU) is

Africa’s premier institution and is the principal organization for the promotion of socio-economic

integration on the continent. The AU is also the monitoring body established to oversee

implementation of the Yamoussoukro Decision. Given the AU’s objective to promote sustainable

development and to integrate African economies, the African Union (AU) is best positioned to provide

the necessary oversight platform for steering implementation of the Yamoussoukro Decision and

liberalization of the air transport industry in Africa. Its recent moves to actively support the African Civil

Aviation Commission (AFCAC) and the various regional economic communities (RECs) demonstrated the

willingness of the organization to accept leadership. Individual national governments need therefore to

support the AU and provide the necessary funds and resources to assist the AU in this regard.

If implemented successfully, the impact of the YD would be immensely positive for countries partaking

in the decision. It would create an environment for the development of intra-African and international

air services, liberalized intra-African aviation markets and highly stimulatory developments concerning,

traffic rights, capacity, frequency and pricing. YD will lead to the rapid development of inter-African air

transport activities and improved quality of service to consumers. Sub-regional services will be

encouraged to merge and grow as well as permit air transport services to privatise. With the

implementation of YD, countries will establish safe, reliable and affordable air transport services that are

attractive to customers and that will stimulate a freer and much higher level of movement of persons,

goods and services in Africa. Implementation of YD may also protect African airlines from European and

other non-African competitors and eliminate barriers that hamper the sustainable development of air

transport services. African airlines will be able to create a strong regional base from which they can

expand and compete with international airlines by forming international alliances and strong business

partnerships that will assist in future growth and development. Although the impact is largely expected

to be positive, stakeholders do recognise that some countries may struggle to adapt mainly due to a

misguided commitment to outdated aviation practices and equipment. Countries that are reluctant to

embrace transformation and face competition will eventually suffer dire consequences in respect of

their own national airlines and other aviation industry stakeholders as continent-wide competition

overtakes those who refuse to adapt.

Stake holders agree that companies throughout Africa that embrace the changes implied by full

implementation of YD will be able to build strong partnerships with other operators around Africa and

further afield and will enjoy the chance to exploit the many opportunities available to them. Airlines will

benefit as it will be easier to obtain quicker flight clearances and all fees surrounding flights which

include landing and parking fees should be more competitive as opposed to companies not based in

Africa. Increased scheduled flight services will act as a catalyst for economic growth within the

continent. The financial benefit gained from implementing the YD will be significant for almost all

participants as there will be greater freedom, more capacity to accommodate new routes, increased

revenue for all stakeholders. Implementation of YD will create the opportunities to increase aircraft

fleets for both new and established operators as they build their capacity to serve the higher levels of

demand created from the implementation. Thus, not only will airlines benefit, but also companies that

service, lease and maintain aircraft will reap benefits.



Muller Associates

The view of stakeholders is that the companies most likely to benefit from the YD will be start up and

low cost operators, regional airlines, established airlines and airlines that can sustain the more intense

levels of competition. With the freedom to operate on any routes airlines will prioritise the most

lucrative ones. Small carriers will have the opportunity to expand and diversify their current flight

operations. Companies involved in maintenance and aircraft leasing will benefit from the opening of

new potential markets enabling stakeholders to widen their business horizons. Some stakeholders feel

that emerging airlines will be faced with limited growth while established airlines that already have a

strong base in the market will find it easier to attract new business. Companies least likely to benefit

from the YD are underperforming domestic carriers, inefficient national carriers and companies that are

unable to compete effectively.

Infrastructure constraints that stakeholders indentified as possibly restricting implementation of YD are:

Air traffic control

Airport runway capacity (no. of slots)

Airport runway length

Baggage handling

Security

Freight logistics capacity

The above constraints are the same as those mentioned by both the airlines and airports groups of

stakeholders. Stakeholders are mainly concerned that those factors that will affect the smooth

operation of companies due to the increased demand that will result once the YD has been

implemented. In some countries, where services have not been upgraded to meet international

standards, infrastructure may not be able to cope with the increased air traffic. In many cases airports

are not geared to accommodate large aircraft and thus they do not have sufficient capacity or the

appropriate runway length for modern aircraft. In terms of freight logistics, airports and freight

companies would have to ensure that they can handle an increase in freight and cargo volumes by

creating efficient cargo hubs. Air freight usually consists of perishable goods that have a short life span

and must be handled with speed and without delay. One of the biggest passenger concerns when

travelling around Africa is baggage handling and security. This would have to be addressed effectively

and measures need to be taken to ensure that no compromises are made.

A comprehensive air transportation liberalisation agreement would be a great benefit to all stakeholders

in the aviation industry as it gives companies the opportunity to investigate new markets and routes and

source new and modern equipment in partnership with other operators. This will inevitably lead to

structural changes to some of the companies to allow for ongoing expansion. Expansion will benefit not

only the company but the economy as whole through creating employment and generating higher levels

of revenue. The implications for ground handling companies are also positive as the increased demand

will require larger operations allowing these companies to expand; however, these trends may also

attract an increase in competition. Stakeholders are generally realistic in recognising that before any of



Muller Associates

the benefits are enjoyed, infrastructure investment will be required to accommodate the increase in

flights, passenger numbers and cargo volumes. Some stakeholders are concerned that they may not be

able to survive as they will get swallowed by the competition of an open market and thus are not

entirely enthusiastic about the implementation of YD.

Overall, however, airlines, airports and other stakeholders are positive about the implementation of YD

but are sceptical about the progress made to date and likely to be made into the future. Stakeholders

support the idea behind YD and are willing to open their markets to Africa but are not certain that the

current infrastructure, legislation and policies support the rapid implementation of such a decision.



Muller Associates

2.4 Cost-Benefit Analysis Methodology

2.4.1 Model

2.4.1.1 Introduction

The demand forecast model predicts the potential routes that airlines could operate in the South African

Development Community (SADC) under an air transportation liberalisation regime. It is principally based

on the gravity method described in the literature review. The gravity model traditionally uses the size of

the origin (city or country) times the size of the destination as an indication of the demand for flights

between them. This model assumes that the bigger the population size or GDP of the origin and the

population size or GDP of the destination, the bigger the attraction and demand for flights. Equation (1)

shows the typical mathematical equation that would be used to determine the potential demand

between an origin and destination.

Equation (1) Demand = (GDP Origin * GDP Destination)/Distance

For the purpose of this study the demand forecast model has been based on the principles of the gravity

model, by using data from origin and destination location in a similar fashion as Equation 1 above (this

will be explained in the sections that follow.) In the sections to follow it will be shown how a demand

forecast has been predicted for each potential route in the SADC region and this forecast has been

weighted between 0 and 1 (0 being very low demand and 1 being extremely high demand). The model

excludes all airports with a runway length shorter than 6500 feet (1.98 km), as airlines and aircraft

manufacturers cited this length as a minimum for commercial aircrafts and aircrafts designed to carry

freight, and runways that are unpaved. Routes that are less than 200 km were excluded, due to

ineffectiveness of flying distances this short.

2.4.1.2 Data Utilised To Calculate Demand Forecast Indicator

The demand forecast indicator takes into account various indices for each airport that fit the description

discussed above. The indices accounted for include:

Country’s gross domestic product per capita;

Population of origin and destination cities;

Country’s urban population for 2005;

The business, politics and development index indicators;

Tourism infrastructure index;

Whether the origins and destinations fall internally within one country;

Airport infrastructure; and

Distance between the various origins and destinations.



Muller Associates

A brief description of these various data sets and indices follows in the remainder of this section.

2.4.1.2.1 Gross domestic product per capita

The gross domestic product per capita has been sourced from the International Monetary Fund website.

The GDP per capita figures used are stated in US$ 2007 at current prices and are displayed in Table 2.4-1

below. GDP per capita was used as countries with a higher GDP per capita are more likely to demand

more flights as flying is still largely a luxury form of transport in Africa.

Table 2.4-1 Gross Domestic Product Per Capita, Current 2007 Prices Country GDP per capita US$

Angola 5,276.83

Botswana 8,032.88

Democratic Republic of Congo 174.068

Lesotho 706.021

Madagascar 430.419

Malawi 268.594

Mauritius 5,891.24

Mozambique 420.611

Namibia 3,502.10

Seychelles 8,482.88

South Africa 6,185.43

Swaziland 2,380.52

Tanzania 392.434

Zambia 957.335

Zimbabwe 139.754

2.4.1.2.2 Population by city

Where a city has an airport with the appropriate runway length and surface, the rough population of

that city has been taken into account. It has been assumed that the larger the city, the higher the

demand for flights to and from that city. A full list of cities in the SADC region and the population levels

for each of these cities was obtained from http://www.tageo.com/index.htm. This data was used to

create relative proportions for each of the cities, thereby determining the ranking of cities expected to

have a higher demand for flights under an air transportation liberalisation regime. A table listing the

populations used by city can be found in Appendix F.

http://www.tageo.com/index.htm



Muller Associates

2.4.1.2.3 Urban population

In addition to the city population data, each country’s urban population levels were gathered from a

United Nations database (http://data.un.org/Default.aspx). Urban population data for 2005 for the

SADC countries in question was utilised. This data is shown in Table 2.4-2, below. These figures have

been taken into account to determine a ranking of origin and destination cities that could be expected

to have a higher demand for flights under an air transportation liberalisation regime based on the

overall urban population of the countries where these sites are located.

Table 2.4-2 Urban Population by Country Country Urban population

Angola 5,930,052

Botswana 926,625

Democratic Republic of Congo 18,818,523

Lesotho 326,690

Madagascar 5,023,620

Malawi 2,216,048

Mauritius 545,310

Mozambique 7,520,960

Namibia 680,385

Seychelles 46,980

South Africa 27,463,128

Swaziland 246,648

Tanzania 14,373,375

Zambia 4,258,820

Zimbabwe 4,670,590

2.4.1.2.4 Business, politics and development index indicators

The business, politics and development indicators have been drawn from various sources and have been

combined to create one weight in the demand forecast model. The business information which included

the ‘Country Risk Rating (September 2008)’ and ‘Global Competitiveness Index (2007-2008)’, is sourced

from the World Economic Forum (gcr.weforum.org). The political information is sourced from the ‘Press

Freedom Index (2008)’ and can be found in the Reporters Without Borders website

(http://www.rsf.org/). The development information utilised is the ‘Human Development Index (2006)’

from the United Nations Development Program (http://hdr.undp.org/en/statistics/). These indicators

are summarised in Table 2.4-3, overleaf. Each of these indicators has been modified to be rated

between 100 and 0 (with 100 being an excellent rating and 0 being an extremely poor rating). The

various indicators have been averaged in the last column of the table and these averages have been

used in determining the demand weighting for each qualifying airport.

http://data.un.org/Default.aspx

http://www.rsf.org/

http://hdr.undp.org/en/statistics/



Muller Associates

Table 2.4-3 Business, Political and Development Indicators for SADC Country Country Country Risk Rating

(Sept 2008) Global Competitiveness

Index (2007-2008) HDI

2006 Press Freedom

Index (2008) Average

Angola 36 45 48.4 70.5 50.1

Botswana 65 60.71428571 66.4 86 69.6

Democratic Republic of Congo 30 41.14285714 36.1 48.75 39.0

Lesotho 41 48.57142857 49.6 70.5 52.3

Madagascar 35 48.28571429 53.3 79 54.0

Malawi 35 48.85714286 45.7 85 53.6

Mauritius 56 60.71428571 80.2 91 72.0

Mozambique 41 45 36.6 79.5 50.5

Namibia 40 57 63.4 94.5 63.7

Seychelles 40 60.71428571 83.6 84.5 67.2

South Africa 60 63 67 92 70.6

Swaziland 38 48.57142857 54.2 49.5 47.6

Tanzania 39 49.85714286 50.3 85 56.1

Zambia 36 49.85714286 45.3 84.5 53.9

Zimbabwe 30 41.14285714 32.1 46 37.3

Source: World Economic Forum (gcr.weforum.org), Reporters Without Borders website (http://www.rsf.org/) and United Nations Development

Program (http://hdr.undp.org/en/statistics/)

2.4.1.2.5 Tourism infrastructure index

The level of tourism infrastructure is likely to influence the number of flights demanded in each country

under an air transportation liberalisation regime. Countries with modern and developing tourism

infrastructure tend to attract far more tourists; therefore the ‘Tourism Infrastructure index’ was sourced

from the World Economic Forum website (http://www.weforum.org/documents/TTCR09/index.html).

This index takes into account the following:

Air transport infrastructure in each country,

Ground transport infrastructure,

Tourism infrastructure,

Information and Communication Technologies (ICT) infrastructure and,

Price competitiveness in the transport and tourism industry.

The tourism infrastructure index is measured between 7 and 0 (with 7 representing excellent tourism

infrastructure and 0 representing extremely poor tourism infrastructure.) The tourism infrastructure

index for each SADC country is summarised in Table 2.4-4.

http://www.weforum.org/documents/TTCR09/index.htm



Muller Associates

Table 2.4-4 Tourism Infrastructure Index by Country Country Tourism Infrastructure Index

Angola 3.05

Botswana 4.125

Democratic Republic of Congo 3.1

Lesotho 3.05

Madagascar 3.425

Malawi 3.025

Mauritius 5.05

Mozambique 3.05

Namibia 4.075

Seychelles 5.05

South Africa 4.775

Swaziland 3.05

Tanzania 3.2

Zambia 3.325

Zimbabwe 3.1

2.4.1.2.6 Airport infrastructure

Airport infrastructure influences the demand forecast for routes. Where infrastructure is lacking, so is

the supply of flights. A detailed list of airport infrastructure has been obtained from the International

Civil Aviation Organisation. This data indicates the airports with an instrument procedure list (a landing

procedure manual for pilots), airports with runways, airports with customs facilities, and whether the

airports run privately, publicly or by the military. An example of the information utilised can be seen in

Table 2.4-5 below, where an airport which has a given infrastructure is given a value of 1.

Table 2.4-5 Airport Infrastructure Airport Country Usage Customs Runway

Paved Instrument Approach Procedure

Previously Served Airport

Luanda Angola Civil 1 1 1 1

Gaborone Botswana Civil 1 1 1 1

Maseru Lesotho Civil 1 1 1 1

Antanànarìvo Madagascar Civil 1 1 1 1

Lilongwe Malawi Civil 1 1 1 1

Port Louis Mauritius Civil 1 1 1 1

Maputo Mozambique Civil 1 1 1 1

Windhoek Namibia Civil 1 1 1 1

Johannesburg South Africa Private 0 1 1 0

Johannesburg South Africa Civil 1 1 1 1

Dar-Es-Salaam Tanzania Civil 1 1 1 1

Lusaka Zambia Civil 1 1 1 1 Source: International Civil Aviation Organisation



Muller Associates

2.4.1.2.7 Domestic flights

Domestic routes within one country exhibit higher flight supply than international routes. Therefore

where air routes are entirely domestic a positive weighting of one has been assigned.

2.4.1.3 Determining the Demand for Each Potential Route in SADC

2.4.1.3.1 Method of calculating the indices for each factor

As already mentioned, each of the aforementioned data sets for each of the potential pairs of airports in

the SADC region has been converted into an index between 0 and 1. The calculation of these indices

varies according to the data available; the 1 and 0 index only considers two airports. The varied data

results in a varied effect on the ultimate anticipated demand for flights to and from various destinations.

The indices have been calculated by one of two methods, the dimension index method or as a

proportion.

2.4.1.3.1.1 The dimension index method

For each indicator a minimum and maximum goalpost must be defined and then the indicator must be

normalized between 0 and 1, based on the country or the airports relative position. This concept is

displayed in Box 2.4-1 below.

Box 2.4-1

Actual value

of indicator

Minimum of indicator|------------x------------------|Maximum of indicator

Index =(Actual value of indicator) – (Minimum of indicator)

(Maximum of indicator) – (Minimum of indicator)

Where this method was utilised in determining the various indices it was observed that those indices

would tend to supply more flights if they started from a low level of operation. This was evident when

considering GDP per capita (discussed in detail below). Therefore each indicator was logged, as seen in

Box 2.4-2.

Box 2.4-2

Index = log (Actual value of indicator) – log (Minimum of indicator)

log (Maximum of indicator) – log (Minimum of indicator)



Muller Associates

In the case of GDP per capita this effectively means that increases in income at a lower level has a

greater impact on the GDP per capita index, as shown in Figure 2.4-1 below.

Figure 2.4-1 GDP per Capita Index

2.4.1.3.1.2 Proportion method

The proportion method was used where data had already been taken from an existing index. This was

effectively converted into an index between 0 and 1, where proportions were maintained.

2.4.1.3.2 Gross domestic product per capita index

The GDP per capita index used the dimension index method to determine the weight of the index. The

calculation of the GDP per capita index assumes that an air transport liberalisation agreement in SADC

will make flying more affordable and that those individuals with lower income levels. These individual

will switch to air transportation when cost and amount of time travelling between various cities within

the SADC region decreases. Therefore the higher an individual’s income and countries GDP per capita

the higher the amount of people utilising air transport as method of transportation. Thereby as incomes

increase within a country the transition from road and rail transport to air transport will increase at an

increasing rate due to new low cost carriers entering the market.

2.4.1.3.3 Urban population of countries

Urbanization has increased significantly around Africa; we would expect this over the next 50 years.

Governments increasingly will be required to respond to this phenomenon with appropriate social,

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

GD

P p

er

cap

ita

Ind

ex

GDP per capita, US$ (2007)



Muller Associates

political and economic interventions that would lead to increased job creation and economic activity

around urban centres. As shown in the literature review one of the basic assumptions of the gravity

model is that increased urban populations will lead to an increase in demand for flights.

Once again the dimension index method is utilised, since countries moving off a low base of

urbanization would, under an air transportation liberalisation regime, demand flights from low income

carriers more rapidly as the population urbanises. The bias towards countries with lower urban

populations follows the argument presented by Swan (2008) in the literature review where under an air

transportation liberalisation agreement between countries flights and aviation development shift away

from the traditional airport hubs to the more decentralised airports and cities. This has been observed in

South Africa over the last decade where low income carrier airlines have increasingly expanded their

destinations to urban centres with lower populations such as the Durban to George, Durban to Port

Elizabeth and Johannesburg to Windhoek or Gaborone flights (www.1time.aero & www.kulula.com).

This is a trend that has also been displayed in the European Union and India where routes have began to

expand to traditionally less well serviced airports and cities with lower populations.

2.4.1.3.4 Population by city

Similar to the argument above it is anticipated that cities with higher populations tend to demand more

flights, and with the implementation of air transport liberalisation agreement in SADC it is expected that

there will be a gradual shift away from the traditional airport hubs and major urban centres. Once again

the dimension index method was employed to determine an index level for each airport.

2.4.1.3.5 Business, politics and development index indicators

The countries business, politics and development index indicators were already in index form. They

were converted into proportions between 0 and 100 as shown in Table 2.4-3 above. These were then

averaged and then converted to an index between 0 and 1, maintaining the established proportions.

2.4.1.3.6 Tourism infrastructure index

Likewise the tourism infrastructure index has already been established by the World Economic Forum as

shown in Table 2.4-4. These indices fall between 0 and 7 for each country, thus we divided each of these

indices by 7 to establish proportion between 0 and 1.

2.4.1.3.7 Airport infrastructure

As seen in Table 2.4-5, above, airport infrastructure for the various airports in SADC has been rated

between 0 – 1, depending on whether an airport has the infrastructure in place for the four factors

listed. To calculate this into an index we added the factors together and divided by 4 to yield an airport

infrastructure index.



Muller Associates

2.4.1.3.8 Example of calculated Indices

Table 2.4-6, below, gives an example of the various indices discussed for the main airports of each SADC

country.

Table 2.4-6 Example of Calculated Indices by Airport Airport Country Airport

Infra. GDP per capita

City Pop.

Urban Pop.

Business, Politics & Development

Tourism Infra.

Luanda Angola 1 0.8991 0.9169 0.6740 0.5006 0.4357

Gaborone Botswana 1 0.9802 0.6707 0.4189 0.6958 0.5893

Kinshasa DRC 0.95 0.2407 0.9747 0.8328 0.3900 0.4429

Maseru Lesotho 1 0.5109 0.6379 0.2756 0.5232 0.4357

Antanànarìvo Madagascar 1 0.4154 0.8308 0.6512 0.5397 0.4893

Lilongwe Malawi 1 0.3244 0.7513 0.5387 0.5364 0.4321

Port Louis Mauritius 1 0.9203 0.6432 0.3460 0.7204 0.7214

Maputo Mozambique 1 0.4110 0.8562 0.7067 0.5048 0.4357

Windhoek Namibia 1 0.8200 0.6928 0.3764 0.6373 0.5821

Seychelles Seychelles 1 0.9907 0.4969 0.0025 0.6719 0.7214

Johannesburg South Africa 1 0.9297 0.9604 0.8847 0.7062 0.6821

Manzini Swaziland 0.9375 0.7455 0.6013 0.2369 0.4757 0.4357

Dar-Es-Salaam Tanzania 1 0.3976 0.8960 0.7980 0.5605 0.4571

Lusaka Zambia 1 0.5697 0.8346 0.6285 0.5392 0.4750

Harare Zimbabwe 0.875 0.1983 0.8902 0.6412 0.3731 0.4429

2.4.1.4 Utilising the Gravity Model to Establish the Route Demand

Determining the demand for each factor above between airports in SADC requires use of the gravity

model, where similar factors are averaged to determine a combined index per route. The methods

employed in the model are shown in Box 2.4-3 overleaf.

Box 2.4-3

Equation (2) Factor Demand = (Factor Index airpory A

) + (Factor Index airport B

)

2

Example: GDP demand airport A&B

= (GDP per capita index airport A

) + (GDP per capita index airport B

)

2

To determine the estimate route demand, each of the factor demands needs to be combined. The

model in question has done this by assigning weights to each factor depending on the importance that

this factor has on overall demand. See equation (3) in Box 2.4-4 below. The model allows these weights



Muller Associates

to be changed for the various demand factors on the tab ‘Weights & Proportions’. Table 2.4-7 below

gives an example of how the demand estimates for each potential route in SADC has been calculated

using the weights. The higher the demand estimate the higher the number of flights will be demanded.

Box 2.4-4

Equation (3) Route demand = (GDP demand airport A&B

x A)+(City pop demand airport A&B

x B)+(Urban pop demand airport A&B

x C)+(Airport infra demand

airport A&B x D)+(Bus, Pol & Dev demand

airport A&B x E)+(Tourism infra demand

airport A&B x F)

where: A + B + C + D + E + F = 100%

Table 2.4-7 Determining the Demand Estimate for Routes Airports Same

Country Airport Infra-structure

GDP per capita

City Populatn

Urban Populatn

Business, Politics & Development

Tourism Infra-structure

DEMAND ESTIMATE

Weight 15% 5% 20% 25% 5% 20% 10% 100%

Windhoek Johannesburg 0 1 0.8748 0.8266 0.6306 0.6717 0.6321 0.6607

Cape Town Johannesburg 1 1 0.9297 0.9363 0.8847 0.7062 0.6821 0.8737

Durban Johannesburg 1 1 0.9297 0.9302 0.8847 0.7062 0.6821 0.8722

Johannesburg Lusaka 0 1 0.7497 0.8975 0.7566 0.6227 0.5786 0.6445

2.4.1.5 Time Frames

There are 3916 potential routes in the SADC region. These routes are comprised of 89 airports with

paved runways that are longer than 6400 feet. Not all of these routes will be feasible or cost effective in

the short run, particularly if the current aviation market in SADC is taken into account. However, in the

long term there is no reason for these routes not to become feasible, provided infrastructure, business

and income levels continue to improve in each country. Therefore the model is structured such that it

determines demand, potential turnover and seat numbers over a 50 year period.

In the first 5 years post implementation of an air transport liberalisation agreement in SADC, it can be

expected that all the routes that are currently being operated by national flag carriers and low cost

carriers would expand and attract new airlines and lower prices. New routes are unlikely as airlines and

airports adjust to the new market regulations and demands. The first five years post the air transport

liberalisation agreement in SADC only takes into account current routes being used. After 10 years the

model predicts that routes with a demand estimate of greater than 0.75 would see new flights being

operated. After a 15 year period the model predicts that routes with a demand estimate of greater than

0.70 would see new flights being operated. The model continues in this fashion of decreasing the

demand estimate by 0.05 over 5 year intervals all the way to a 50 year time period where all routes have

been included in the model.



Muller Associates

2.4.2 Direct Impacts

2.4.2.1 Determining Potential Turnover and Seat Numbers per Route

This section deals only with the direct impact experienced by airlines if an air transport liberalisation

agreement was implemented in the SADC region. The red blocks highlighted in Figure 2.4-2 below

display the primary focus of this model, namely; introduction and expansion of new flights to both new

and existing destinations. Sections that follow will detail methodology used to estimate the direct and

indirect impacts.

Figure 2.4-2 Flow chart showing methodology for the section

The demand estimate for each route has been used to determine the potential turnover as well as the

seats demanded per week. The following section explains the methodology on how the figures for each

individual route have been determined.

The questionnaire sent to airlines revealed both current seat capacities and pricing per flight. We

received information on these from South African Airways (SAA), Comair (British Airways & Kulula.com)

and Airports Company South Africa (ACSA). This information combined with the now calculated demand

estimates between 0 and 1 reveals potential turnover and seat requirements on each route per week.

The model only takes into account data from South African domestic flights on very competitive routes

(namely: Durban to Johannesburg, Cape Town to Johannesburg and Cape Town to Durban.) This is

because of the vigorous competition of the established low cost carriers that operate on these routes.

An air transportation liberalisation agreement in the SADC region will encourage aviation competition

along all routes, which favours mostly low cost carriers.

Open SkiesDirect

Impacts

Airlines

Benefits New Flights

New destinations

Current Destinations

Costs

Airports

Passengers

Freight

Customs



Muller Associates

Table 2.4-8 shows how the supply of seats and potential turnover per route were determined. The

average seats per route, along with the minimum price per seat were obtained from Kulula, British

Airways and SAA questionnaires and online information. Multiplying these columns gives us the

estimated turnover per flight; this has then been adjusted for a 75% take up of capacity. (SAA stated in

their questionnaire that roughly 75% of capacity is taken up on flights). The distance in kilometres was

then used to determine the turnover per kilometre on the three routes, which as can be seen in Table

2.4-8 ranged from R 34.68 to R 40.64. The turnover per kilometre was then divided by the demand

estimate (these ranged between R 40.18 to R 46.60.) From these figures we determined if the demand

estimate was 1 then an average of R 43.71 per kilometre would be the potential turnover per kilometre.

The R43.71 per kilometre was then multiplied by:

Each routes distance in kilometres;

Each routes demand estimate; and

131.56 (the average number of flights per week to and from Johannesburg to each South African domestic destination, as obtained from ACSA), and this was used to estimate the potential turnover per week for each particular route.

To estimate seat numbers per week, the ‘average seats per flight’ (130) was multiplied by the 131.56

(average number of flights to and from Johannesburg to each South African domestic destination) and

then multiplied by each routes demand estimate. This calculated the estimated number of seats that

would be demanded on each particular route. From the estimated turnover and seat numbers per week,

an average ticket price per seat per flight was estimated.



Table 2.4-8 Potential Turnover and Seat Numbers Airport Demand

Estimate Average Seats / flight

Minimum Price

Estimated Turnover / flight

Capacity take up of 75%

Distance (km)

Turnover per km

Turnover per Km / Demand estimate

Potential Turnover per week

Seat Numbers per week

Average Ticket Price per flight

Cape Town

Durban 0.8630 123 R 480.00 R 59,040.00 R 44,280.00 1,277.00 R 34.68 R 40.18 R 6,336,564.47 7,361 R 430.42

Cape Town

Johannesburg 0.8706 136 R 480.00 R 65,440.00 R 49,080.00 1,271.43 R 38.60 R 44.34 R 6,364,160.74 7,425 R 428.55

Durban Johannesburg 0.8722 130 R 200.00 R 25,933.33 R 19,450.00 478.59 R 40.64 R 46.60 R 2,400,018.47 7,439 R 161.31

Average: 130 R 43.71 8,529

2.4.2.2 Passenger Time Saving

This section focuses on the benefit to passenger if an air transport liberalisation agreement is implemented in SADC. Passengers firstly benefit

from the decrease in airfares (due to increased competition among airlines), secondly from time saving now that airlines can bypass hub airports

and land in destinations of their choice. Due to the lack of the current aviation information collected from the survey questionnaires provided by

airlines it is impossible to determine the benefit that would accrue to passengers from a decrease in aviation prices. This price decrease would

also happen over a period of time and only as competition increases; competition currently is marginal in SADC and therefore it would be guess

work or complete speculation to predict how the competition would increase over time. Figure 2.4-3 displays how the passengers’ benefits fit

into the overall impact.



Muller Associates

Figure 2.4-3 Showing how passengers’ benefits fit into the overall methodology

The time benefit to passengers has been calculated by assuming that in order for a person to currently

travel between various locations in SADC they are required to travel through the major airports in each

country. This therefore means that a person wanting to travel from Durban, South Africa to Beira,

Mozambique would need firstly to travel OR Tambo, Johannesburg and then to Maputo, Mozambique

before connecting to Beira. This assumption has been followed for each potential origin and destination

in SADC. Due to the sheer volume of potential routes that are available under the regulation allowed by

an air transport liberalisation agreement, and the complexities of air travel in SADC this simplified

assumption has been adopted. Under an air transport liberalisation agreement in SADC flying from

origin to destination would be shortened because airline are allowed to fly directly from Durban, South

Africa to Beira, Mozambique, thus there is massive time saving due to the direct flight offered.

Figure 2.4-4 overleaf illustrates the assumption of current air travel around SADC. It can be seen that all

air traffic filters through a central hub within each country (yellow/gold lines to and from red points) and

then through the central airport hub in SADC, namely OR Tambo in Johannesburg (red lines to the

largest red point.) From this figure it can be seen that travelling around SADC can be costly in terms of

tickets, airport taxes and time. An air transport liberalisation agreement in SADC would eventually do

away with the large number of connecting flights and passengers could connect directly to their ultimate

destination.

With the distances travelled by passengers prior to an air transport liberalisation agreement in SADC and

the distances travelled post an air transport liberalisation agreement in SADC, there is saving in the

distance travelled by passenger (this distance saved can be translated into the amount of kilometres

saved in travel.) This distance can be converted into time when we take into account the average

cruising speed of a commercial aircraft. The current average cruising speed of a commercial Airbus,

Boeing or McDonald Douglas Aircraft is 900 kilometres per hour. With the amount of time saved in

Open Skies Direct Impacts

Airlines

Airports

Passengers Benefit Time Saving

Freight

Customs



Muller Associates

terms of air travel known and now converted into time savings per hour it is easy to calculate the time

saving benefit if you know the value of a passengers time in hours. Assuming the value of an hour for a

passenger is a tricky undertaking due to the cross section of passengers that make use of air travel

(these is an infinite number of reasons passenger fly and each of these would vary the value of time.)

For the purposes of this study it has assumed that a person utilising air transportation would values an

hour at R 200 (this is a completely arbitrary amount and a further study is required to understand a

passengers value time saved.)

Figure 2.4-4 Assumed flight patterns between origins and destinations pre air transport liberalisation in SADC

Source: adapted, Google Earth 2010



Muller Associates

2.4.2.3 Direct Costs to Airlines

The direct impacts likely to be experienced by airlines are divided into costs and benefits. For this study,

these costs have been broken down into five categories – cancellation costs, diversion costs, cost of fuel,

aircraft operation costs and increased accidents and incidents.

All data has been derived from the EUROCONTROL 2007 document1 and the Standard Economic Values

Guidelines report2. Where applicable, values sourced from these two documents have been converted

into 2009 Rands3.

The table below summarises the monetary value of the abovementioned costs. The cost of fuel and the

effect of an increase in the rate of fuel burn have been excluded from the table, and will be discussed

separately below.

Table 2.4-9 The Monetary Value of Costs Details Minimum Maximum Value

Cancellation Costs

The cost of cancelling the flight of a 120 seat narrow body jet aircraft

- - R 172,033.02

Diversion Costs

The cost of diverting a regional flight R 8,028.28 R 57,344.83 -

The cost of diverting a continental flight R 11,468.97 R 86,017.24 -

Aircraft operating costs

Estimated aircraft operating costs / hour in Rands (excluding fixed annual overheads) for an average aircraft

- - R 23,330.00

Accidents/ incidents

The average cost to an airline of a fatality - - R 26,378,620.74

The average cost to an airline of an injury

Minor injury - R 406,001.38 -

Major injury - R 5,502,809.67 -

Note: all values are expressed in constant 2009 Rands.

The first aspect of direct costs that must be taken into account is the cost of cancellation.

Cancellation costs refer to the cost of abandoning a commercial scheduled flight on the day of

operation. With more flights expected to be scheduled in an air transportation liberalisation

environment, cancellation costs can be expected to rise following implementation of an air transport

liberalisation agreement in SADC. These costs include service recovery costs, interline costs, loss of

1 Standard Inputs for EUROCONTROL Cost Benefit Analyses, 2007 Edition

2 Australian Government, Civil Aviation Safety Authority, Standard Economic Values Guidelines, Version 1.0: 2007

3 2007 AUD $ inflated by 6.25% to equal 2009 AUD $. 2009 AUD $ multiplied by 6.8106 to equal 2009 ZAR Rands.

2007 €’s inflated by 6.09% to equal 2009 €’s. 2009 €’s multiplied by 10.8106 to equal 2009 ZAR Rands.



Muller Associates

future value and decrease in operational savings4. The cost above is specifically for a 120 seat narrow

body aircraft and is estimated at R172,033.02 per cancellation.

The next cost category considered is the average cost per flight diversion, estimated separately for

regional and continental flights. This is the cost of diverting a commercially-scheduled flight. As with

cancellations, with more flights expected to be scheduled in an air transportation liberalisation

environment, the costs of diversions can be expected to rise following implementation of an air

transport liberalisation agreement in SADC. These values are estimated by means of a minimum-

maximum bracket, as they can vary depending on the nature of the diversion. For regional flights, the

range of cost is R8,028.28 to R 57,344.83, while for continental flights; the range is R 11,468.97 to R

86,017.24.

The cost of fuel, and subsequently the increased rate of fuel burn have been excluded from the table for

two reasons. Firstly, data that was available on the cost of jet fuel was extremely generalised and thus

generated no valuable information. Secondly, all data that was available in this area was gathered as

fuel usage according to the tonnes per flight or kilograms per landing/take-off phase. Information on

fuel use per kilometre was not available at this time. For these reasons, the cost of fuel has been

excluded.

Aircraft operating costs refers to the average estimated cost of running an aircraft per hour. This cost

has been estimated per hour at R 23,330.00. This value excludes all fixed annual overheads.

The value for accidents and incidents is an estimation of the cost to an airline in the event of an

accident, whether resulting in injury or death. The possibility exists that implementing an air transport

liberalisation agreement in SADC will result in more fatalities, from more flights operating at each

airport. The cost to an airline in the event of such accidents and incidents must then be taken into

account.

The estimated cost of a fatality is R 26,378,620.74. The cost of injury is estimated with an upper limit

only. The cost of a minor injury is R 406,001.38 and the cost of a major injury is R 5,502,809.67. These

estimates are the cost incurred to the airline in the event of an injury or a fatality.

4 Source: Cost-Benefit Analysis Methodology, Graham Muller Associates, 2010



Muller Associates

2.4.3 Indirect Impacts

2.4.3.1 Security

The indirect costs of increased air travel within the SADC region would include an increase in the

amount of security personnel and infrastructure required to handle increased traffic.

There is currently no public information available for security costs across the SADC region; however a

report on security costs in Australia5, a large common flying area revealed some interesting costs on a

per passenger basis.

Airport security costs have some element of economies of scale and the per passenger charge in the

Australian study was significantly lower for larger airports. Every airport will require security scanners

and personnel to man them, but the throughput for an airport with a constant stream of arrivals versus

one with few daily flights will obviously vary greatly.

Security mandates at airports under an air transportation liberalisation agreement should adhere to

standardised security protocols and procedures and thus costing could be assumed to be similar through

all airports of a similar size.

High fixed costs mean that smaller airports have to charge more for the same security functions as

larger airports. Additionally international passengers have more security procedures to complete and

thus international arrivals cost more. The variation in price for Australia varied from A$16 for a small

international airport passenger arrival to A$4 for large airports handling domestic passengers.

Airports pass onto airlines the costs of operating the facilities based on passenger numbers and freight

volumes and airlines therefore consider security costs when deciding on which airports to utilise.

Additionally there are two elements to the costing of airport security, one is the cost borne by the

airlines and relates directly to their security costs and the other relates to the security of the country as

a whole and thus some of the security costs are carried by national government.

The increased flights will result in a turnover in security costs of A$4,90 per passenger for domestic

flights and A$8 for international flights. That will account for increased spending of R32,93 per

passenger boarding or disembarking for domestic flights and R53,76 for international flights.

5http://www.infrastructure.gov.au/aviation/nap/files_green_paper/Government_of_Northern_Territory-

Access%20Economics_att.pdf

http://www.infrastructure.gov.au/aviation/nap/files_green_paper/Government_of_Northern_Territory-Access%20Economics_att.pdf

http://www.infrastructure.gov.au/aviation/nap/files_green_paper/Government_of_Northern_Territory-Access%20Economics_att.pdf



Muller Associates

2.4.3.2 Transport

Benefits of an air transportation liberalisation policy to the travel and transport industry will extend to

both tourism and freight. The impacts of increased freight would be an increase in the number of air

freight routes and more timely arrival of freight to a variety of destinations. However current patterns of

air traffic suggest that air freight transportation is dependent on an established passenger air travel

service. The impact on the transport industry can be predicted on its own in relation to air arrivals,

however the tourism impact section accounts for these impacts by estimating the change in passenger

arrivals will have on the country of destination as a whole. The tourism impact includes transport

spending and thus in order to avoid double counting we can assume that the impact on the transport

section is included in the tourism section.

Some statistics from a Detroit Metropolitan Wayne County Airport Impact Study conducted in 2006

indicate the transport patterns of traveller arrivals. Tourists accounted for 33% of air arrivals and

residents accounted for 63% of arrivals. For tourists, the average stay was 3.5 days. Half of tourists, or

16% or air arrivals rented a car for the average 3,14 days. The average spend on car rental was the

equivalent of R770 per stay.

2.4.3.3 Pollution

A further consideration as a negative externality which is difficult to quantify is the impact of an air

transportation liberalisation policy on pollution in the SADC region.

The standard inputs for EUROCONTROL Cost benefit Analyses 2007 edition suggests two types of

pollution; noise emanating from aircraft engines and air pollutants from the of burning fuel.

For the fuel portion they suggest the following rate of pollution:

Table 2.4-10 Cost of Fuel

Pollutant per kg of fuel burned6 Cost

7 Burn Rate

8 (737- 800) Cost per hour of

flying time

CO2 3.149 kg R360 per tonne 2,572 tonnes/h R925,92

H20 1.230 kg R101 per tonne 2,572 tonnes/h R259,72

Total: R1185,67

The 737-800 aircraft was used as it is one of the most likely planes to be used on the SADC routes.

6 http://www.eurocontrol.int/eec/gallery/content/public/documents/EEC_notes/2001/EEC_note_2001_08.pdf

7 “Economic incentives to control the global environmental impact of European aviation/Level of the incentive”,

CE, Solutions for environment, economy and technology, Delft, The Netherlands

8 http://www.eurocontrol.int/prc/gallery/content/public/Docs/cost_of_delay.pdf

http://www.eurocontrol.int/eec/gallery/content/public/documents/EEC_notes/2001/EEC_note_2001_08.pdf

http://www.eurocontrol.int/prc/gallery/content/public/Docs/cost_of_delay.pdf



Muller Associates

Furthermore noise pollution levels in the EUROCONTROL study are costed at R693 per take off and an

additional R693 per landing. It must be noted that aircrafts used in Europe are generally newer and

therefore create less pollution. The study has maintained the levels set by the EUROCONTROL study, as

there is no data that is more relevant to the South African aviation situation.

2.4.3.4 Tourism Impact

Implementation of an air transport liberalisation agreement in SADC will result in increased visitor

arrivals and increased overnight visitor stays boosting the tourism industry in participating countries. To

estimate the impact of this effect on the economy of the countries involved in the study, tourism data

was obtained from the World Travel and Tourism website9. The website contains tourism data for

thirteen of the fifteen countries in SADC. The countries omitted are Mozambique and Seychelles, for

these countries the data for Tanzania in Mozambique’s case and Mauritius in Seychelles case was used.

The economic data search tool on the website allows this data to be edited into a suitable format. The

figures for the total impact of tourism on the economy (including indirect and induced spending) in

terms of gross domestic product (GDP) and employment, as well as the direct tourism industry impact

on GDP and employment for the period 1988 to 2010 was acquired. In addition numbers of international

visitors and overnight visitors’ data was obtained in order to translate seat numbers within the model

into an overnight tourism figure.

In order to arrive at a usable “multiplier” for the seat numbers data produced by the routes demand

model, the following process is carried out. First each data set for each country is averaged over the

period (1988 – 2010). As data does not exist for Mozambique and Seychelles, the averages from

Tanzania and Mauritius were used respectively, as these countries are likely to have similar

circumstances in terms of tourism. This average, for example the total average impact of the tourism

industry on a country’s GDP, is divided by the total number of overnight visitors to give the total impact

of the tourism industry on a country’s GDP by one overnight visitor. The percentage of the increase in

seat numbers from the model that can apply to tourism spend is translated into an overnight visitor

figure by taking the average percentage of international visitors between 1988 and 2010 and dividing it

by the average overnight visitors for the period. This gives an estimate of how many of the new

passengers will contribute to the tourism industry.

The methodology is applied to generate a forecast of total impact of tourism on employment, and direct

impact of tourism on GDP and employment. To arrive at the aggregate estimated impact of increased

levels of tourism activity resulting from implementation of an air transport liberalisation agreement in

SADC for ten five year periods totalling fifty years in all. The results of this process are included in

chapter 4.

9 http://www.wttc.org/

http://www.wttc.org/



Muller Associates

The methodology the WTTC employed to arrive at the figures in the council’s database that the study

team used in this process can be found on the WTTC website10.

2.4.4 Airport and Navigational Infrastructure

Adequate airport and navigational infrastructure is essential in creating the platform for airlines to take

advantage of air transport liberalisation regulations. Airport capacity and navigational infrastructure is

mostly below international standards beyond the borders of South Africa in the SADC region. Airport

and navigational infrastructure would need to be upgraded or installed throughout the region to create

capacity for all the additional flights and passengers due to air transport liberalisation within the SADC

region. All the information and data regarding infrastructure requirements and costs have been

provided by Air Traffic & Navigational Services (ATNS) and the Airports Company South Africa (ACSA).

The navigational infrastructure costs have been broken into two parts: the first being the navigational

equipment required per route; and the second being the navigational equipment required per airport.

The airport infrastructure costs are purely an airport cost to create the capacity to handle increased

number of passengers.

2.4.4.1 Navigational Infrastructure per Route

Navigational equipment is not only required at the various airports but also at various intervals along

each route. The navigational equipment required depends on the nautical miles (NM) separation

between aircrafts and the flight level being flown by aircrafts. For the purpose of this study we’ve

assumed that all navigational equipment needs to be standardised across the SADC region at South

African specifications. This would entail navigational equipment being installed with the technological

stipulations to allow aircrafts to travel 5 NM apart from each other. The navigational equipment

requirements has been listed in Table 2.4-11 below for 5 NM distance between aircrafts, it can be seen

the unit cost has been provided for each piece of equipments, as well as their theoretical coverage in

kilometres and the number of these units required to accommodate a distance of 5 NM per aircraft.

With this information displayed in Table 2.4-11 it is possible to calculate the cost of navigational

equipment per kilometre for each route within the SADC region. This information has been calculated

for both the 145 and 195 flight levels (the upper and lower range of flight levels.) Although the cost of

navigational infrastructure is a cost that is incurred every 15 years, for the purpose of our study this cost

has been broken down into a weekly cost and can be compared with the other costs and benefits.

10http://www.wttc.org/viewfile.php?file=/var/www/wttc/public_html/bin/pdf/original_pdf_file/economic_impact_res

earch_metho.pdf

http://www.wttc.org/viewfile.php?file=/var/www/wttc/public_html/bin/pdf/original_pdf_file/economic_impact_research_metho.pdf




Muller Associates

Table 2.4-11 Navigational Equipment Requirements per Route at 5 NM11 Navigational Equipment

Unit Costs Theoretical Coverage (KM) 5 NM Navigational Requirement

FL 145 FL 195 FL 145 FL 195

DVOR/DME 6,000,000 180 200 1 1

SSR 25,000,000 230 315 2 2

VHF 150,000 230 315 1 1

2.4.4.2 Airport Navigational Equipment Costs

Airport navigational costs have been provided by ATNS. The airport navigational infrastructure that

ATNS has recommended is aligned with the navigational systems and standards currently adopted in

South African airports. The navigational airport infrastructure has a 15 year life span, after which the

navigational equipment needs to be replaced. Table 2.4-12 lists the navigational equipment required

depending on the type of airport.

Table 2.4-12 Airport Navigational Equipment Required per Airport Type Facilities Unit Cost Type 1 Type 2 Type 3

DVOR/DME 6,000,000 1 1 1

VDF (Class C) 350,000 1 1

SSR 25,000,000 1 1

PSR 35,000,000 1

VHF 150,000 1 2 3

TCU 10,000,000 1

The number of flights determines the amount of navigational equipment required. For the purposes of

this report the airports have been separated into three categories based on the number of passengers

passing through the terminals annually. The simplified definitions of the three types of airports are: Type

1 airports have low number of annual passengers; type 2 airports have medium number of annual

passengers; and type 3 airports are the major airports in the SADC region. The various classifications of

airports have been listed in Table 2.4-13 to Table 2.4 -16.

This information helps determine the cost navigational equipment cost per airport. As this is a sunk

capital cost every 15 years, the profitability per airport will be determined over the 50 year period to

assess the overall impact of the infrastructure installed per airport.

11 The rand value’s are based on a Euro Rand exchange rate of R11=1 Euro at July 2010prices



Muller Associates

Table 2.4-13 Type 1 Airports in the SADC Region Type 1

Location Country Location Country Location Country

Dundo Angola Gemena D.R. Congo Mariental Namibia

Huambo Angola Goma D.R. Congo Ondangwa Namibia

Kuito Angola Isiro-Matari D.R. Congo Rundu Namibia

Lubango Angola Kananga D.R. Congo Mafikeng South Africa

Luena Angola Kindu D.R. Congo Polokwane South Africa

Malanje Angola Mbandaka D.R. Congo Pilanesberg South Africa

Menongue Angola Mbuji-Mayi D.R. Congo Umtata South Africa

Namibe Angola Nosy Be Madagascar Welkom South Africa

Ondjiva Angola Toliara Madagascar Mtwara Tanzania

Saurimo Angola Chimoio Mozambique Mwanza Tanzania

Soyo Angola Cuamba Mozambique Kitwe Zambia

Uíge Angola Mueda Mozambique Mfuwe Zambia

Kasane Botswana Tete Mozambique Ndola Zambia

Bukavu D.R. Congo Karabib Namibia Hwange Zimbabwe

Buta-Zega D.R. Congo Katima Mulilo Namibia

Gbadolite D.R. Congo Keetmanshoop Namibia



Cabinda Angola Beira Mozambique Nelspruit South Africa

Catumbela Angola Lichinga Mozambique Port Elizabeth South Africa

Francistown Botswana Moçimboa da Praia Mozambique Upington South Africa

Maun Botswana Nampula Mozambique Manzini Swaziland

Kisangani D.R. Congo Grootfontein Namibia Dodoma Tanzania

Lubumbashi D.R. Congo Bisho South Africa Kilimanjaro Tanzania

Maseru Lesotho Bloemfontein South Africa Livingstone Zambia

Mahajanga Madagascar George South Africa Bulawayo Zimbabwe

Toamasina Madagascar Johannesburg (Lanseria) South Africa Victoria Falls Zimbabwe

Blantyre Malawi Kimberley South Africa



Muller Associates



Luanda Angola Maputo Mozambique Dar-Es-Salaam Tanzania

Gaborone Botswana Windhoek Namibia Zanzibar Tanzania

Kinshasa D.R. Congo Seychelles Seychelles Lusaka Zambia

Antanànarìvo Madagascar Cape Town South Africa Harare Zimbabwe

Lilongwe Malawi Durban South Africa

Port Louis Mauritius Johannesburg South Africa

2.4.4.3 Airport capacity constraints and expansions

Airports are constrained by peak hour capacity limits, as there are a limited number of bays for

aeroplanes and a limited amount of trained staff to deal with passengers. Therefore, it is important to

assess the additional capacity required based on the demand predicted by this study and determine the

cost of airport infrastructure. This study has utilised the ACSA estimate that determines it would roughly

cost R 600 million to create an additional airport capacity for one million passengers.

Verifying the capacities for all the airports in the SADC region is extremely difficult, as only the ACSA

airports capacities are known. Therefore, capacities have been assumed based on the capacity

information provided by ACSA. Table 2-20 SADC airport capacities display the assumed capacities for the

airports in the SADC region. Major airports outside of South Africa have been given a 14 million annual

passenger capacity (in line with Cape Town International), medium sized airports have been given an

annual capacity of 4.5 million passengers (in line with King Shaka International), and small airports have

been given an annual capacity of 720,000 passengers (an average of all the smaller ACSA airports.)

The investment in airport infrastructure has been linked with the forecasted number of passengers

utilising the airports annually over the 50 year period. As passenger numbers exceed capacities

displayed in Table 2.4-16 the ratio of R 600 million for every one million extra passengers is applied. This

would yield an increased airport capacity aligned with the passenger forecast growth over the 50 years.

The ACSA airports where annual passenger capacities are known are highlighted in red in Table 2.4-16.



Muller Associates

Table 2.4-16 SADC Airport Capacities Location Annual Capacity Location Annual Capacity Location Annual Capacity

Cabinda 720,000 Mbuji-Mayi 720,000 Durban 4,500,000

Catumbela 4,500,000 Maseru 4,500,000 George 900,000

Dundo 720,000 Antanànarìvo 14,000,000 Lanseria 720,000

Huambo 720,000 Mahajanga 4,500,000 Johannesburg 28,000,000

Kuito 720,000 Nosy Be 720,000 Kimberley 200,000

Luanda 14,000,000 Toamasina 4,500,000 Mafikeng 720,000

Lubango 720,000 Toliara 720,000 Nelspruit 720,000

Luena 720,000 Blantyre 4,500,000 Polokwane 720,000

Malanje 720,000 Lilongwe 14,000,000 Port Elizabeth 2,000,000

Menongue 720,000 Port Louis 14,000,000 Pilanesberg 40,000

Namibe 720,000 Beira 4,500,000 Umtata 720,000

Ondjiva 720,000 Chimoio 720,000 Upington 100,000

Saurimo 720,000 Cuamba 720,000 Welkom 720,000

Soyo 720,000 Lichinga 720,000 Manzini 4,500,000

Uíge 720,000 Maputo 14,000,000 Dar-Es-Salaam 14,000,000

Francistown 720,000 Moçimboa da Praia 720,000 Dodoma 720,000

Gaborone 14,000,000 Mueda 720,000 Kilimanjaro 4,500,000

Kasane 720,000 Nampula 4,500,000 Mtwara 720,000

Maun 4,500,000 Tete 720,000 Mwanza 720,000

Bukavu 720,000 Grootfontein 4,500,000 Zanzibar 720,000

Buta-Zega 720,000 Karabib 720,000 Kitwe 720,000

Gbadolite 720,000 Katima Mulilo 720,000 Livingstone 4,500,000

Gemena 720,000 Keetmanshoop 720,000 Lusaka 14,000,000

Goma 720,000 Mariental 720,000 Mfuwe 720,000

Isiro-Matari 720,000 Ondangwa 720,000 Ndola 720,000

Kananga 720,000 Rundu 720,000 Bulawayo 720,000

Kindu 720,000 Windhoek 14,000,000 Harare 14,000,000

Kinshasa 14,000,000 Seychelles 14,000,000 Hwange 720,000

Kisangani 4,500,000 Bisho 1,200,000 Victoria Falls 4,500,000

Lubumbashi 4,500,000 Bloemfontein 600,000

Mbandaka 720,000 Cape Town 14,000,000



Muller Associates

2.5 Cost-Benefit Analysis Results

2.5.1 Direct Impacts

2.5.2 Benefit to airlines

As explained in the methodology the number of flights added, at each five year interval, is determined

by whether the demand estimate per route is greater than the progressive 0.05 decrease in the demand

estimate hurdle rate assumed by the model for every five year period into the future. The model

therefore predicts that flights yielding a higher demand will be taken up by airlines in the early stages of

implementation of an air transport liberalisation agreement in SADC as they offer the prospect of lowest

commercial risk and the highest return in terms of profitability.

During the 35 to 50 year period post full implementation of an air transport liberalisation agreement in

SADC, flights still being added by airlines will effectively be serving progressively higher commercial risk

and lower profit routes. The reason for this is that all the major routes will be fully operational and there

will be reduced market share for additional airlines or additional flights. Airlines will therefore seek to

grow their market share by offering flights on these commercially riskier and less profitable routes. Of

course, in reality, air fares are likely to be higher on these routes to reflect the higher commercial risk,

because fewer airlines will be attracted to the routes with lower commercial potential.

Table 2.5-1, below, shows the forecasted turnover, seat numbers and flights (per week) over a 50 year

period starting from the day an air transport liberalisation agreement in SADC is broadly implemented in

SADC. This gross turnover included existing turnover on routes flown prior to implementation of an air

transport liberalisation agreement in SADC. Unfortunately, for reasons of confidentiality, the airlines

responding to the study questionnaire were not willing to disclose existing turnover figures. In

consequence, the study only forecasted the gross turnover projections post implementation of an air

transport liberalisation agreement in SADC. It can be observed that over a 50 year period the forecasted

turnover per week for low cost carriers would total R 21.8 billion (2009 prices).

Table 2.5-1 Forecasted Turnover, Seat Numbers & Number of flights (per week)

Years Turnover Seat Numbers Number of flights

5 R 395,592,569.17 1,157,834 13,024

10 R 615,030,014.60 2,155,705 22,628

15 R 631,437,961.30 2,253,469 23,680

20 R 1,055,829,325.19 3,634,050 39,598

25 R 3,194,221,298.65 7,059,728 82,222

30 R 8,886,816,358.07 15,622,239 197,596

35 R 15,354,301,000.26 24,847,174 333,625

40 R 20,306,047,606.09 32,446,460 456,498

45 R 21,592,032,312.26 34,280,245 489,124

50 R 21,804,364,460.93 34,697,974 498,464



Muller Associates

On average 34.6 million passengers would travel within SADC weekly and there would be almost half a

million flight operating across all SADC routes per week. Turnover grows rapidly, especially from the

15th year and indicates the significant benefit to airlines of implementing an air transport liberalisation

agreement in SADC.

Figure 2.5-1, below, displays the growth in turnover for low cost carriers over the 50 year period

following the implementation of an air transport liberalisation agreement in SADC. It is expected that

the graph would encompass an S-bending curve because the initial take up after liberalisation would be

slow due to airlines adjusting to the new regulatory environment. It can also be expected that the

lower commercial risk and higher return routes will be added to airlines’ routes flown in the early stages

of liberalisation, before the higher commercial risk and lower return routes are added. This is reflected

in what the model predicts – as shown in Figure 2.5-1. This graph shows that between implementation

and 35 years turnover would increase at an increasing rate and then from the 35th to the 50th year

turnover would increase at a decreasing rate.

Figure 2.5-1 Forecasted Turnover

The marginal turnover graph can be seen in Figure 2.5-2. This graph shows the amount of additional

turnover added at each 5 year interval. It can be seen that at 35 years the amount of turnover being

added begins to decrease. This reflects that during the first 35 years route and flight additions would

focus on the commercially more feasible and low risk routes. There would be heavy competition

amongst airlines operating in the SADC region. The routes added beyond 35 years of implementing an

air transport liberalisation agreement in SADC would be higher risk and lower demand and would only

be taken up by airlines once the major routes are completely serviced, but airlines seek to further

extend their aviation market share.

R -

R 5,000,000,000.00

R 10,000,000,000.00

R 15,000,000,000.00

R 20,000,000,000.00

R 25,000,000,000.00

5 10 15 20 25 30 35 40 45 50

Years



Muller Associates

The marginal cost curves and all other marginal benefit curves, with the exception of the marginal

benefit to passengers graph display a similar shape, peaking at 35 years. The marginal benefit to

passengers did not peak at the 35 year. This graph is displayed and discussed at a later stage in this

section.

The rest of these graphs have not been included in this report but can be viewed in the accompanying

Microsoft Excel economic forecast model.

Figure 2.5-2 Marginal turnover

Figure 2.5-3, overleaf, indicates the growth in seat numbers purchased over a 50 year period after

implementing an air transport liberalisation agreement in SADC based on the assumption that 75% of

seats on offer are taken up. Similarly to Figure 2.5-1, which indicates growth in turnover over the same

50 year time frame, an s-bend curve is observed. As seat numbers are closely correlated with turnover

the s-bend similar to that of turnover is expected.

R -

R 1,000,000,000.00

R 2,000,000,000.00

R 3,000,000,000.00

R 4,000,000,000.00

R 5,000,000,000.00

R 6,000,000,000.00

R 7,000,000,000.00

5 10 15 20 25 30 35 40 45 50



Muller Associates

Figure 2.5-3 Growth in Seat Numbers

It can also be expected that growth in the number of flights per week over the 50 year period following

the implementation of an air transport liberalisation agreement in SADC will increase in a similar way to

that of turnover and seat numbers, since the number of flights is directly related to the number of seats

demanded and sold. The s-bending curve for the number of flights per week can be seen in Figure 2.5-4,

below. Once again the same reasoning is applicable, where flights are added to the low commercial risk

and high return routes during the initial 35 year period and thereafter, with limited opportunity for

additional flights on these routes, flights being added to the higher commercial risk and lower return

routes are embarked on in the 35 to 50 year period.

Figure 2.5-4 Growth in Number of Flights per Week

-

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

30,000,000

35,000,000

40,000,000

5 10 15 20 25 30 35 40 45 50

Year

-

100,000

200,000

300,000

400,000

500,000

600,000

5 10 15 20 25 30 35 40 45 50

Year



Muller Associates

2.5.3 Benefits to passengers

As discussed in the methodology there are primarily two benefits that would accrue to passengers

following a liberalisation of aviation regulations. Firstly the benefit of decreased ticket prices and

secondly time savings from flights bypassing hub airports and flying directly from the points of origin to

destinations that passengers actually want to fly to. It has already been noted that it proved impossible

to account for the benefit from the decrease in ticket prices due to the limited commercial information

received from airlines currently operating in SADC. However the study team has calculated the time

saving benefit that would accrue to passengers due to time savings of flying directly to a destination,

bypassing hub airports and flying directly.

2.5.3.1 Time savings

The assumptions that are spelled out in the methodology section of this report have informed the

results that follow. It has been estimated that there will be a 7.9 million kilometre (per week) decrease

in the distance flown by passengers to reach their final destinations. If the average cruising speed of an

aircraft is 900km/h then approximately 8805 hours would be saved in air travel for all routes within

SADC. Table 2.5-2 below shows how this time saving was estimated in 2009 Rands if a person values an

hour saved at the entirely notional value of R200 per hour. Table 2.5-2 indicates that time saving by

passengers over a 50 year period would total R 13.9 billion. Regardless of the notional value per hour

chosen for passenger time this indicates that the value of this aggregate benefit will be substantial.

Table 2.5-2 Passenger Time Saving Benefit Years Value of Passenger Time Saved at a

Value of R200/hour

5 R 80,704,142.39

10 R 148,353,788.17

15 R 152,429,875.57

20 R 265,108,382.22

25 R 766,732,401.87

30 R 2,961,410,846.08

35 R 7,207,220,265.68

40 R 12,429,642,407.48

45 R 13,703,434,148.72

50 R 13,957,174,567.04

Once again, as can be seen in Figure 2.5-5 overleaf, an S-bend shaped curve describes the relationship

between the values of passengers’ time saved over a 50 year period. Again this is expected as initially

routes that exhibit generally low commercial risk and high returns would be adopted by low cost

carriers. As the results from the model indicate that routes operating to or from hub airports generally

exhibit lower commercial risk and higher returns due to higher population concentrations and higher

levels of business activities, this means that relatively limited time savings to passengers would be



Muller Associates

generated in the early years post implementation of an air transport liberalisation agreement in SADC. A

number of these routes are currently being operated by national flag carriers and therefore a low cost

carrier operating on these routes would be able to fairly easily win business, at relatively low

commercial risk, on these routes, in a de-regulated operating environment. As more commercially

challenging routes that bypass the hub airports, are added in later years, time savings to passengers

would begin to increase, exponentially at first and then tapering off as the overall SADC aviation market

approaches saturation.

Figure 2.5-5 Passengers Time Saving Benefit

Figure 2.5-6 shows the marginal benefits resulting from passengers’ time saving in each five year period

post implementation of an air transport liberalisation agreement in SADC. As mentioned earlier in the

report, the 5 year marginal benefit from passengers’ time peaks at year 40 post implementation of an

air transport liberalisation agreement in SADC, somewhat later than for other benefits predicted by the

cost-benefit model, the quantum of which peak in year 35 post implementation of an air transport

liberalisation agreement in SADC. This is again a reflection that the largest time benefits to passengers

are experienced as the highest commercial risk and lowest return routes (which tend to be those that

bypass hub airports) are added to the route networks of low cost carriers.

R -

R 2,000,000,000.00

R 4,000,000,000.00

R 6,000,000,000.00

R 8,000,000,000.00

R 10,000,000,000.00

R 12,000,000,000.00

R 14,000,000,000.00

R 16,000,000,000.00

5 10 15 20 25 30 35 40 45 50

Years



Muller Associates

Figure 2.5-6 Marginal benefits from passengers’ time saving

2.5.3.2 Ticket pricing and distances flown per week

Table 2.5-3 below displays the average ticket price per flight, the distance flown per week and the

average distance flown per flight. Each of the columns in Table 2.5-3 has been graphed and this is

displayed in Figures 2.5-7, 2.5-8, and 2.5-9.

Table 2.5-3 Additional flight information Years Average Ticket Price per flight

(2009 Rands) Distance flown per week (km)

Average distance flown per flight (km)

5 R 341.67 13,727,109.91 1,053.99

10 R 285.30 20,009,690.53 884.31

15 R 280.21 20,536,909.37 867.27

20 R 290.54 35,158,912.46 887.89

25 R 452.46 114,571,046.97 1,393.43

30 R 568.86 343,103,208.33 1,736.38

35 R 617.95 627,218,254.45 1,880.01

40 R 625.83 865,880,913.94 1,896.79

45 R 629.87 934,034,723.71 1,909.61

50 R 628.40 948,018,098.80 1,901.88

Figure 2.5-7 shows the average ticket price per flight in constant 2009 Rands. Initially the average ticket

price decreases to R280 and then increases before stabilising at roughly R625. One of the key

R -

R 1,000,000,000.00

R 2,000,000,000.00

R 3,000,000,000.00

R 4,000,000,000.00

R 5,000,000,000.00

R 6,000,000,000.00

5 10 15 20 25 30 35 40 45 50

Year



Muller Associates

determinants of the price of an air ticket is the distance flown. The model predicts that domestic routes

that are by their nature relatively shorter are targeted first as these are commercially less risky.

Figure 2.5-7 Average ticket price per flight

This is confirmed in Figure 2.5-9, where the average distance flown per flight correlates. As more

routes, including international routes that involve longer distances and flying times are added there will

be a associated increase in the average price of air tickets sold in the region. The average air ticket prices

stabilise at around 35 years post implementation of an air transport liberalisation agreement in SADC, as

routes with origins and destinations further apart are added by the low cost airlines. Once these are

added the effects of distance on the average price of air tickets is reflected it is once again moderated.

The total distance flown per week over the 50 year period is reflected in Figure 2.5-8 overleaf.

R -

R 100.00

R 200.00

R 300.00

R 400.00

R 500.00

R 600.00

R 700.00

5 10 15 20 25 30 35 40 45 50

Year



Muller Associates

Figure 2.5-8 Total distance flown per week (km)

Figure 2.5-9 shows the predicted average distance flown per flight throughout SADC over the 50 year

period post implementation of an air transport liberalisation agreement in SADC. Figure 2.5-9 confirms

that initially shorter routes are adopted by low cost airlines; this directly lowers the price of air tickets

and allows airlines to attract new customers. As longer routes are added, it can be seen that the average

distance flown increases and this directly impacts the average price of tickets throughout the region.

The average price of tickets graph rises steeply at first from year 20 to year 30 post implementation of

an air transport liberalisation agreement in SADC and then rises more moderately from year 35 post

implementation.

Figure 2.5-9 Average distance flown per flight (km)

-

100,000,000.00

200,000,000.00

300,000,000.00

400,000,000.00

500,000,000.00

600,000,000.00

700,000,000.00

800,000,000.00

900,000,000.00

1,000,000,000.00

5 10 15 20 25 30 35 40 45 50

Year

-

500.00

1,000.00

1,500.00

2,000.00

2,500.00

5 10 15 20 25 30 35 40 45 50

Year



Muller Associates

Tables 2.5-4 and 2.5-5 below show the direct costs to airlines and the projection of these costs over a 50

year period. In Table 2.5-4, the five direct costs to an airline are listed in the first column. In the second

column, an estimate of the frequency, in terms of how often the airline would incur this cost, is

provided. This is estimated by means of a percentage of the flights within the region over the 50 year

period and then the costs have been calculated to reflect a per week cost to an airlines. For example, if

0.1% of flights in a week are diverted, that cost is estimated by the study team at R32,686.56 per week.

The third column of Table 2.5-4 shows the estimated cost per week in 2009 Rands.

Table 2.5-4 Assumptions, Weights, Proportions and Figures Used COST TO AIRLINES Frequency Cost to an Airline per week (2009 Rands)

Cost of flight cancellation 1.0% R 172,033.02

Cost of flight diversion 0.1% R 32,686.56

Cost of fatality 0.0000321% R 26,378,620.74

Cost of minor injury 0.0000321% R 406,001.38

Cost of major injury 0.0000321% R 5,502,809.67

Table 2.5-5 below shows all the direct costs to airlines over a 50 year period in 2009 Rands. To

determine these costs, the frequency of each cost has been multiplied by the projected number of

flights projected under an air transportation liberalisation agreement, and then multiplied by the

estimated cost in Rands, over the next 50 years. For example, if it is projected that in the next 5 years,

there will be 9649 flights and 1% if those flights will be cancelled, then there will be 96.49 cancelled

flights. If the cost is estimated at R172,033.02 per cancellation, then the cost to airlines of cancellations

in the first 5 years is R16,598,813.09. In Table 2.5-4 above, the most prominent of all costs is the cost of

cancellation. This is not surprising since it is also the cost with the highest predicted frequency of

occurrence. The cost of diversion is the second highest cost, followed by the cost of fatality, major injury

and then minor injury. A graphed comparison of these costs in relation to each other is shown in the

figure overleaf.



Muller Associates

Table 2.5-5 Results Over 50 Year Period

Years Cost of flight cancellations

Cost of flight diversions




5 R 16,598,813.09 R 315,380.21 R 81,714.64 R 1,257.69 R 17,046.38

10 R 30,904,371.61 R 315,380.21 R 95,086.12 R 1,447.96 R 17,703.70

15 R 32,305,924.57 R 768,932.95 R 199,229.61 R 3,066.40 R 41,561.03

20 R 52,098,054.07 R 1,204,203.34 R 312,007.65 R 4,802.20 R 65,087.51

25 R 101,208,861.28 R 2,207,196.63 R 571,882.02 R 8,802.01 R 119,299.56

30 R 223,961,749.86 R 4,561,179.38 R 1,181,796.15 R 18,189.38 R 246,532.95

35 R 356,211,204.63 R 7,081,209.60 R 1,834,732.98 R 28,238.93 R 382,741.25

40 R 465,155,209.94 R 9,153,406.58 R 2,371,636.76 R 36,502.58 R 494,744.05

45 R 491,444,508.29 R 9,652,907.63 R 2,501,056.88 R 38,494.53 R 521,742.21

50 R 497,433,106.58 R 9,766,691.99 R 2,530,538.28 R 38,948.28 R 527,892.29

Figure 2.5-10 Total Costs to Airlines

Over the 50 year period, the cost of cancelled flights would be the most significant cost to airlines under

an air transportation liberalisation agreement (Figure 2.5-10).

The trend in Table 2.5-5 above follows a distinctive S bend in the curve, in that marginal cost to airlines

will increase over time, reach a peak and then decrease in later years. The graphs of each cost indicate

that the steepest point on all graphs (the point of inflection) is between the 30 year and 35 year mark.

R -

R 100,000,000.00

R 200,000,000.00

R 300,000,000.00

R 400,000,000.00

R 500,000,000.00

R 600,000,000.00

5 10 15 20 25 30 35 40 45 50

Years




Cost of flight diversions

Cost of flight cancellation



Muller Associates

Even before the costs to airlines are increasing at an increasing rate, in that the difference in cost

between each consecutive year gets bigger. After the inflection point in the graph, the difference in the

cost between consecutive years gets smaller. The reason for the S bend shape is that as the air

transportation liberalisation agreement matures in the SADC region, more flights would be added each

year. For the first 30-35 years of an air transportation liberalisation operation, more flights would be

added in each 5-year period. The flights added in this period will be the most attractive to airlines, and

which will therefore also tend to be the most profitable. In the years after the inflection point (at 30-35

years and beyond) the number of flights added per five year period will tend to be fewer and fewer each

year, as these are the routes that are less popular with airlines, being the less profitable, generally

longer and lower trafficked routes. Because more flights are added in the earlier period, the direct costs

to airlines will also be higher in this period (because the cost to airlines is correlated with the number of

flights undertaken). In the later period, fewer flights added per 5 years will also translate into lower

additional direct cost to airlines in each 5 year period.

Figure 2.5-11 Cost of Flight Cancellation

The cost of flight cancellations is illustrated in Figure 2.5-11 above. The steepest point on the curve is

between 30 and 35 years. This reflects a cost of flight cancellation between R 223.9 million and R 356.2

million respectively.

R -

R 100,000,000.00

R 200,000,000.00

R 300,000,000.00

R 400,000,000.00

R 500,000,000.00

R 600,000,000.00

5 10 15 20 25 30 35 40 45 50

Year



Muller Associates

Figure 2.5-12 Cost of Flight Diversions

The cost of flight diversions is shown above in Figure 2.5-12. As above, the steepest point on the curve is

between 30 and 35 years. This reflects a cost of flight diversions between R 4.5 million and R 7 million

respectively.

Figure 2.5-13 Cost of Accident Resulting in Fatality

The cost of accident resulting in fatality has been illustrated in Figure 2.5-13 above. The S-bend can be

seen clearly in this figure, reaching its steepest point at 30-35 years. This reflects a cost of accident

resulting in fatality between R 1.1 million and R 1.8 million respectively.

R -

R 2,000,000.00

R 4,000,000.00

R 6,000,000.00

R 8,000,000.00

R 10,000,000.00

R 12,000,000.00

5 10 15 20 25 30 35 40 45 50

Years

R -

R 500,000.00

R 1,000,000.00

R 1,500,000.00

R 2,000,000.00

R 2,500,000.00

R 3,000,000.00

5 10 15 20 25 30 35 40 45 50

Years



Muller Associates

Figure 2.5-14 Cost of Accident Resulting in Minor Injury

Figure 2.5-14 shows the cost of accidents resulting in minor injury. The steepest point on the line is

between 30 and 35 years after implementation of an air transport liberalisation agreement in SADC, as

in the previous figure. This reflects a cost of accident resulting in minor injury between R 18,189 and R

28,238 respectively.

Figure 2.5-15 Cost of Accident Resulting in Major Injury

Figure 2.5-15 shows the cost of accidents resulting in major injury. The curve follows the same shape as

previous figures – an S-bend with the steepest point between 30 and 35 years after implementation of

R -

R 5,000.00

R 10,000.00

R 15,000.00

R 20,000.00

R 25,000.00

R 30,000.00

R 35,000.00

R 40,000.00

R 45,000.00

5 10 15 20 25 30 35 40 45 50

Years

R -

R 100,000.00

R 200,000.00

R 300,000.00

R 400,000.00

R 500,000.00

R 600,000.00

5 10 15 20 25 30 35 40 45 50Years



Muller Associates

YD, as in the previous figures. This reflects a cost of accident resulting in major injury between R 0.25

million and R 0.38 million respectively.

Figure 2.5-16 Potential Turnover and Costs to Airlines

The final figure above, Figure 2.5-16, shows these costs in relation to airline turnover. Although the

costs look quite large when graphed alone, relative to turnover, the identified costs are minimal.

However, expect the graph to change after aircraft operational costs are incorporated (this information

was not provided by the airlines.)

2.5.4 Indirect Impacts

2.5.4.1 Tourism Impact Over 50 Years

The SADC airport routes demand forecast model is able to give the impact on tourism, measured as

impact on GDP and impact on Employment, of various routes opening up for different countries at

different times. The below Table 2.5-6 is an aggregate summary of the impact an air transport

liberalisation agreement in SADC would have on the economies of the countries within SADC, from five

years after implementation to fifty years after implementation.

R -

R 5,000,000,000.00

R 10,000,000,000.00

R 15,000,000,000.00

R 20,000,000,000.00

R 25,000,000,000.00

5 10 15 20 25 30 35 40 45 50

Years

Potential Turnover

Total Costs To Airlines



Muller Associates

Table 2.5-6 Tourism Impact Over 50 Years Tourism impact

Years Total Impact On GDP (2009 Rands)


Total Impact on Employment

Direct Impact on Employment

5 38 153 667 234 7 552 340 410 18 834 396 2 946 352

10 52 495 280 062 13 205 292 139 20 148 872 3 552 166

15 56 242 018 920 13 673 144 858 22 474 400 3 803 567

20 168 404 489 659 28 251 360 599 96 497 793 11 969 962

25 283 584 702 100 50 738 372 512 153 113 422 20 618 568

30 592 312 694 411 105 672 816 915 292 815 107 42 028 595

35 965 917 528 251 165 457 639 030 479 527 314 70 831 341

40 1 325 217 246 927 217 448 285 885 641 150 459 96 702 448

45 1 398 653 761 279 228 121 055 753 662 282 465 101 085 855

50 1 410 118 459 326 229 837 249 447 667 355 671 101 896 069

The data illustrates that there are four distinct growth periods over the next fifty years in terms of

tourism which will impact GDPs of countries within SADC. For the first fifteen years growth is lower as

few routes would have been opened up or had little time to establish new tourist industries, but as

more routes are enabled growth would pick up between years fifteen and twenty-five. Beyond year

twenty-five these routes would have established new tourism areas and industries, and even more

routes would be opening up leading to the steep growth seen on the following figures. At around year

forty most of the routes that would have been established and given the restraints built into the model

it can be seen that growth slows which could reflect a maturing tourism situation within SADC. Overleaf

is the graphical representation of the total and direct impact on GDP and employment over the fifty

years. Each of the four stages impact data is represented in the following sub-sections.



Muller Associates

Figure 2.5-17 Total and Direct Impact on GDP (2009 Rands)

Figure 2.5-18 Total and Direct Impact on Employment

R -

R 200 000 000 000.00

R 400 000 000 000.00

R 600 000 000 000.00

R 800 000 000 000.00

R 1 000 000 000 000.00

R 1 200 000 000 000.00

R 1 400 000 000 000.00

R 1 600 000 000 000.00

5 10 15 20 25 30 35 40 45 50

Years

Total & Direct Impact on GDP (2009 Rands)

Total Impact On GDP (2009 Rands)


-

100 000 000

200 000 000

300 000 000

400 000 000

500 000 000

600 000 000

700 000 000

800 000 000

5 10 15 20 25 30 35 40 45 50

Years

Total & Direct Impact of Employment

Total Impact on Employment

Direct Impact on Employment



Muller Associates

2.5.4.1.1 Year 5

Table 2.5-7 below, which has been derived from the routed forecast model, shows the impact that

tourism will have on SADC countries five years after an air transport liberalisation agreement in SADC

has been implemented.

Table 2.5-7 Tourism Impact in Year 5 Countries Routes Total Impact On

GDP (2009 Rands) Direct Impact On GDP (2009 Rands)

Total Impact of Employment

Direct Impact of Employment

Angola 15 22 542 071 514 2 732 989 045 15 303 371 1 618 571

Botswana 7 460 066 146 145 079 268 44 953 19 510

Democratic Republic of Congo 7 4 468 444 338 429 890 342 540 779 67 928

Lesotho 1 87 726 912 31 076 572 10 485 4 247

Madagascar 5 1 208 731 887 492 479 095 731 726 298 908

Malawi 3 204 833 615 81 897 543 76 255 31 919

Mauritius 3 491 704 994 188 788 352 59 760 25 475

Mozambique 8 1 329 509 622 541 169 345 771 621 319 812

Namibia 0 0 0 0 0

Seychelles 2 347 137 813 142 322 615 39 656 18 154

South Africa 33 5 855 278 401 2 302 594 211 633 534 285 533

Swaziland 0 0 0 0 0

Tanzania 6 945 480 236 385 258 461 571 007 236 433

Zambia 3 92 097 194 32 674 791 31 413 11 540

Zimbabwe 4 120 584 561 46 120 769 19 835 8 322

Total 97 38 153 667 234 7 552 340 410 18 834 396 2 946 352

There would be ninety seven routes opened, thirty three of which would be in South Africa and fifteen

from Angola. The results are distorted due to Angola’s figures, which are much higher than any of the

other countries leading to a shift in the overall impact on tourism. Angola is an oil-producing country

which has benefitted massively from the oil production and increased business being attracted because

of this. The model is suggesting it will be one of the major beneficiaries of air transportation

liberalisation. It also has the effect of skewing forecast data since it is unlikely to have the same level of

economic performance as it has had in recent years; however it is this data which has to be used in

forecasting.

2.5.4.1.2 Year 15

Ten years from an air transport liberalisation agreement in SADC it would be seen that 81 routes would

be expected to have opened up, increasing the impact of tourism on total GDP by R18 billion and on jobs

by 4 million, in SADC. The major differences are between the year five scenario and the year fifteen

scenario, the 73 new routes available to and from South Africa, which would have a major impact on

South Africa’s GDP and employment increasing total impact on GDP almost 4 fold to R20 billion and total

impact of employment almost 3 fold to 1.9 million.



Muller Associates





Angola 17 25 828 044 557 3 124 166 392 17 549 572 1 855 239

Botswana 8 509 009 242 158 356 285 49 901 21 590

Democratic Republic of Congo 7 4 468 444 338 429 890 342 540 779 67 928

Lesotho 1 87 726 912 31 076 572 10 485 4 247

Madagascar 5 1 208 731 887 492 479 095 731 726 298 908

Malawi 3 204 833 615 81 897 543 76 255 31 919

Mauritius 3 491 704 994 188 788 352 59 760 25 475

Mozambique 8 1 329 509 622 541 169 345 771 621 319 812

Namibia 5 411 822 719 63 398 355 74 380 12 653

Seychelles 2 347 137 813 142 322 615 39 656 18 154

South Africa 106 20 196 891 229 7 955 545 940 1 948 009 891 346

Swaziland 0 0 0 0 0

Tanzania 6 945 480 236 385 258 461 571 007 236 433

Zambia 3 92 097 194 32 674 791 31 413 11 540

Zimbabwe 4 120 584 561 46 120 769 19 835 8 322

Total 178 56 242 018 920 13 673 144 858 22 474 400 3 803 567

2.5.4.1.3 Year 25

Twenty five years after the implementation of air transportation liberalisation, there would be a total of

623 routes available to airlines (445 more than the previous scenario). The impact on GDP would have

increased by over five times its level at year fifteen, and employment by an even larger margin.





Angola 176 206 275 515 037 26 296 691 304 137 284 187 14 687 694

Botswana 67 6 197 312 531 2 229 768 612 650 991 285 051

Democratic Republic of Congo 25 17 354 854 704 1 697 127 175 2 092 519 264 345

Lesotho 2 177 302 632 62 808 070 21 191 8 583

Madagascar 23 5 171 444 341 2 099 346 216 2 947 490 1 205 281

Malawi 9 735 139 917 292 620 305 208 890 88 334

Mauritius 19 3 203 946 435 1 279 421 571 415 698 185 774

Mozambique 37 5 900 823 034 2 392 080 268 3 052 249 1 268 299

Namibia 71 7 028 653 501 1 886 638 075 971 494 254 526

Seychelles 15 2 499 592 802 1 024 805 052 285 548 130 721

South Africa 156 26 327 026 112 10 380 713 543 3 619 753 1 594 586

Swaziland 0 0 0 0 0

Tanzania 15 2 468 401 787 1 006 351 685 1 500 286 621 194

Zambia 4 124 104 705 43 879 868 43 292 15 857

Zimbabwe 4 120 584 561 46 120 769 19 835 8 322

Total 623 283 584 702 100 50 738 372 512 153 113 422 20 618 568



Muller Associates

A significant difference between this scenario and the previous is that ten of the fourteen countries

would have had a significant increase in the number of routes opened up, which would result in the

steep increase in the impact from this scenario to the next (year forty).

This could be due to the fact that other SADC countries (other than South Africa) would require a

significantly higher level of investment in infrastructure in order to let certain routes open up. Since the

number of routes within this analysis is based on the factors set out by the routes demand forecast

model, it is clear that by twenty five years after implementation of an air transport liberalisation

agreement in SADC these factors would have all improved to a level that tourism within SADC would

have a widespread impact.

2.5.4.1.4 Year 40

Table 2.5-10 Tourism Impact in Year 40 Countries Routes Total Impact On GDP

(2009 Rands) Direct Impact On GDP (2009 Rands)



Angola 1 086 840 729 260 494 110 081 377 944 530 634 836 60 918 028

Botswana 276 36 180 665 295 8 039 926 585 7 650 628 2 500 990

Democratic Republic of Congo 640 274 261 929 632 33 068 514 393 39 027 428 7 328 414

Lesotho 49 3 326 557 540 1 124 708 069 1 179 321 462 570

Madagascar 244 39 294 600 212 15 655 428 090 22 254 205 9 058 674

Malawi 90 5 865 157 643 2 243 125 495 2 614 027 1 065 563

Mauritius 47 6 852 074 474 2 699 642 431 1 394 296 593 033

Mozambique 352 42 555 722 679 16 687 713 112 19 760 528 8 130 856

Namibia 260 22 798 196 513 6 712 238 710 4 728 699 1 571 337

Seychelles 29 4 124 427 991 1 698 478 633 714 190 313 647

South Africa 310 42 777 340 455 16 879 369 876 7 688 656 3 318 649

Swaziland 12 559 326 724 197 665 089 262 611 107 940

Tanzania 52 5 327 530 384 2 153 568 234 3 088 480 1 274 761

Zambia 16 414 380 714 149 128 603 127 870 47 630

Zimbabwe 5 150 076 178 57 400 621 24 686 10 358

Total 3 468 1 325 217 246 927 217 448 285 885 641 150 459 96 702 448

The routes open would have increased by 2845 and the impact on the economies of the SADC countries

would have increased by a large amount from year 25, as can be seen in Table 2.5-10.



Muller Associates

2.5.4.1.5 Year 50





Angola 1 123 862 950 838 267 112 675 025 388 543 271 426 62 293 308

Botswana 280 36 270 819 793 8 067 334 439 7 669 855 2 508 281

Democratic Republic of Congo 815 330 399 812 171 40 350 699 246 49 313 945 9 817 931

Lesotho 54 3 524 207 131 1 191 180 670 1 269 359 498 283

Madagascar 265 41 633 774 979 16 606 041 230 23 760 119 9 673 330

Malawi 96 5 982 259 593 2 289 193 433 2 689 300 1 096 182

Mauritius 48 6 923 003 100 2 727 923 957 1 405 943 598 009

Mozambique 381 44 448 322 970 17 438 104 141 20 800 309 8 557 940

Namibia 273 23 214 179 360 6 802 166 393 4 815 759 1 593 254

Seychelles 30 4 189 945 857 1 725 545 242 725 092 318 304

South Africa 321 43 445 362 666 17 137 934 573 7 779 967 3 356 839

Swaziland 14 590 922 702 206 202 692 267 877 109 959

Tanzania 62 5 919 157 876 2 390 848 574 3 417 929 1 410 268

Zambia 20 475 776 685 171 648 848 144 106 53 824

Zimbabwe 5 150 076 178 57 400 621 24 686 10 358

Total 3 787 1 410 118 459 326 229 837 249 447 667 355 671 101 896 069

Table 2.5-11 displays the impact increased tourism as a result of an air transport liberalisation

agreement would have on SADC in the final year of the forecast. There would be 3787 routes open, and

the impact on GDP and Employment in the region would have increased greatly over the fifty year

period.

2.5.4.2 Impact of Atmospheric Pollution, Noise Pollution and Security Over 50 Years

Three major indirect costs were highlighted in this study. An air transportation liberalisation policy will

increase atmospheric pollutants in the air, create more noise pollution and increase the burden of

security at airports. These costs have been calculated using the impact model and the results are shown

in Table 2.5-12. The calculations for the units used in the model are discussed in Section 2.4.3. The

results are in Table 2.4-10.

In the US the Federal Aviation Agency defines airline noise pollution as that which is loud enough to

disturb a family watching television. This definition is used to define noise pollution in this study as well.

Noise pollution impacts on property values and quality of life. The Eurocontrol measure of noise

pollution places it at R693 per takeoff and landing and as air transportation liberalisation policy takes

effect the impact will increase significantly over time, reaching R345m per annum in fifty years from

implementation. The short term (5 year) impact is rather small at R8,8m per annum and relatively

insignificant in terms of the overall positive impact.



Muller Associates

Table 2.5-12 Cost of Pollution and Security

Figure 2.5-19 Cost of Noise Pollution

Aircraft pollution from emissions is an emotive issue as people often have the perception that

aeroplanes are large contributors to CO2 emissions. However, currently aircraft atmospheric emissions

(70% of which are CO2) contribute only 3% of EU total CO2 emissions. The total calculated cost of

pollution in the fifth year of air transportation liberalisation implementation is R8,9m rising steadily with

an exponential increase from the 17th year as the impact of an air transportation liberalisation policy

takes effect. The total cost of pollution increases to R645m at the fifty year mark as total flying hours

R -

R 50,000,000.00

R 100,000,000.00

R 150,000,000.00

R 200,000,000.00

R 250,000,000.00

R 300,000,000.00

R 350,000,000.00

R 400,000,000.00

5 10 15 20 25 30 35 40 45 50

Years

Indirect Costs

Years Cost of Pollution Cost of noise pollution Cost of Security

5 R 8,913,136.87 R 8,843,296.00 R 44,638,920.25

10 R 13,051,507.63 R 15,498,560.00 R 77,498,800.90

15 R 13,398,789.61 R 16,227,904.00 R 80,718,169.30

20 R 23,030,384.28 R 27,259,232.00 R 132,556,756.40

25 R 75,339,598.46 R 56,797,664.00 R 306,044,392.79

30 R 225,875,002.76 R 136,752,000.00 R 753,253,360.05

35 R 413,023,162.06 R 231,019,712.00 R 1,247,466,816.32

40 R 570,231,581.77 R 316,170,624.00 R 1,656,004,413.96

45 R 615,124,874.90 R 338,780,288.00 R 1,754,588,698.25

50 R 624,335,801.75 R 345,253,216.00 R 1,777,045,808.69



Muller Associates

increase. This total is nearly double that of the noise pollution total as the calculation is based on flying

hours and not number of flights.

Figure 2.5-20 Cost of Pollution

Currently most security costs are carried by the carrier airlines and vary between international flights

(R53.76) and domestic flights (R32.93). These costs are based on the Australian costing model and are

per passenger. Not all costs are carried by airlines and some of the total spending would be a burden of

the state where the flights originate and end. Airline security is a national security interest. Airport

security costs as a result of air transportation liberalisation policy will rise to R1,8bn in the fiftieth year,

and as such will become a large industry as a result of the air transportation liberalisation policy across

the SADC region. Even in the fifth year a boost of R45m into regional airports will contribute significantly

to employment. An increase in airport security costs will be good for the economy as it will lead to

increased spending on employment.

R -

R 100,000,000.00

R 200,000,000.00

R 300,000,000.00

R 400,000,000.00

R 500,000,000.00

R 600,000,000.00

R 700,000,000.00

5 10 15 20 25 30 35 40 45 50

Years



Muller Associates

Figure 2.5-21 Cost of Security

Whilst the security costs will be the largest contributor to indirect costs it is the easiest one to quantify.

The true cost of noise and fuel burning pollution could be much higher. From a fairly modest level of

R63m in the fifth year, indirect costs from an air transportation liberalisation policy will balloon up to

R2,7bn at current prices by the fiftieth year of operation.

R -

R 200,000,000.00

R 400,000,000.00

R 600,000,000.00

R 800,000,000.00

R 1,000,000,000.00

R 1,200,000,000.00

R 1,400,000,000.00

R 1,600,000,000.00

R 1,800,000,000.00

R 2,000,000,000.00

5 10 15 20 25 30 35 40 45 50

Years



Muller Associates

Figure 2.5-22 Total Indirect Costs

2.5.5 Airport and navigational infrastructure

2.5.5.1 Navigational infrastructure per route

As discussed in the methodology we can estimate the cost of navigational infrastructure required per

route at flight level 145 and 195. The weekly costs for this infrastructure is displayed in Table 2.5-13

below, as can be observed the weekly costs exceed R 1 billion after 50 years as the number of routes

being flown increases. The weekly cost of navigational infrastructure per route has been graphically

represented by Figure 2.5-23. The graph once again adopts the s bend curve that is present in all the

graphs before.

R -

R 500,000,000.00

R 1,000,000,000.00

R 1,500,000,000.00

R 2,000,000,000.00

R 2,500,000,000.00

R 3,000,000,000.00

5 10 15 20 25 30 35 40 45 50

Years

Cost of Security


Cost of Pollution



Muller Associates

Table 2.5-13 Weekly cost navigational infrastructure per route Years Flight Level 145 Flight Level 195

5 R 20,021,153.85 R 16,192,628.21

10 R 30,307,051.28 R 27,660,512.82

15 R 31,258,269.23 R 29,897,051.28

20 R 53,547,307.69 R 50,750,128.21

25 R 162,721,282.05 R 141,441,858.97

30 R 473,688,910.26 R 384,301,410.26

35 R 858,029,358.97 R 683,673,269.23

40 R 1,184,967,692.31 R 937,951,794.87

45 R 1,277,056,025.64 R 1,009,440,641.03

50 R 1,296,504,038.46 R 1,024,944,166.67

Figure 2.5-23 Weekly cost navigational infrastructure per route

2.5.5.2 Airport navigational infrastructure

All the results up to this point have been exhibited as per route weekly costs. In order to correctly

estimate the cost of airport navigational infrastructure and the cost of airport expansions to increase

airport capacity we’ve calculated these costs annually and per airport. These results are to be viewed

separately from previous results, and will be brought in line with other results in sections to come.

R -

R 200,000,000.00

R 400,000,000.00

R 600,000,000.00

R 800,000,000.00

R 1,000,000,000.00

R 1,200,000,000.00

R 1,400,000,000.00

5 10 15 20 25 30 35 40 45 50

Flight Level 145

Flight Level 195



Muller Associates

Figure 2.5-24 below displays the cost of airport navigational infrastructure over the 50 year period. As

the number of origin and destination airports increase, the costs for navigational infrastructure at the

various airports in the SADC region are required.

Figure 2.5-24 Airport navigational infrastructure

Table 2.5-14 displays the total airport navigational infrastructure costs over the 50 year forecast. The

cost are higher at airports with higher passenger numbers. It can be seen that in excess of R 12 billion

(2009 Rands) would be required to cover the airports navigational infrastructure costs over the 50 year

period.

R 1,130,000,000.00

R 1,140,000,000.00

R 1,150,000,000.00

R 1,160,000,000.00

R 1,170,000,000.00

R 1,180,000,000.00

R 1,190,000,000.00

R 1,200,000,000.00

R 1,210,000,000.00

R 1,220,000,000.00

R 1,230,000,000.00

5 10 15 20 25 30 35 40 45 50

Airport Navigational Infrastructure



Muller Associates

Table 2.5-14 Airport Navigational Infrastructure Location Airport Navigational

Infrastructure Location Airport

Navigational Infrastructure

Location Airport Navigational Infrastructure

Cabinda R 105,500,000.00 Mbuji-Mayi R 21,666,666.67 Durban R 521,500,000.00

Catumbela R 105,500,000.00 Maseru R 105,500,000.00 George R -

Dundo R - Antanànarìvo R 521,500,000.00 Lanseria R 105,500,000.00

Huambo R 21,666,666.67 Mahajanga R 105,500,000.00 Johannesburg R 521,500,000.00

Kuito R 21,666,666.67 Nosy Be R 13,000,000.00 Kimberley R 105,500,000.00

Luanda R 521,500,000.00 Toamasina R 105,500,000.00 Mafikeng R 21,666,666.67

Lubango R 21,666,666.67 Toliara R 21,666,666.67 Nelspruit R 105,500,000.00

Luena R 21,666,666.67 Blantyre R 105,500,000.00 Polokwane R 21,666,666.67

Malanje R 21,666,666.67 Lilongwe R 521,500,000.00 Port Elizabeth R 105,500,000.00

Menongue R 21,666,666.67 Port Louis R 521,500,000.00 Pilanesberg R 19,500,000.00

Namibe R 21,666,666.67 Beira R 105,500,000.00 Umtata R 21,666,666.67

Ondjiva R 21,666,666.67 Chimoio R 15,166,666.67 Upington R 105,500,000.00

Saurimo R 21,666,666.67 Cuamba R 13,000,000.00 Welkom R 19,500,000.00

Soyo R 21,666,666.67 Lichinga R 105,500,000.00 Manzini R 105,500,000.00

Uíge R 17,333,333.33 Maputo R 521,500,000.00 Dar-Es-Salaam

R 521,500,000.00

Francistown R 105,500,000.00 Moçimboa da Praia R 105,500,000.00 Dodoma R 105,500,000.00

Gaborone R 521,500,000.00 Mueda R 13,000,000.00 Kilimanjaro R 105,500,000.00

Kasane R 21,666,666.67 Nampula R 105,500,000.00 Mtwara R 21,666,666.67

Maun R 105,500,000.00 Tete R 21,666,666.67 Mwanza R 21,666,666.67

Bukavu R 13,000,000.00 Grootfontein R 84,400,000.00 Zanzibar R 521,500,000.00

Buta-Zega R 13,000,000.00 Karabib R 15,166,666.67 Kitwe R -

Gbadolite R 21,666,666.67 Katima Mulilo R 17,333,333.33 Livingstone R 105,500,000.00

Gemena R 13,000,000.00 Keetmanshoop R 17,333,333.33 Lusaka R 521,500,000.00

Goma R 13,000,000.00 Mariental R 15,166,666.67 Mfuwe R 8,666,666.67

Isiro-Matari R 13,000,000.00 Ondangwa R 17,333,333.33 Ndola R 21,666,666.67

Kananga R 13,000,000.00 Rundu R 17,333,333.33 Bulawayo R 105,500,000.00

Kindu R 13,000,000.00 Windhoek R 521,500,000.00 Harare R 521,500,000.00

Kinshasa R 521,500,000.00 Seychelles R 521,500,000.00 Hwange R 21,666,666.67

Kisangani R 105,500,000.00 Bisho R 105,500,000.00 Victoria Falls R 105,500,000.00

Lubumbashi R 105,500,000.00 Bloemfontein R 105,500,000.00 TOTAL R 12,076,400,000.00

Mbandaka R 13,000,000.00 Cape Town R 521,500,000.00



Muller Associates

2.5.5.3 Airport Infrastructure Costs

As explained in the previous section airport infrastructure costs have been reported per airport

displaying all costs incurred over the 50 year period. The airport infrastructure costs have been pegged

to the forecasted number of passengers per airport over the 50 year period. When the number of

forecasted passengers exceeds the airports annual capacity, the airport infrastructure costs are incurred

(the cost ratio applied for addition infrastructure is one million additional passenger capacity is the

equivalent of R 600 million spend on airport infrastructure.) Figure 2.5-25 displays the escalation of

airport infrastructure costs over the 50 year period as additional routes are added thereby increasing

the number of passengers utilising air transport as it becomes increasingly cheaper to fly and as flights

become more direct.

Figure 2.5-25 Airport Infrastructure Costs

Table 2.5-15 below indicates the total investment required in airport infrastructure over the 50 year

period per airport. It can be seen that mostly the South African airports require the largest investment

over the 50 year period; this is due to the higher demand for flights from other SADC regions to South

Africa, as business and leisure activities are more developed and available when compared to other

SADC partners. Interestingly Lanseria Airport in Johannesburg requires the largest investment in airport

infrastructure to take advantage of all the added demand for flights in and out of the

Johannessburg/Pretoria area.

R -

R 100,000,000,000.00

R 200,000,000,000.00

R 300,000,000,000.00

R 400,000,000,000.00

R 500,000,000,000.00

R 600,000,000,000.00

5 10 15 20 25 30 35 40 45 50

Year

Airport Infrastructure Costs



Muller Associates

Table 2.5-15 Airport Infrastructure Costs Location Airport Infrastructure

Costs Location Airport Infrastructure

Costs Location Airport Infrastructure Costs

Cabinda R 30,762,646,164.32 Mbuji-Mayi R 24,753,794,341.17 Durban R 38,705,155,564.19

Catumbela R 21,704,608,870.95 Maseru R 15,845,658,240.17 George R -

Dundo R - Antanànarìvo R 8,121,960,885.89 Lanseria R 50,916,414,646.06

Huambo R 32,799,705,107.64 Mahajanga R 16,996,112,278.87 Johannesburg R -

Kuito R 31,326,914,030.96 Nosy Be R 21,804,839,914.27 Kimberley R 44,083,043,709.13

Luanda R 14,454,353,582.72 Toamasina R 19,094,988,395.56 Mafikeng R 40,811,869,973.20

Lubango R 31,374,951,738.71 Toliara R 22,937,552,849.95 Nelspruit R 42,677,327,210.89

Luena R 27,386,961,412.25 Blantyre R 17,641,591,388.30 Polokwane R 42,265,713,353.11

Malanje R 31,857,532,088.63 Lilongwe R 6,055,562,817.46 Port Elizabeth R 41,889,245,560.08

Menongue R 30,677,820,412.50 Port Louis R 12,345,883,086.00 Pilanesberg R 40,046,339,330.98

Namibe R 31,967,122,412.18 Beira R 20,113,697,084.71 Umtata R 40,306,034,452.31

Ondjiva R 29,117,281,210.36 Chimoio R 23,705,642,728.46 Upington R 42,797,693,603.02

Saurimo R 30,955,943,213.46 Cuamba R 21,423,216,316.07 Welkom R 42,529,814,312.88

Soyo R 29,976,647,083.97 Lichinga R 23,590,797,888.70 Manzini R 17,821,283,568.37

Uíge R 30,352,589,997.88 Maputo R 7,783,416,063.19 Dar-Es-Salaam R 8,424,782,414.41

Francistown R 35,135,585,164.11 Moçimboa da Praia

R 19,933,260,259.03 Dodoma R 24,775,748,996.14

Gaborone R 11,489,436,347.38 Mueda R 19,705,744,750.39 Kilimanjaro R 21,088,863,923.42

Kasane R 27,894,701,088.10 Nampula R 20,528,698,093.77 Mtwara R 24,211,283,509.89

Maun R 26,245,742,033.60 Tete R 23,765,714,787.34 Mwanza R 27,957,419,377.31

Bukavu R 20,836,679,462.91 Grootfontein R 21,432,237,428.37 Zanzibar R 27,027,185,020.59

Buta-Zega R 18,670,970,710.90 Karabib R 24,282,126,980.62 Kitwe R -

Gbadolite R 19,005,255,956.46 Katima Mulilo R 28,014,954,576.04 Livingstone R 18,800,111,355.35

Gemena R 21,174,304,236.40 Keetmanshoop R 28,306,690,156.58 Lusaka R 8,921,260,503.81

Goma R 21,571,107,574.57 Mariental R 27,107,878,848.06 Mfuwe R 8,502,307,048.99

Isiro-Matari R 21,672,433,830.73 Ondangwa R 27,454,733,325.99 Ndola R 27,766,951,019.44

Kananga R 23,874,821,942.88 Rundu R 29,184,572,232.87 Bulawayo R 23,414,456,927.59

Kindu R 21,663,633,278.31 Windhoek R 9,559,680,304.59 Harare R 6,518,897,872.57

Kinshasa R 8,183,067,356.52 Seychelles R 8,749,277,162.18 Hwange R 17,155,638,948.89

Kisangani R 17,332,241,664.06 Bisho R 38,724,314,820.06 Victoria Falls R 10,761,251,323.26

Lubumbashi R 19,548,909,955.13 Bloemfontein R 42,568,700,235.46 TOTAL R 2,133,076,262,959.25

Mbandaka R 22,957,803,412.03 Cape Town R 19,395,099,852.65



Muller Associates

2.6 Impact of an air transport liberalisation agreement in the Southern

African Development Community (SADC)

In this section of the report the focuses on the overall impact of implementing an air transport

liberalisation agreement in SADC.

2.6.1 Total Computable Benefits

Table 2.6-1 below shows the total computable benefits (in constant 2009 Rands) arising from

implementation of an air transport liberalisation agreement in SADC. It can be seen that initially the

total computable benefit occurring throughout SADC equals R 8 billion per week. After 50 years this

would grow to R 265 billion per week. In calculating total impact of an air transport liberalisation

agreement on SADC, the direct impact of tourism on GDP was used as this captures the direct impact

felt by the tourism industry as the number of passengers using air travel increase over the 50 year

period.

Table 2.6-1 Total Benefits from the implementation of an air transport liberalisation agreement in SADC

Years* BENEFITS

Potential Turnover Time Saving (Rand per KM)


TOTAL BENEFITS

5 R 395,592,569.17 R 80,704,142.39 R 7,552,340,410.36 R 8,028,637,121.92

10 R 615,030,014.60 R 148,353,788.17 R 13,205,292,139.30 R 13,968,675,942.07

15 R 631,437,961.30 R 152,429,875.57 R 13,673,144,858.21 R 14,457,012,695.08

20 R 1,055,829,325.19 R 265,108,382.22 R 28,251,360,598.84 R 29,572,298,306.25

25 R 3,194,221,298.65 R 766,732,401.87 R 50,738,372,511.99 R 54,699,326,212.51

30 R 8,886,816,358.07 R 2,961,410,846.08 R 105,672,816,915.10 R 117,521,044,119.25

35 R 15,354,301,000.26 R 7,207,220,265.68 R 165,457,639,030.49 R 188,019,160,296.43

40 R 20,306,047,606.09 R 12,429,642,407.48 R 217,448,285,885.45 R 250,183,975,899.02

45 R 21,592,032,312.26 R 13,703,434,148.72 R 228,121,055,753.45 R 263,416,522,214.43

50 R 21,804,364,460.93 R 13,957,174,567.04 R 229,837,249,446.98 R 265,598,788,474.95

*post implementation of an air transport liberalisation agreement in SADC

Figure 2.6-1 exhibits the breakdown of total benefit incurred by the implementation of an air transport

liberalisation agreement in SADC. It can be seen that the largest contributor to total benefits is the

impact on the tourism industry followed by the benefit accruing to airlines. The passengers benefit due

to time saving is relatively minimal, however if the anticipated general decrease in airline ticket prices

was quantifiable and was taken into account this would increase the benefits considerably.



Muller Associates

Figure 2.6-1 Breakdown of Total Benefits incurred by the implementation of an air transport liberalisation agreement in SADC

R -

R 50,000,000,000.00

R 100,000,000,000.00

R 150,000,000,000.00

R 200,000,000,000.00

R 250,000,000,000.00

R 300,000,000,000.00

5 10 15 20 25 30 35 40 45 50

Year


Time Saving (Rand per KM)

Potential Turnover



2.6.2 Total Costs

The breakdown of total computable costs arising from the implementation of an air transport liberalisation agreement in SADC is shown in Table

2.6-2 below. When both direct and indirect costs are totalled initially cost incurred total R 99 million per week, this increases to R 4.5 billion per

week after 50 years.

Table 2.6-2 Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC Years Cost of flight

cancellation Cost of flight diversions




Cost of Pollution


Cost of Security Navigation Route Costs (FL 145)

TOTAL COSTS

5 R 16,598,813 R 315,380 R 81,715 R 1,258 R 17,046 R 8,913,137 R 8,843,296 R 44,638,920 R 20,021,154 R 99,430,719

10 R 30,904,372 R 694,787 R 180,018 R 2,771 R 37,553 R 13,051,508 R 15,498,560 R 77,498,801 R 30,307,051 R 168,175,421

15 R 32,305,925 R 768,933 R 199,230 R 3,066 R 41,561 R 13,398,790 R 16,227,904 R 80,718,169 R 31,258,269 R 174,921,847

20 R 52,098,054 R 1,204,203 R 312,008 R 4,802 R 65,088 R 23,030,384 R 27,259,232 R 132,556,756 R 53,547,308 R 290,077,835

25 R 101,208,861 R 2,207,197 R 571,882 R 8,802 R 119,300 R 75,339,598 R 56,797,664 R 306,044,393 R 162,721,282 R 705,018,979

30 R 223,961,750 R 4,561,179 R 1,181,796 R 18,189 R 246,533 R 225,875,003 R 136,752,000 R 753,253,360 R 473,688,910 R 1,819,538,721

35 R 356,211,205 R 7,081,210 R 1,834,733 R 28,239 R 382,741 R 413,023,162 R 231,019,712 R 1,247,466,816 R 858,029,359 R 3,115,077,177

40 R 465,155,210 R 9,153,407 R 2,371,637 R 36,503 R 494,744 R 570,231,582 R 316,170,624 R 1,656,004,414 R 1,184,967,692 R 4,204,585,812

45 R 491,444,508 R 9,652,908 R 2,501,057 R 38,495 R 521,742 R 615,124,875 R 338,780,288 R 1,754,588,698 R 1,277,056,026 R 4,489,708,596

50 R 497,433,107 R 9,766,692 R 2,530,538 R 38,948 R 527,892 R 624,335,802 R 345,253,216 R 1,777,045,809 R 1,296,504,038 R 4,553,436,042

*post implementation of an air transport liberalisation agreement in SADC



Muller Associates

As can be seen in Figure 2.6-2, below, the cost of navigational infrastructure per route, security,

pollution, noise pollution and flight cancellation make up the largest proportions of total costs incurred.

Due to low proportion of aircraft accidents and injuries, the cost of accidents resulting in fatality, minor

injury and major injury per flight is relatively inconsequential. Likewise the cost of diverting a flight is

slight due to infrequency of such flights.

Figure 2.6-2 Breakdown of Total Costs incurred by the implementation of an air transport liberalisation agreement in SADC

2.6.3 Impact of an air transport liberalisation agreement in the Southern African

Development Community

The impact of implementation of an air transport liberalisation agreement in SADC is overwhelming

positive when one considers the total benefits and costs computed in Table 2.6-1 and 2.6-2 above. It

must be noted that aircraft operational costs have been excluded due to lack of information provided by

airlines. Computable benefits are larger than computable costs by a factor ranging between 1000 during

the first five year period to 78 at the end of the 50 year modelling period. This is because the existence

of excess capacity in aviation infrastructure within SADC at the start of the implementation process

keeps initial costs relatively modest. The required investment to sustain implementation of an air

transport liberalisation agreement in SADC also grows substantially over the 50 year study period.

Nevertheless the net benefit at the end of the 50 year study period still totals a very significant R249.7

billion per week, growing from an initial net benefit totalling R7.8 billion per week during the first 5

years post the an air transport liberalisation agreement implementation. This would indicate that over

a 50 year period the net benefit would grow at a real rate of 7.98% annually, an annual real growth rate

R -

R 500,000,000

R 1,000,000,000

R 1,500,000,000

R 2,000,000,000

R 2,500,000,000

R 3,000,000,000

R 3,500,000,000

R 4,000,000,000

R 4,500,000,000

R 5,000,000,000

5 10 15 20 25 30 35 40 45 50

Year

Navigation Route Costs (FL 145)

Cost of Security


Cost of Pollution






Muller Associates

somewhat higher than the annual real GDP growth currently anticipated and experienced in SADC. In

2009 the SADC Gross Domestic Product was estimated at R 4.4 trillion12 . At this level the aviation

industry would be contributing 0.18% of total GDP (2009 Rands) in the first 5 years post an air transport

liberalisation agreement implementation and 5.64% of total GDP (2009 Rands) post 50 years of an air

transport liberalisation agreement implementation.

Figure 2.6-3 below, graphs the total computable impact of an air transport liberalisation agreement in

SADC over the 50 year period. It can be seen that total costs (in red) are slight in comparison to total

benefits (in blue). The net computable benefits comprise the blue area alone. The total computable

benefits are signified by the red and blue areas put together, while the red area alone indicates total

computable costs.

Figure 2.6-3 The total impact of an air transport liberalisation agreement in SADC being implemented in the Southern African Development community

12 International Monetary Fund, 2007. http://www.imf.org/external/pubs/ft/weo/2007/02/weodata/index.aspx

R -

R 50,000,000,000.00

R 100,000,000,000.00

R 150,000,000,000.00

R 200,000,000,000.00

R 250,000,000,000.00

R 300,000,000,000.00

5 10 15 20 25 30 35 40 45 50

Years

TOTAL BENEFITS

TOTAL COSTS

http://www.imf.org/external/pubs/ft/weo/2007/02/weodata/index.aspx



Muller Associates

2.7 Impact of an air transport liberalisation agreement reflecting the

investment and capital expenditure in airport and navigational

infrastructure

Table 2.7-1 below displays the total impact of air transport liberalisation over the 50 year period per

airport. The benefit less costs column takes into account all the weekly benefits less costs mentioned in

previous sections, this displays the impact per airport. The airport infrastructure costs indicate the total

cost of expanding annual passenger capacities over the 50 year period per airport. The airport

navigational systems column display the total cost of navigational infrastructure per airport over the 50

year period. The last column ‘Total impact after infrastructure costs’ measures the financial impact of air

transport liberalisation in SADC when taking into account all capital and infrastructural investments

required to take advantage of this liberalisation.

Most importantly there are 5 airports that have a negative impact over the 50 year period; these

airports are Cabinda, Catumbela, Huambo and Kuito from Angola; and Kitwe from Zambia. Although

these airports have a negative impact over the 50 year period, the total impact in the region is

overwhelmingly positive, even when taking into account the additional airport and navigational

infrastructural requirements. For a comprehensive and detailed list of impacts over the 50 year period

per airport please refer to Appendix G.

Table 2.7-1 Total impact over 50 years after infrastructure costs are taken into account per airport Location Benefits less costs Airport

infrastructure Airport navigational systems

Total impact after infrastructure costs

Cabinda R 13,135,594,876 R 30,762,646,164 R 105,500,000 R -17,732,551,288

Catumbela R 15,135,950,379 R 21,704,608,871 R 105,500,000 R -6,674,158,492

Dundo R - R - R - R -

Huambo R 18,968,271,072 R 32,799,705,108 R 21,666,667 R -13,853,100,703

Kuito R 18,689,215,470 R 31,326,914,031 R 21,666,667 R -12,659,365,227

Luanda R 35,312,114,184 R 14,454,353,583 R 521,500,000 R 20,336,260,601

Lubango R 32,307,418,877 R 31,374,951,739 R 21,666,667 R 910,800,471

Luena R 37,396,632,803 R 27,386,961,412 R 21,666,667 R 9,988,004,724

Malanje R 33,419,030,001 R 31,857,532,089 R 21,666,667 R 1,539,831,245

Menongue R 42,194,390,670 R 30,677,820,412 R 21,666,667 R 11,494,903,591

Namibe R 52,565,917,229 R 31,967,122,412 R 21,666,667 R 20,577,128,150

Ondjiva R 55,206,012,572 R 29,117,281,210 R 21,666,667 R 26,067,064,695

Saurimo R 66,112,557,006 R 30,955,943,213 R 21,666,667 R 35,134,947,126

Soyo R 73,599,566,822 R 29,976,647,084 R 21,666,667 R 43,601,253,072

Uíge R 60,701,876,855 R 30,352,589,998 R 17,333,333 R 30,331,953,524

Francistown R 112,435,059,703 R 35,135,585,164 R 105,500,000 R 77,193,974,539

Gaborone R 126,747,019,578 R 11,489,436,347 R 521,500,000 R 114,736,083,231

Kasane R 87,449,683,593 R 27,894,701,088 R 21,666,667 R 59,533,315,838



Muller Associates

Maun R 104,737,840,516 R 26,245,742,034 R 105,500,000 R 78,386,598,482

Bukavu R 91,974,793,085 R 20,836,679,463 R 13,000,000 R 71,125,113,622

Buta-Zega R 90,872,827,828 R 18,670,970,711 R 13,000,000 R 72,188,857,118

Gbadolite R 97,660,364,082 R 19,005,255,956 R 21,666,667 R 78,633,441,459

Gemena R 102,803,308,089 R 21,174,304,236 R 13,000,000 R 81,616,003,852

Goma R 108,712,929,432 R 21,571,107,575 R 13,000,000 R 87,128,821,857

Isiro-Matari R 120,400,614,619 R 21,672,433,831 R 13,000,000 R 98,715,180,789

Kananga R 97,178,167,198 R 23,874,821,943 R 13,000,000 R 73,290,345,255

Kindu R 102,167,901,405 R 21,663,633,278 R 13,000,000 R 80,491,268,127

Kinshasa R 146,328,475,939 R 8,183,067,357 R 521,500,000 R 137,623,908,582

Kisangani R 131,214,272,888 R 17,332,241,664 R 105,500,000 R 113,776,531,224

Lubumbashi R 155,406,013,907 R 19,548,909,955 R 105,500,000 R 135,751,603,952

Mbandaka R 127,269,799,143 R 22,957,803,412 R 13,000,000 R 104,298,995,731

Mbuji-Mayi R 125,232,224,584 R 24,753,794,341 R 21,666,667 R 100,456,763,576

Maseru R 167,101,320,224 R 15,845,658,240 R 105,500,000 R 151,150,161,984

Antanànarìvo R 309,736,207,278 R 8,121,960,886 R 521,500,000 R 301,092,746,392

Mahajanga R 231,990,742,240 R 16,996,112,279 R 105,500,000 R 214,889,129,962

Nosy Be R 225,102,887,915 R 21,804,839,914 R 13,000,000 R 203,285,048,001

Toamasina R 295,708,091,889 R 19,094,988,396 R 105,500,000 R 276,507,603,493

Toliara R 239,258,253,432 R 22,937,552,850 R 21,666,667 R 216,299,033,915

Blantyre R 190,228,104,292 R 17,641,591,388 R 105,500,000 R 172,481,012,904

Lilongwe R 181,331,634,287 R 6,055,562,817 R 521,500,000 R 174,754,571,469

Port Louis R 606,131,604,552 R 12,345,883,086 R 521,500,000 R 593,264,221,466

Beira R 217,136,053,533 R 20,113,697,085 R 105,500,000 R 196,916,856,448

Chimoio R 170,895,781,172 R 23,705,642,728 R 15,166,667 R 147,174,971,776

Cuamba R 159,194,864,421 R 21,423,216,316 R 13,000,000 R 137,758,648,105

Lichinga R 177,744,106,905 R 23,590,797,889 R 105,500,000 R 154,047,809,016

Maputo R 285,106,971,134 R 7,783,416,063 R 521,500,000 R 276,802,055,071

Moçimboa da Praia

R 202,459,822,345 R 19,933,260,259 R 105,500,000 R 182,421,062,085

Mueda R 187,439,099,382 R 19,705,744,750 R 13,000,000 R 167,720,354,631

Nampula R 269,697,762,029 R 20,528,698,094 R 105,500,000 R 249,063,563,935

Tete R 195,888,132,266 R 23,765,714,787 R 21,666,667 R 172,100,750,812

Grootfontein R 248,492,530,242 R 21,432,237,428 R 84,400,000 R 226,975,892,814

Karabib R 221,958,472,576 R 24,282,126,981 R 15,166,667 R 197,661,178,929

Katima Mulilo R 229,639,103,367 R 28,014,954,576 R 17,333,333 R 201,606,815,458

Keetmanshoop R 309,841,858,605 R 28,306,690,157 R 17,333,333 R 281,517,835,115

Mariental R 269,882,924,036 R 27,107,878,848 R 15,166,667 R 242,759,878,521

Ondangwa R 258,900,704,039 R 27,454,733,326 R 17,333,333 R 231,428,637,379

Rundu R 257,454,998,068 R 29,184,572,233 R 17,333,333 R 228,253,092,501

Windhoek R 396,517,070,883 R 9,559,680,305 R 521,500,000 R 386,435,890,578



Muller Associates

Seychelles R 703,501,657,625 R 8,749,277,162 R 521,500,000 R 694,230,880,462

Bisho R 554,445,228,667 R 38,724,314,820 R 105,500,000 R 515,615,413,847

Bloemfontein R 518,236,753,001 R 42,568,700,235 R 105,500,000 R 475,562,552,766

Cape Town R 850,893,805,391 R 19,395,099,853 R 521,500,000 R 830,977,205,539

Durban R 680,019,685,523 R 38,705,155,564 R 521,500,000 R 640,793,029,959

George R - R - R - R -

Lanseria R 623,425,486,875 R 50,916,414,646 R 105,500,000 R 572,403,572,229

Johannesburg R 599,808,390,969 R - R 521,500,000 R 599,286,890,969

Kimberley R 520,597,571,517 R 44,083,043,709 R 105,500,000 R 476,409,027,808

Mafikeng R 456,878,656,267 R 40,811,869,973 R 21,666,667 R 416,045,119,627

Nelspruit R 511,508,260,400 R 42,677,327,211 R 105,500,000 R 468,725,433,189

Polokwane R 459,727,696,484 R 42,265,713,353 R 21,666,667 R 417,440,316,465

Port Elizabeth R 757,947,901,871 R 41,889,245,560 R 105,500,000 R 715,953,156,311

Pilanesberg R 458,020,497,838 R 40,046,339,331 R 19,500,000 R 417,954,658,507

Umtata R 589,451,162,905 R 40,306,034,452 R 21,666,667 R 549,123,461,786

Upington R 564,438,760,296 R 42,797,693,603 R 105,500,000 R 521,535,566,693

Welkom R 539,261,292,507 R 42,529,814,313 R 19,500,000 R 496,711,978,194

Manzini R 337,187,877,496 R 17,821,283,568 R 105,500,000 R 319,261,093,927

Dar-Es-Salaam R 640,241,051,391 R 8,424,782,414 R 521,500,000 R 631,294,768,976

Dodoma R 460,907,809,563 R 24,775,748,996 R 105,500,000 R 436,026,560,566

Kilimanjaro R 601,328,818,794 R 21,088,863,923 R 105,500,000 R 580,134,454,871

Mtwara R 463,076,216,765 R 24,211,283,510 R 21,666,667 R 438,843,266,588

Mwanza R 599,323,031,470 R 27,957,419,377 R 21,666,667 R 571,343,945,426

Zanzibar R 575,823,890,548 R 27,027,185,021 R 521,500,000 R 548,275,205,528

Kitwe R -770,778,388 R - R - R -770,778,388

Livingstone R 370,996,780,292 R 18,800,111,355 R 105,500,000 R 352,091,168,937

Lusaka R 456,850,384,931 R 8,921,260,504 R 521,500,000 R 447,407,624,427

Mfuwe R 95,333,266,016 R 8,502,307,049 R 8,666,667 R 86,822,292,300

Ndola R 430,933,005,132 R 27,766,951,019 R 21,666,667 R 403,144,387,446

Bulawayo R 307,810,325,118 R 23,414,456,928 R 105,500,000 R 284,290,368,191

Harare R 382,745,641,210 R 6,518,897,873 R 521,500,000 R 375,705,243,338

Hwange R 238,906,513,453 R 17,155,638,949 R 21,666,667 R 221,729,207,837

Victoria Falls R 228,987,817,785 R 10,761,251,323 R 105,500,000 R 218,121,066,462

TOTAL R 24,566,019,405,225 R 2,133,076,262,959 R 12,076,400,000 R 22,420,866,742,266



Muller Associates

Conclusion

There is overwhelming evidence that implementation of an air transport liberalisation agreement in

SADC will produce significant and sustainable benefits to the economy of the region (even when the

additional infrastructural requirements are taken into account.) The forecast growth in the aviation

market and tourism markets together with the wider economic benefits that will flow from this are so

vast and far reaching that not only are the computable costs to be regarded as insignificant (when

excluding the aircrafts operational costs), but in all likelihood, it can be considered that the

unquantifiable costs identified as associated with such an initiative will, similarly, be no obstacle to

success.

Based on the results discussed in this study an air transport liberalisation agreement in the Southern

African Development Community would have an overwhelming impact in this region. It would

encourage and stimulate tourism and the numbers of passengers utilising air transport as a primary

means of transport between two major cities in SADC would increase significantly. The only potential

inhibitor to this agreement would be the additional navigational and airport infrastructure required to

make an agreement such as this successful, this would need to be funded by airports authorities or

governments in the region. Furthermore, the establishment of a regional regulatory and competition

authority is essential to monitor the implementation of this agreement and ensure that no country or

airlines acts in an uncompetitive manner.



Muller Associates

References

List of References

World Trade and Tourism Website

o http://www.wttc.org/

o http://www.wttc.org/viewfile.php?file=/var/www/wttc/public_html/bin/pdf/original_pdf_file/economic_impact_research_metho.pdf

Source for pollutant volumes: “Forecasting Civil Aviation Fuel Burn and Emissions in Europe, EEC

Note No. 8/2001”, EUROCONTROL Experimental Centre, May 2001

http://www.eurocontrol.int/eec/gallery/content/public/documents/EEC_notes/2001/EEC_note

_2001_08.pdf

Source for cost of pollutants: “Economic incentives to control the global environmental impact of European aviation/Level of the incentive”, CE, Solutions for environment, economy and technology, Delft, The Netherlands. Draft preliminary study, 2 May 2001 suggests the medium costs of aviation pollution as follows:

Source for Burn Rate: “Evaluating the true cost to airlines of one minute of airborne or ground delay”, University of Westminster, May 2004

(http://www.eurocontrol.int/prc/gallery/content/public/Docs/cost_of_delay.pdf)

Type here (replace this text)

Conversions are based on the following websites

Australian Dollar (AUD) inflation

http://www.rateinflation.com/consumer-price-index/australia-historical-cpi.php?form=auscpi

Australian Dollar - South African Rand (AUD-ZAR) exchange rate history

http://www.exchangerates.org.uk/AUD-ZAR-exchange-rate-history.html

Average for last 150 days (from 5 March, back 150 days)

Euro inflation

http://www.ecb.europa.eu/stats/prices/hicp/html/inflation.en.html

Euro – South African Rand (EUR-ZAR) exchange rate history

http://www.exchangerates.org.uk/EUR-ZAR-exchange-rate-history.html

http://www.wttc.org/





http://www.eurocontrol.int/prc/gallery/content/public/Docs/cost_of_delay.pdf

http://www.rateinflation.com/consumer-price-index/australia-historical-cpi.php?form=auscpi

http://www.exchangerates.org.uk/AUD-ZAR-exchange-rate-history.html

http://www.ecb.europa.eu/stats/prices/hicp/html/inflation.en.html

http://www.exchangerates.org.uk/EUR-ZAR-exchange-rate-history.html



Muller Associates

Average for last 150 days (from 14 March, back 150 days)

Bureau of Transportation Statistics

http://www.bts.gov/press_releases/2003/dot016_03.html

“The consumer report includes BTS data on the number of domestic flights cancelled by the reporting carriers. In

January, the carriers cancelled 2.5 percent of their scheduled domestic flights, higher than the 2.3 percent rate

recorded in January 2009 but lower than December 2009's rate of 2.8.”

http://www.bts.gov/press_releases/2003/dot016_03.html



List of Tables

Table 1.1-1 Definition of air freedom rights ................................................................................................ vi

Table 1.1-2 Total number of domestic and international airline passengers, by region ............................ vii

Table 1.1-3 Total Benefits incurred by the implementation of an air transport liberalisation aagreement

in SADC ....................................................................................................................................................... xvii

Table 1.1-4 Total Costs incurred by the implementation of an air transport liberalisation agreement in

SADC ............................................................................................................................................................ xix

Table 1.1-5 impact over 50 years after infrastructure costs are taken into account per airport .............. xxii

Table 1.2-1 Definition of air freedom rights ................................................................................................. 4

Table 1.5-1 Capacity and Traffic Growth for All Europe, 1990-2002 .......................................................... 21

Table 1.5-2 Summary of Intra-EU transport packages ................................................................................ 21

Table 1.5-3 : Capacity Shares of Low Cost Carriers ..................................................................................... 22

Table 1.5-4 Frequency market shares at the beginning of IATA Summer 2004 and 2006 seasons ........... 24

Table 1.6-1 Section analysis of regression on transport costs .................................................................... 28

Table 1.6-2 Forecasts in North-East Asian travel to North America ........................................................... 31

Table 2.2-1 Airports in SADC – Total Passengers ........................................................................................ 64

Table 2.3-1 Airlines Data ............................................................................................................................. 70

Table 2.3-2 Airports Data ............................................................................................................................ 74

Table 2.3-3 Stakeholders Data .................................................................................................................... 77

Table 2.4-1 Gross Domestic Product Per Capita, Current 2007 Prices ....................................................... 83

Table 2.4-2 Urban Population by Country .................................................................................................. 84

Table 2.4-3 Business, Political and Development Indicators for SADC Country ......................................... 85

Table 2.4-4 Tourism Infrastructure Index by Country ................................................................................ 86



Muller Associates

Table 2.4-5 Airport Infrastructure ............................................................................................................... 86

Table 2.4-6 Example of Calculated Indices by Airport ................................................................................ 90

Table 2.4-7 Determining the Demand Estimate for Routes ........................................................................ 91

Table 2.4-8 Potential Turnover and Seat Numbers .................................................................................... 94

Table 2.4-9 The Monetary Value of Costs ................................................................................................... 97

Table 2.4-10 Cost of Fuel .......................................................................................................................... 100

Table 2.4-11 Navigational Equipment Requirements per Route at 5 NM ................................................ 103

Table 2.4-12 Airport Navigational Equipment Required per Airport Type ............................................... 103

Table 2.4-13 Type 1 Airports in the SADC Region ..................................................................................... 104



Table 2.4-16 SADC Airport Capacities ....................................................................................................... 106

Table 2.5-1 Forecasted Turnover, Seat Numbers & Number of flights (per week) .................................. 107

Table 2.5-2 Passenger Time Saving Benefit .............................................................................................. 111

Table 2.5-3 Additional flight information ................................................................................................. 113

Table 2.5-4 Assumptions, Weights, Proportions and Figures Used .......................................................... 116

Table 2.5-5 Results Over 50 Year Period ................................................................................................... 117

Table 2.5-6 Tourism Impact Over 50 Years ............................................................................................... 122

Table 2.5-7 Tourism Impact in Year 5 ....................................................................................................... 124

Table 2.5-8 Tourism Impact in Year 15 ..................................................................................................... 125

Table 2.5-9 Tourism Impact in Year 25 ..................................................................................................... 125

Table 2.5-10 Tourism Impact in Year 40 ................................................................................................... 126



Muller Associates

Table 2.5-11 Tourism Impact in Year 50 ................................................................................................... 127

Table 2.5-12 Cost of Pollution and Security .............................................................................................. 128

Table 2.5-13 Weekly cost navigational infrastructure per route .............................................................. 132

Table 2.5-14 Airport Navigational Infrastructure ..................................................................................... 134

Table 2.5-15 Airport Infrastructure Costs ................................................................................................. 136

Table 2.6-1 Total Benefits from the implementation of an air transport liberalisation agreement in SADC

.................................................................................................................................................................. 137

Table 2.6-2 Total Costs incurred by the implementation of an air transport liberalisation agreement in

SADC .......................................................................................................................................................... 139

Table 2.7-1 Total impact over 50 years after infrastructure costs are taken into account per airport .... 142



Muller Associates

List of Figures

Figure 1.1-1 Breakdown of Total Benefits incurred by the implementation of an air transport

liberalisation agreement in SADC ............................................................................................................. xviii

Figure 1.1-2 Breakdown of Total Costs incurred by the implementation of an air transport liberalisation

agreement in SADC ...................................................................................................................................... xx

Figure 1.1-3 The total impact of an air transport liberalisation agreement being implemented in the

Southern African Development community ............................................................................................... xxi

Figure 1.3-1 South African Airways International Route Map ...................................................................... 6

Figure 1.3-2 Demand Curve for both a Pure and Normal Monopoly ........................................................... 8

Figure 1.3-3 Total number of domestic and international airline passengers, by region .......................... 11

Figure 1.3-4 Break down of the Yamoussoukro Decision implementation organs .................................... 12

Figure 1.4-1 Gravity forecast fails to fit actual data, European Region ...................................................... 17

Figure 1.5-1 Air market share between U.S. carriers and U.K. carriers ...................................................... 19

Figure 1.5-2 Growth in UK-India direct services 2000-2006 ....................................................................... 23

Figure 1.5-3 Breakdown of direct services to India in summer 2004 and 2006 ......................................... 24

Figure 1.5-4 Growth of direct point-to-point markets from the UK to India .............................................. 25

Figure 1.6-1 The effect of air transportation liberalisation agreements on air transport costs over time 30

Figure 1.6-2 Actual air travel between North-East Asia and North America .............................................. 31

Figure 2.2-1 Fleet size – Airlines in Angola ................................................................................................. 36

Figure 2.2-2 Air Botswana Financial data.................................................................................................... 37

Figure 2.2-3 Air Botswana Domestic and International departures ........................................................... 38

Figure 2.2-4 Air Botswana Domestic and International passengers ........................................................... 38

Figure 2.2-5 Air Botswana Fleet .................................................................................................................. 39



Muller Associates

Figure 2.2-6 Fleet size – DRC Airlines .......................................................................................................... 40

Figure 2.2-7 Air Lesotho Domestic and International Departures .............................................................. 40

Figure 2.2-8 Air Madagascar Domestic and International departures ....................................................... 41

Figure 2.2-9 Air Madagascar Domestic and International passenger numbers ......................................... 42

Figure 2.2-10 Air Madagascar Financial Data ............................................................................................. 43

Figure 2.2-11 Fleet size – Madagascar airlines ........................................................................................... 43

Figure 2.2-12 Air Malawi domestic and international departures ............................................................. 44

Figure 2.2-13 Air Malawi Domestic and International Passengers ............................................................. 44

Figure 2.2-14 Air Malawi Fleet .................................................................................................................... 45

Figure 2.2-15 Air Mauritius Domestic and International departures ......................................................... 46

Figure 2.2-16 Air Mauritius Domestic and International passengers ......................................................... 46

Figure 2.2-17 Air Mauritius Fleet ................................................................................................................ 47

Figure 2.2-18 LAM Domestic and International Departures ....................................................................... 48

Figure 2.2-19 LAM Domestic and International Passengers ....................................................................... 48

Figure 2.2-20 LAM Fleet .............................................................................................................................. 49

Figure 2.2-21 Air Namibia Domestic and International Departures ........................................................... 49

Figure 2.2-22 Air Namibia Domestic and International Passengers ........................................................... 50

Figure 2.2-23 Air Namibia Fleet .................................................................................................................. 50

Figure 2.2-24 Air Seychelles Domestic and International Departures ........................................................ 51

Figure 2.2-25 Air Seychelles Domestic and International passengers ........................................................ 52

Figure 2.2-26 Air Seychelles Fleet ............................................................................................................... 52

Figure 2.2-27 South African Airways Domestic and International departures ........................................... 53



Muller Associates

Figure 2.2-28 South African Airways Domestic and International passengers ........................................... 54

Figure 2.2-29 SA Airlink Domestic and International departures ............................................................... 54

Figure 2.2-30 SA Airlink Domestic and International passengers ............................................................... 55

Figure 2.2-31 Comair Domestic and International departures ................................................................... 56

Figure 2.2-32 Comair Domestic and International passenger numbers ..................................................... 56

Figure 2.2-33 Fleet size – South African Airlines ......................................................................................... 57

Figure 2.2-34 Air Tanzania Domestic and International departures ........................................................... 58

Figure 2.2-35 Air Tanzania Domestic and International Passengers .......................................................... 58

Figure 2.2-36 Air Tanzania Financial data ................................................................................................... 59

Figure 2.2-37 Fleet size – Tanzania airlines................................................................................................. 60

Figure 2.2-38 Zambia Airways Domestic and International departures ..................................................... 60

Figure 2.2-39 Zambezi Airlines Fleet ........................................................................................................... 61

Figure 2.2-40 Air Zimbabwe Domestic and International Departures ........................................................ 62

Figure 2.2-41 Air Zimbabwe Domestic and International passengers ........................................................ 62

Figure 2.2-42 Air Zimbabwe Financial Data ................................................................................................ 63

Figure 2.2-43 Airports with highest frequency: .......................................................................................... 65

Figure 2.2-44 Airports with mid to high frequency: ................................................................................... 66

Figure 2.2-45 International Airports with low frequency: .......................................................................... 67

Figure 2.2-46 Domestic Airports with low frequency: ................................................................................ 67

Figure 2.2-47 Fleet Size (2007) .................................................................................................................... 69

Figure 2.4-1 GDP per Capita Index .............................................................................................................. 88

Figure 2.4-2 Flow chart showing methodology for the section .................................................................. 92



Muller Associates

Figure 2.4-3 Showing how passengers’ benefits fit into the overall methodology .................................... 95

Figure 2.4-4 Assumed flight patterns between origins and destinations pre air transport liberalisation in

SADC ............................................................................................................................................................ 96

Figure 2.5-1 Forecasted Turnover ............................................................................................................. 108

Figure 2.5-2 Marginal turnover ................................................................................................................. 109

Figure 2.5-3 Growth in Seat Numbers ...................................................................................................... 110

Figure 2.5-4 Growth in Number of Flights per Week ................................................................................ 110

Figure 2.5-5 Passengers Time Saving Benefit ........................................................................................... 112

Figure 2.5-6 Marginal benefits from passengers’ time saving .................................................................. 113

Figure 2.5-7 Average ticket price per flight .............................................................................................. 114

Figure 2.5-8 Total distance flown per week (km) ..................................................................................... 115

Figure 2.5-9 Average distance flown per flight (km)................................................................................. 115

Figure 2.5-10 Total Costs to Airlines ......................................................................................................... 117

Figure 2.5-11 Cost of Flight Cancellation .................................................................................................. 118

Figure 2.5-12 Cost of Flight Diversions ..................................................................................................... 119

Figure 2.5-13 Cost of Accident Resulting in Fatality ................................................................................. 119

Figure 2.5-14 Cost of Accident Resulting in Minor Injury ......................................................................... 120

Figure 2.5-15 Cost of Accident Resulting in Major Injury ......................................................................... 120

Figure 2.5-16 Potential Turnover and Costs to Airlines ............................................................................ 121

Figure 2.5-17 Total and Direct Impact on GDP (2009 Rands) ................................................................... 123

Figure 2.5-18 Total and Direct Impact on Employment ............................................................................ 123

Figure 2.5-19 Cost of Noise Pollution ....................................................................................................... 128

Figure 2.5-20 Cost of Pollution ................................................................................................................. 129



Muller Associates

Figure 2.5-21 Cost of Security ................................................................................................................... 130

Figure 2.5-22 Total Indirect Costs ............................................................................................................. 131

Figure 2.5-23 Weekly cost navigational infrastructure per route ............................................................ 132

Figure 2.5-24 Airport navigational infrastructure ..................................................................................... 133

Figure 2.5-25 Airport Infrastructure Costs ................................................................................................ 135

Figure 2.6-1 Breakdown of Total Benefits incurred by the implementation of an air transport

liberalisation agreement in SADC ............................................................................................................. 138

Figure 2.6-2 Breakdown of Total Costs incurred by the implementation of an air transport liberalisation

agreement in SADC ................................................................................................................................... 140

Figure 2.6-3 The total impact of an air transport liberalisation agreement in SADC being implemented in

the Southern African Development community ....................................................................................... 141



Muller Associates

List of Boxes

Box 2.4-1 ..................................................................................................................................................... 87

Box 2.4-2 ..................................................................................................................................................... 87

Box 2.4-3 ..................................................................................................................................................... 90

Box 2.4-4 ..................................................................................................................................................... 91



Muller Associates

Appendix A – Signing States of the Chicago Convention 1944

Afghanistan Democratic Republic of the Congo

Lithuania Saint Vincent and the Grenadines

Albania Denmark Luxembourg Samoa

Algeria Djibouti Macedonia San Marino

Andorra Dominican Republic Madagascar Sao Tome and Principe

Angola Ecuador Malawi Saudi Arabia

Antigua and Barbuda Egypt Malaysia Senegal

Argentina El Salvador Maldives Serbia

Armenia Equatorial Guinea Mali Seychelles

Australia Eritrea Malta Sierra Leone

Austria Estonia Marshall Islands Singapore

Azerbaijan Ethiopia Mauritania Slovakia

Bahamas Fiji Mauritius Slovenia

Bahrain Finland Mexico Solomon Islands

Bangladesh France Micronesia (Federated States of)

Somalia

Barbados Gabon Monaco South Africa

Belarus Gambia Mongolia Spain

Belgium Georgia Montenegro Sri Lanka

Belize Germany Morocco Sudan

Benin Ghana Mozambique Suriname

Bhutan Greece Myanmar Swaziland

Bolivia Grenada Namibia Sweden

Bosnia and Herzegovina Guatemala Nauru Switzerland

Botswana Guinea-Bissau Nepal Syrian Arab Republic

Brazil Guinea Guyana Netherlands Tajikistan

Brunei Haiti Honduras New Zealand Thailand

Darussalam Hungary Iceland Nicaragua Timor-Leste

Bulgaria India Nigeria Togo

Burkina Faso Indonesia Niger Tonga

Burundi Iran (Islamic Republic of) Norway Trinidad and Tobago

Cambodia Iraq Oman Tunisia

Cameroon Ireland Pakistan Turkey

Canada Israel Palau Turkmenistan

Cape Verde Italy Panama Uganda

Central African Republic Jamaica Papua New Guinea Ukraine

Chad Japan Paraguay United Arab Emirates

Chile Jordan People's Republic of Korea United Kingdom

China Kazakhstan Peru United Republic of Tanzania

Colombia Kenya Philippines United States

Comoros Kiribati Poland Uruguay

Congo Kuwait Portugal Uzbekistan

Cook Islands Kyrgyzstan Qatar Republic of Vanuatu

Costa Rica Lao People's Korea Republic of Moldova Venezuela

Croatia Democratic Republic Latvia Romania Viet Nam

Cuba Lebanon Russian Federation Yemen

Cyprus Lesotho Rwanda Zambia

Czech Republic Liberia Saint Kitts and Nevis Zimbabwe

Côte d'Ivoire Democratic Libyan Arab Jamahiriya Saint Lucia



Muller Associates

Appendix B – United States Air transportation liberalisation Partners

and status of the agreement

Partner Application Date Concluded

All-cargo 7th air freedom

Albania In Force 9/24/2003 Yes

Armenia C&R 8/7/2010 Yes

Aruba In Force 9/18/1997 Yes

Australia C&R 2/14/2008 Yes

Austria In Force 6/14/1995

Bahrain In Force 5/24/1999 Yes

Belgium Provisional 3/1/1995

Benin N/A 11/28/2000 Yes[1]

Bosnia and Herzegovina In Force 11/22/2005 Yes

Brunei In Force 6/20/1997 Yes

Bulgaria Provisional 3/30/08

4/30/2007 Yes

Burkina Faso In Force 2/9/2000 Yes1

Cameroon In Force 2/16/2006 Yes1

Canada In Force 7/12/2003 Yes

Cape Verde In Force 6/21/2002 Yes1

Chad Provisional 5/31/2006 Yes1

Chile In Force 10/28/1997 Yes

Cook Islands In Force 2/28/2006 Yes

Costa Rica In Force 5/8/1997

Croatia N/A 3/13/2008 Yes

Cyprus Provisional 3/30/08

4/30/2007 Yes

Czech Republic In Force 12/8/1995 Yes

Denmark In Force 4/26/1995

El Salvador In Force 5/8/1997 Yes

Estonia Provisional 3/30/08

4/30/2007 Yes

Ethiopia Provisional 5/17/2005 Yes

Finland In Force 3/24/1995

France In Force 10/19/2001 Yes

Gabon In Force 5/26/2004 Yes1

Gambia In Force 5/2/2000 Yes1

Georgia In Force 7/6/2012 Yes

Germany Provisional 2/29/1996 Yes

Ghana In Force 3/16/2000 Yes1

Greece Provisional 3/30/08

4/30/2007 Yes

Guatemala In Force 5/8/1997 Yes

Honduras Provisional 5/8/1997 Yes

Hungary Provisional 3/30/08

4/30/2007 Yes

Iceland In Force 6/14/1995 Yes

India In Force 1/15/2005 Yes

Indonesia C&R 7/26/2004 Yes



Muller Associates

Ireland Provisional 3/30/08

4/30/2007 Yes

Italy C&R 11/11/1998

Jamaica In Force 10/30/2008

Jordan In Force 11/10/1996

Kenya C&R 5/30/08 --[1]

Korea In Force 4/23/1998

Kuwait In Force 5/27/2007 Yes

Laos C&R 8/3/2010 Yes

Latvia Provisional 3/30/08

4/30/2007 Yes

Liberia In Force 2/15/2007 Yes

Lithuania Provisional 3/30/08

4/30/2007 Yes

Luxembourg In Force 6/6/1995 Yes

Madagascar Provisional 4/10/2003 Yes1

Malaysia In Force 6/21/1997 Yes

Maldives In Force 5/5/2005 Yes

Mali In Force 10/17/2005 Yes1

Malta In Force 10/12/2000 Yes

Morocco In Force 10/5/2000 Yes

Namibia C&R 2/4/2000 1

Netherland Antilles In Force 7/14/1998 Yes

Netherlands In Force 10/14/92

New Zealand In Force 5/29/1997 Yes

Nicaragua In Force 5/8/1997 Chart Only

Nigeria Provisional 8/26/2000 Yes1

Norway In Force 4/26/1995

Oman C&R 9/16/2001 Yes

Pakistan In Force 4/29/1999 Yes

Panama In Force 5/8/1997 Yes

Paraguay In Force 5/2/2005 Yes

Peru In Force 6/10/1998 Yes

Poland In Force 5/31/2001 Yes

Portugal In Force 12/22/1999 Yes

Qatar Provisional 1/3/2010 Yes

Romania In Force 7/15/1998

Rwanda N/A 10/11/2000 Yes1

Samoa In Force 2/4/2007 Yes

Senegal C&R 12/15/2000 Yes1

Singapore In Force 1/22/1997 Yes

Slovak Republic In Force 1/7/2000 Yes

Slovenia Provisional 3/30/08

4/30/2007 Yes

Spain Provisional 4/30/2007 Yes



Muller Associates

3/30/08

Sri Lanka In Force 1/1/2011

Sweden In Force 4/26/1995

Switzerland In Force 6/15/1995

Taiwan In Force 2/28/1997

Tanzania Provisional 11/3/1999 Yes[2]

Thailand In Force 9/19/2005 Yes

Tonga In Force 9/19/2003 Yes

Turkey In Force 3/22/2000

U.A.E. In Force 4/13/1999 Yes

Uganda C&R 2/4/2006 Yes1

United Kingdom Provisional 3/30/08

4/30/2007 Yes

Uruguay Provisional 10/20/2004 Yes

Uzbekistan In Force 2/27/1998 Yes

Source: http://www.state.gov/e/eeb/rls/othr/ata/114805.htm, accessed 17/07/2009

http://www.state.gov/e/eeb/rls/othr/ata/114805.htm



Appendix C – State ownership for international flag carriers

Country Airline Designated State-owned

Afghanistan Ariana Afghan Airlines Yes Majority

Albania Albanian Airlines Yes Joint-Venture

Andorra AeroKing Andorra Yes Joint-Venture

Algeria Air Algérie Yes Majority[1]

Angola TAAG Angola Airlines Yes Full1

Åland Islands Air Åland

Argentina Aerolíneas Argentinas Yes Full

Armenia Armavia Yes No

Australia Qantas Yes No

Austria Austrian Airlines Yes Minority (42.75%)

Azerbaijan Azerbaijan Airlines Yes Full

Bahamas Bahamasair Yes Full

Bahrain Gulf Air Yes Full

Bangladesh Biman Bangladesh Airlines Yes Full

Barbados LIAT No No

Belarus Belavia Yes Full

Belgium Brussels Airlines Yes No

Belize Maya Island Air No No

Benin Benin Golf Air Yes No1

Bhutan Drukair Yes Full

Bolivia AeroSur Yes Minority (48%)

Bosnia and Herzegovina B&H Airlines Yes Majority (51%)

Botswana Air Botswana Yes Full1

Brazil TAM Airlines Yes No

Brunei Royal Brunei Airlines Yes Full

Bulgaria Bulgaria Air Yes No

Hemus Air Yes No

Burkina Faso Air Burkina Yes Majority1

Burundi Air Burundi Yes Full1

Cambodia Royal Khmer Airlines Yes Full

Cameroon Cameroon Airlines Yes

Canada Air Canada Yes No (privatised in 1988)

Cape Verde TACV Cabo Verde Airlines Yes Full1

Cayman Islands Cayman Airways Yes

Chad Toumaï Air Tchad 1

Chile LAN Airlines No

China Air China Yes Majority

Colombia Avianca Yes No

Comoros Air Comores International



Republic of the Congo Trans Air Congo Full[2]

Democratic Republic of the Congo

Hewa Bora Airways Full1

Costa Rica Lacsa (now part of TACA)

Côte d'Ivoire Air Ivoire 1

Croatia Croatia Airlines Yes Majority

Cuba Cubana de Aviación Yes Full

Cyprus Cyprus Airways Yes Majority

Northern Cyprus Cyprus Turkish Airlines

Czech Republic Czech Airlines Yes Full

Denmark Scandinavian Airlines System Yes Joint-Venture

Djibouti Air Djibouti 1

Dominican Republic Air Dominicana Yes Minority (33%)

Ecuador TAME

Egypt EgyptAir Yes Full

El Salvador TACA

Equatorial Guinea Ecuato Guineana

Eritrea Eritrean Airlines Yes Full

Estonia Estonian Air Yes Minority

Ethiopia Ethiopian Airlines Yes Full1

Faroe Islands Atlantic Airways

Fiji Air Pacific

Finland Finnair Yes Majority

France Air France No Minority

French Guiana Air Guyane Yes

French Polynesia Air Tahiti Nui Yes

Gabon Gabon Airlines 1

Gambia Gambia International Airlines

Yes 1

Georgia Georgian Airways Yes

Guernsey Aurigny Air Services Yes Full

Germany Lufthansa Yes No

Ghana Ghana International Airlines Yes 1

Greece Olympic Airlines Yes Majority

Greenland Air Greenland Yes

Guadeloupe Air Caraïbes

Guam Continental Micronesia

Guatemala Aviateca (now part of TACA)

Guinea Air Guinee Express Yes

Guyana Caribbean Airlines No

Haiti Tortug' Air

Honduras TACA

Hong Kong Cathay Pacific Yes No

Hungary Malév Yes No

Iceland Icelandair Yes No



Indonesia Garuda Indonesia Yes Full

India Air India Yes Full

Indian Yes Full

Iran Iran Air Yes Full

Iraq Iraqi Airways Yes Full

Ireland Aer Lingus Yes Minority (28%)

Israel El Al Yes Minority (30%)

Italy Alitalia Yes No (Privatised in 2009)

Jamaica Air Jamaica Yes

Japan Japan Airlines Yes No

Jordan Royal Jordanian Airlines Yes

Kazakhstan Air Astana Yes 0.51

Kenya Kenya Airways Yes [3]

Kiribati Air Kiribati Yes

North Korea Air Koryo Yes Full

South Korea Korean Air Yes No

Kuwait Kuwait Airways Yes Full

Kyrgyzstan Kyrgyzstan Airlines Yes Majority

Laos Lao Airlines Yes Full

Latvia Air Baltic Yes Majority

Lebanon Middle East Airlines Full

Liberia Air Liberia Yes 1

Libya Libyan Arab Airlines Yes 1

Lithuania

Luxembourg Luxair Yes Minority

Macau Air Macau Yes No

Macedonia MAT Macedonian Airlines Yes No

Madagascar Air Madagascar Yes Majority1

Malawi Air Malawi Yes Full1

Malaysia Malaysia Airlines Yes Minority

Maldives Maldivian Yes Full

Mali Air Mali International Yes No

Malta Air Malta Yes Majority

Marshall Islands Air Marshall Islands Yes Full

Martinique Air Caraïbes Yes No

Mauritania Mauritania Airways Minority

Mauritius Air Mauritius Yes Minority1

Mexico Aeromexico

Mexicana Yes

Federated States of Micronesia

Continental Micronesia

Moldova Air Moldova Yes

Mongolia MIAT Mongolian Airlines Yes

Montenegro Montenegro Airlines Yes

Montserrat Air Montserrat



Morocco Royal Air Maroc Yes

Mozambique Linhas Aéreas de Moçambique

Yes Full[4]

Myanmar Myanma Airways Yes Yes

Namibia Air Namibia Yes Majority1

Nauru Our Airline Yes

Nepal Nepal Airlines Yes

Netherlands KLM Yes No

Netherlands Antilles Dutch Antilles Express

New Caledonia Aircalin

New Zealand Air New Zealand Yes Majority

Nicaragua NICA (now part of TACA) Yes

Nigeria Virgin Nigeria Airways Yes No1

Norway Scandinavian Airlines System Yes Minority

Oman Oman Air Yes Majority (82.4%)

Pakistan Pakistan International Airlines (PIA)

Yes Majority (87%)

Palestinian Authority Palestinian Airlines Full

Panama Copa Airlines Yes No

Papua New Guinea Air Niugini

Paraguay Regional Paraguaya Yes No

Peru Air Perú

Philippines Philippine Airlines Yes Joint-Venture

Poland LOT Polish Airlines Yes Majority (67.97%)

Portugal TAP Portugal Yes Full

Qatar Qatar Airways Yes

Republic of China China Airlines[8] No Majority (54%)

Réunion Air Austral

Romania TAROM Yes Majority (95%)

Russia Rossiya Yes Full

Aeroflot Yes Majority (51%)

Rwanda Rwandair Express Yes 1

Samoa Polynesian Blue

São Tomé and Príncipe STP Airways 1

Saudi Arabia Saudi Arabian Airlines Yes Full

Senegal Air Sénégal International Yes 1

Serbia Jat Airways Yes Full

Seychelles Air Seychelles Yes 1

Sierra Leone Sierra National Airlines Yes [5]

Singapore Singapore Airlines Yes Majority (54%)



Slovakia Air Slovakia

Slovenia Adria Airways

Solomon Islands Solomon Airlines Yes

Somalia Somali Airlines[10] Yes

South Africa South African Airways Yes Full1

Spain Iberia Yes Minority (5%)

Sri Lanka SriLankan Airlines Yes

Sudan Sudan Airways Yes 1

Suriname Surinam Airways Yes

Sweden Scandinavian Airlines System Yes Joint-Venture

Swaziland Royal Swazi National Airways

1

Switzerland Swiss International Air Lines [12]

Yes No

Syria Syrian Air Yes Full

Tajikistan Tajik Air Yes

Tanzania Air Tanzania Yes

Thailand Thai Airways International Yes Majority (53%)

Togo Air Togo Yes

Tonga

Trinidad and Tobago Caribbean Airlines Yes Full

Tunisia Tunisair Yes

Turkey Turkish Airlines Yes Majority

Turkmenistan Turkmenistan Airlines Yes

Turks and Caicos Islands Air Turks and Caicos Yes

Uganda Air Uganda Yes 1

Ukraine Ukraine International Airlines

Yes Majority

United Arab Emirates Etihad Airways Yes Yes

Emirates Yes Yes

United Kingdom British Airways Yes No (Privatised in 1987)

United States N/A N/A N/A

Uruguay PLUNA Yes Minority (25%)

Uzbekistan Uzbekistan Airways Yes Majority

Vanuatu Air Vanuatu Yes

Venezuela Conviasa Yes Full

Vietnam Vietnam Airlines Yes Full

Yemen Yemenia Yes

Zambia Zambian Airways Yes 1

Zimbabwe Air Zimbabwe Yes 1



Appendix D – Spider Diagram

Impact of YD (SADC)

Direct Impacts

Airlines

Benefits

New Routes

Expansion on existing routes

Costs

Increase in cancellations

Increase in diversions

Increase in minor/major

injury

Increase in fatalities

Passengers Benefits

Reduction in time travelled

Reduction in airfares

Indirect Impacts

Tourism Impacts Benefits

Direct impact on GDP

Total impact on GDP

Security Cost

International security

personnel

Domestic security personnel

Pollution CostIncreased fuel

burn

Noise Pollution Cost Increased flights



Appendix E – Questionnaires

Air transportation liberalisation Questionnaire for Southern African Airlines

Graham Muller Associates is an economic consultancy who has been appointed by the South African Department of Transport to measure the impacts of a Yamoussoukro Decision (Air transportation liberalisation Aviation Agreement) within the Southern African Development Community (SADC) region. In order for the impacts to be measured as accurately as possible it is essential that we gather information from airlines, airports and other aviation industry stakeholders within the Southern Africa region. We therefore implore that your company/organisation takes part in this survey and complete the questionnaire that follows.

The following questionnaire has been compiled in conjunction with the South African Department of Transport. This questionnaire hopes to determine three things:

1. Determine the understanding that airlines within Southern Africa have of the Yamoussoukro Decision (an African aviation agreement from 1999)

2. Determine the information about all the current routes flown by airlines in Southern Africa 3. Determine the effects of an air transportation liberalisation agreement among the SADC

countries.

It would be greatly appreciated if you could take 20 minute to complete this questionnaire and return it to Graham Muller Associates (no later than a week from receiving the questionnaire, please). Answers are to be completed in the boxes that follow the questions.

Please NOTE that answer boxes will expand in size as you type your answers.

1. Please complete the following information:

Company/Organisation

Country of airport

Name

Position held

Email address

Contact number



Date completed

2. What type of airline are you? Please tick √ the correct box and explain where necessary (Tick

can be cut and pasted).

TICK BRIEFLY EXPLAIN

National flag carrier

Low cost carrier Domestic

International

High end (luxury) carrier

Domestic

International

Freight Carrier Domestic

International

Chartered Carrier

Franchise Who are you franchised from?

Code Sharing Who are code sharing partners? Both domestic and international?

Alliance Who are your alliance partners? Both domestic and international?

Block Space Who do you have block space agreements with? Both domestic and international?

a. If your airline does not fall within the above categories please explain?

b. Very briefly explain the functions of your company/organisation and how it fits into the

aviation industry within the Southern African Region?

3. What was the reported annual turnover of your business at the end of your last financial year? (Please specify the currency)



4. Please √ tick the correct box and explain where necessary?

QUESTION TICK ANSWER IF TICKED BRIEFLY EXPLAIN

a. Has your airline been subsidised by government in the last 5 years?

What was the subsidy you received in proportion to your turnover?

b. Is your airline wholly or partly owned by government?

What is the percentage of government ownership?

c. Is your airline privately owned?

Please tick the structure of private ownership for your airline

Sole proprietorship

A partnership

Close Corporation

Company

Non-profit

d. Is your airline owned by a FOREIGN government?

What is the percentage of foreign governments’ ownership?

e. Is your airline privately owned by FOREIGN owners or shareholders?


Sole proprietorship

A partnership

Close Corporation

Company

Non-profit



5. Please ONLY answer this question if there is more than one shareholder. If the ownership of your airport(s) is split between various shareholders please could you show the percentage split of ownership by the four categories listed below?

Yes: No:

6. Are you familiar with air transportation liberalisation agreements in regions or between countries? Please tick as appropriate:

Yes: No:

7. Are you familiar with the Yamoussoukro Decision (an African air transportation liberalisation aviation industry agreement)? Please tick as appropriate:

Yes: No:

If your answer to either question 6 or 7 is yes, please answer questions 7a – 7h. These questions relate directly to the Yamoussoukro Decision, which looks to establish an air transportation liberalisation agreement between African countries for African airlines. Otherwise if you’ve answered “ NO” for both questions 6 and 7 please continue to question 8:

a. How do you rate the agreement reached with the Yamoussoukro Decision and why? Please tick as appropriate:

Very poor

Why?

Poor

Fair

Good

Very good



OWNERS Eg. %

Domestic Government 33%

Foreign Government 0%

Domestic Private Ownership 50%

Foreign Private Ownership 17%

b. How do you rate the implementation of the Yamoussoukro Decision thus far and why? Please tick as appropriate:

Very poor

Why?

Poor

Fair

Good

Very good



c. What bottlenecks are hindering the full implementation of the Yamoussoukro decision? Please tick as appropriate



Lack of SACD commitment to YD

OTHER PLEASE SPECIFY BELOW:

National flag carriers disapproval of YD

Lack of competition law regionally

Lack of competition law within your country

Corruption

Poor legislation

Political instability in other African countries


d. What role should governments be playing to successfully implement the Yamoussoukro Decision or an air transportation liberalisation agreement between African countries specifically for African airlines?

e. If the Yamoussoukro Decision were fully implemented what would the impacts be on African countries partaking in the decision?



f. How do you see the Yamoussoukro Decision impacting on your company?

i. Frequency of flights

ii. Capacity (number of seats on offer)

iii. Pricing

iv. Volume of freight business

v. No. of competitors on each route

vi. Your market share on each route

a. Which airlines would MOST/LEAST benefit from the implementation of the Yamoussoukro Decision (YD)? Why?

AIRLINES EXPLAIN

Most benefit from YD

Least benefit from YD

b. In your opinion, would the Yamoussoukro Decision or a Southern African air transportation liberalisation agreement be restricted by infrastructure constraints such as:

(Please answer yes or no and give a reason for ‘yes’ answers)

YES / NO: EXPLAIN WHERE ‘YES’:

Air traffic control

Airport runway capacity (slots)


Baggage handling



Security


Other (specify):



8. Could you please list the following airline fleet information in the table below: a. What aircrafts does your fleet consist of? b. What runway lengths are required for the takeoff and landing of each aeroplane model,

at various capacities? (eg. 100% full, 90% full or 80% full)

AEROPLANE MODEL NUMBER IN FLEET

RUNWAY LENGTH (ft)

CAPACITY

100% 90% 80%

Eg. Airbus A320 3 TAKE OFF 6600 5400 4300

LANDING 4800 4225 3650

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF



LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

9. What other airport requirements, besides runway length, does your airline require to fly to a destination both domestically and internationally? (Please tick as appropriate)

TICK

Air traffic control

Baggage Handling

Customs facilities

Airport Security

Other (please

specify)



10. How many passengers were served in the various markets from 2004 to 2008?

2004 2005 2006 2007 2008

Domestic

SADC Region

Africa

Rest of the world

TOTAL

11. How much freight (in tons) did your airline handle in the various markets from 2004 to 2008?

2004 2005 2006 2007 2008

Domestic

SADC Region

Africa

Rest of the world

TOTAL

12. How many flights operated in the various markets from 2004 to 2008?

2004 2005 2006 2007 2008

Domestic

SADC Region

Africa

Rest of the world

TOTAL



13. What routes do you currently cover both domestically and internationally? (please answer this in table below)

BOXES WILL EXPAND AS YOU WRTIE YOUR ANSWERS IN THEM

a. On these various routes please detail the: i. Airport code of origin and destination?

ii. Frequency of flights? iii. Capacity (number of seats on offer)? iv. Pricing? v. Demand (take up of capacity)?

vi. Volume of freight business? vii. No. of competitors on each route?

viii. Your market share – has this increased or decreased? ix. If this route operates under an air transportation liberalisation agreement? x. How would this route change under an air transportation liberalisation agreement?

PLEASE FILL IN THE DESTINATIONS IN THE BLOCKS TO THE RIGHT: O

rigi

n

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

i. Airport Code

ii. No. of flights per week

iii. Weekly Capacity (number of seats on offer)

iv. Pricing

v. Demand (take up of capacity)

vi. Volume of freight business

vii. No. of competitors on route



viii. Current market share of route

viii. Has market share increased or decreased?

Please answer Increase or decrease

ix. Does route operate under air transportation liberalisation?

Please answer YES or NO

x. Change under air transportation liberalisation agreement

Eg. Would fly 10 more flights on this route per month


rigi

n

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

i. Airport Code



iv. Pricing













rigi

n

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

i. Airport Code



iv. Pricing













rigi

n

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

i. Airport Code





iv. Pricing













rigi

n

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

i. Airport Code



iv. Pricing














The following question looks at the possible changes in the aviation industry if the Southern African Development Community (SADC) had a regional air transportation liberalisation agreement. This would give SADC airlines the option of flying to ANY airport within the SADC region an unlimited amount of times.

14. If the SADC had a comprehensive air transportation liberalisation agreement, how would this impact your airline ? (How would it change?) Please list where appropriate the changed staff, aircraft and other related requirements:

b. Would you fly any new routes if there were a SADC air transportation liberalisation agreement? What frequency of flights would you fly on these new routes, as well as the estimated capacity for freight and passengers?

Please add rows if needed

NEW ROUTE FREQUENCY OF FLIGHTS

PASSENGER CAPACITY FREIGHT CAPACITY PRICE



c. What would be the changes in the current routes you fly if there were a SADC air transportation liberalisation agreement? Please list the change in frequency, as well as the estimated capacity for freight and passengers? Please add rows if needed

CHANGE TO CURRENT ROUTES

FREQUENCY OF FLIGHTS

PASSENGER CAPACITY

FREIGHT CAPACITY PRICE



Air transportation liberalisation Questionnaire for Southern African Airlines


The following questionnaire has been compiled in conjunction with the South African Department of Transport. This questionnaire hopes to determine three things:

1. Determine the understanding that airlines within Southern Africa have of the Yamoussoukro Decision (an African aviation agreement from 1999)

2. Determine the information about all the current routes flown by airlines in Southern Africa 3. Determine the effects of an air transportation liberalisation agreement among the SADC

countries.





Country of airport

Name

Position held

Email address

Contact number



Date completed

5. What type of airline are you? Please tick √ the correct box and explain where necessary (Tick

can be cut and pasted).

TICK BRIEFLY EXPLAIN

National flag carrier

Low cost carrier Domestic

International

High end (luxury) carrier

Domestic

International

Freight Carrier Domestic

International

Chartered Carrier

Franchise Who are you franchised from?

Code Sharing Who are code sharing partners? Both domestic and international?

Alliance Who are your alliance partners? Both domestic and international?

Block Space Who do you have block space agreements with? Both domestic and international?

c. If your airline does not fall within the above categories please explain?

d. Very briefly explain the functions of your company/organisation and how it fits into the aviation industry within the Southern African Region?




7. Please √ tick the correct box and explain where necessary?

QUESTION TICK ANSWER IF TICKED BRIEFLY EXPLAIN

a. Has your airline been subsidised by government in the last 5 years?


b. Is your airline wholly or partly owned by government?


c. Is your airline privately owned?


Sole proprietorship

A partnership

Close Corporation

Company

Non-profit

d. Is your airline owned by a FOREIGN government?


e. Is your airline privately owned by FOREIGN owners or shareholders?


Sole proprietorship

A partnership

Close Corporation

Company

Non-profit



8. Please ONLY answer this question if there is more than one shareholder. If the ownership of your airport(s) is split between various shareholders please could you show the percentage split of ownership by the four categories listed below?

OWNERS Eg. %





9. Are you familiar with the air transportation liberalisation agreements in regions or between countries? Please tick as appropriate:

Yes: No:


Yes: No:


g. How do you rate the agreement reached with the Yamoussoukro Decision and why? Please tick as appropriate:

Very poor

Why?

Poor

Fair

Good

Very good



h. How do you rate the implementation of the Yamoussoukro Decision thus far and why? Please tick as appropriate:

Very poor

Why?

Poor

Fair

Good

Very good

i. What bottlenecks are hindering the full implementation of the Yamoussoukro decision? Please

tick as appropriate








Corruption

Poor legislation



j. What role should governments be playing to successfully implement the Yamoussoukro Decision

or an air transportation liberalisation agreement between African countries specifically for African airlines?



k. If the Yamoussoukro Decision were fully implemented what would the impacts be on African countries partaking in the decision?

l. How do you see the Yamoussoukro Decision impacting on your company?

i. Frequency of flights

ii. Capacity (number of seats on offer)

iii. Pricing

iv. Volume of freight business

v. No. of competitors on each route

vi. Your market share on each route

a. Which airlines would MOST/LEAST benefit from the implementation of the Yamoussoukro Decision (YD)? Why?

AIRLINES EXPLAIN



b. In your opinion, would the Yamoussoukro Decision or a Southern African air transportation liberalisation agreement be restricted by infrastructure constraints such as:



Air traffic control





Baggage handling

Security


Other (specify):



11. Could you please list the following airline fleet information in the table below: c. What aircrafts does your fleet consist of? d. What runway lengths are required for the takeoff and landing of each aeroplane model,

at various capacities? (eg. 100% full, 90% full or 80% full)

AEROPLANE MODEL NUMBER IN FLEET

RUNWAY LENGTH (ft)

CAPACITY

100% 90% 80%

Eg. Airbus A320 3 TAKE OFF 6600 5400 4300

LANDING 4800 4225 3650

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING

TAKE OFF

LANDING



12. What other airport requirements, besides runway length, does your airline require to fly to a destination both domestically and internationally? (Please tick as appropriate)

TICK

Air traffic control

Baggage Handling

Customs facilities

Airport Security

Other (please

specify)

13. How many passengers were served in the various markets from 2004 to 2008?

2004 2005 2006 2007 2008

Domestic

SADC Region

Africa

Rest of the world

TOTAL

14. How much freight (in tons) did your airline handle in the various markets from 2004 to 2008?

2004 2005 2006 2007 2008

Domestic

SADC Region

Africa

Rest of the world

TOTAL



15. How many flights operated in the various markets from 2004 to 2008?

2004 2005 2006 2007 2008

Domestic

SADC Region

Africa

Rest of the world

TOTAL



16. What routes do you currently cover both domestically and internationally? (please answer this in table below)

BOXES WILL EXPAND AS YOU WRTIE YOUR ANSWERS IN THEM

d. On these various routes please detail the: i. Airport code of origin and destination?

ii. Frequency of flights? iii. Capacity (number of seats on offer)? iv. Pricing? v. Demand (take up of capacity)?

vi. Volume of freight business? vii. No. of competitors on each route?

viii. Your market share – has this increased or decreased? ix. If this route operates under an air transportation liberalisation agreement? x. How would this route change under an air transportation liberalisation agreement?


rigi

n

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

i. Airport Code



iv. Pricing












Eg. Would fly 10 more flights on this route per month


rigi

n

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

i. Airport Code



iv. Pricing













rigi

n

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

i. Airport Code



iv. Pricing













rigi

n

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

i. Airport Code





iv. Pricing













rigi

n

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

Ori

gin

De

stin

atio

n

i. Airport Code



iv. Pricing















17. If the SADC had a comprehensive air transportation liberalisation agreement, how would this impact your airline ? (How would it change?) Please list where appropriate the changed staff, aircraft and other related requirements:

e. Would you fly any new routes if there were a SADC air transportation liberalisation agreement? What frequency of flights would you fly on these new routes, as well as the estimated capacity for freight and passengers?

Please add rows if needed

NEW ROUTE FREQUENCY OF FLIGHTS

PASSENGER CAPACITY FREIGHT CAPACITY PRICE

f. What would be the changes in the current routes you fly if there were a SADC air transportation liberalisation agreement? Please list the change in frequency, as well as the estimated capacity for freight and passengers? Please add rows if needed

CHANGE TO CURRENT ROUTES

FREQUENCY OF FLIGHTS

PASSENGER CAPACITY

FREIGHT CAPACITY PRICE



Air transportation liberalisation Questionnaire for other Southern Africa

Aviation Industry Stakeholders


The following questionnaire has been compiled in conjunction with the South African Department of Transport. This questionnaire hopes to determine two things:

1. Determine the understanding that your company/organisation has of the Yamoussoukro Decision (an African aviation agreement from 1999)

2. Determine the effects of an air transportation liberalisation agreement among the SADC countries will have on your company/organisation.





Country

Name

Position held

Email address

Contact number

Date completed




5. Please list your main sources of income?



6. Please tick √ the correct box and explain where necessary? (Tick can be cut and pasted).

QUESTION TICK ANSWER IF TICKED BRIEFLY EXPLAIN (if necessary)

a. Has your company been subsidised by government in the last 5 years?


b. Is your company wholly or partly owned by government?


c. Is your company privately owned?

Please tick the structure of private ownership for your company

Sole proprietorship

A partnership

Close Corporation

Company

Non-profit

d. Is your company owned by a FOREIGN government?


e. Is your company privately owned by FOREIGN owners or shareholders?

Please tick the structure of private ownership for your company

Sole proprietorship

A partnership

Close Corporation

Company

Non-profit



7. Please ONLY answer this question if there is more than one shareholder. If the ownership of your business(es) is split between various shareholders please could you show the percentage split of ownership by the four categories listed below?

OWNERS Eg. %







8. Are you familiar with air transportation liberalisation agreements in regions or between countries? Please tick as appropriate:

Yes: No:


Yes: No:


m. How do you rate the agreement reached with the Yamoussoukro Decision and why? Please tick as appropriate:

Very poor

Why?

Poor

Fair

Good

Very good

n. How do you rate the implementation of the Yamoussoukro Decision thus far and why? Please tick as appropriate:

Very poor

Why?

Poor

Fair

Good

Very good

o. What bottlenecks are hindering the full implementation of the Yamoussoukro decision? Please

tick as appropriate










Corruption

Poor legislation



p. What role should governments be playing to successfully implement the Yamoussoukro Decision or an air transportation liberalisation agreement between African countries specifically for African airlines?

q. If the Yamoussoukro Decision were fully implemented what would the impacts be on African countries partaking in the decision?

r. How do you see the Yamoussoukro Decision impacting on your company?

Please explain in detail in the space below, which will expand as you type.



s. Which companies/organistions would MOST/LEAST benefit from the implementation of the Yamoussoukro Decision (YD)? Why?

COMPANIES/ORGANISATIONS EXPLAIN



t. In your opinion, would the Yamoussoukro Decision or a Southern African air transportation liberalisation agreement be restricted by infrastructure constraints such as:



Air traffic control



Baggage handling

Security


Other (specify):


10. If the ‘Southern African Development Community’ (SADC) had a comprehensive air transportation liberalisation agreement, how would your company change?

Please answer in detail, specify staff, infrastructure and capital changes:



Appendix F – Destinations within SADC

City COUNTRY POPULATION

Luanda Angola 3,060,137

Huambo Angola 220,835

Lobito Angola 174,785

Benguela Angola 171,096

Namibe Angola 169,061

Kuito Angola 112,834

Lubango Angola 96,424

Malanje Angola 91,082

M'banza-Kongo Angola 85,993

Uige Angola 62,332

Cabinda Angola 56,990

Saurimo Angola 52,410

Lucapa Angola 45,668

Chissamba Angola 40,580

Waku-Kungo Angola 37,908

Sumbe Angola 32,438

Caxito Angola 31,293

Soyo Angola 30,021

Menongue Angola 29,512

Caala Angola 29,131

Caluquembe Angola 28,368

N'dalatando Angola 28,368

Longonjo Angola 25,060

Catabola Angola 23,152

Catumbela Angola 20,989

Luena Angola 20,481

Luau Angola 17,428

Camacupa Angola 16,919

Catchiungo Angola 16,156

Leua Angola 15,901

N'zeto Angola 15,138

Camabatela Angola 14,756

Cazaje Angola 14,375

Lumeje Angola 14,247

Ondjiva Angola 12,721

Caconda Angola 10,304

Gaborone Botswana 191,223

Francistown Botswana 85,360

Molepolole Botswana 56,141

Selibe Phikwe Botswana 51,255

Maun Botswana 45,027

Serowe Botswana 43,686

Kanye Botswana 41,770

Mahalapye Botswana 40,812

Mochudi Botswana 38,034

Mogoditshane Botswana 33,723

Lobatse Botswana 30,561

Palapye Botswana 27,016

Tlokweng Botswana 21,747

Ramotswa Botswana 21,268



Thamaga Botswana 18,586

Moshupa Botswana 17,436

Tonota Botswana 16,095

Jwaneng Botswana 15,616

Letlhakane Botswana 15,424

Bobonong Botswana 15,041

Tutume Botswana 14,083

Mmadinare Botswana 11,209

Gabane Botswana 10,730

Ghanzi Botswana 10,251

Orapa Botswana 9,389

Kasane Botswana 7,856

Shoshong Botswana 7,664

Tsabong Botswana 6,802

Gumare Botswana 6,227

Letlhakeng Botswana 6,227

Lerala Botswana 5,940

Kopong Botswana 5,748

Maitengwe Botswana 5,461

Otse Botswana 5,365

Mmankgodi Botswana 5,173

Molapowabojang Botswana 4,982

Tsienyane Botswana 4,694

Mmathethe Botswana 4,503

Shakawe Botswana 4,503

Tati Botswana 4,503

Tumasera Seleka Botswana 4,407

Lotlhakane Botswana 4,311

Nata Botswana 4,311

Sefhare Botswana 4,311

Gweta Botswana 4,215

Metsimotlhaba Botswana 4,215

Lentsweletau Botswana 4,120

Mathangwane Botswana 4,120

Bokaa Botswana 3,928

Hukuntsi Botswana 3,928

Sefophe Botswana 3,928

Kang Botswana 3,832

Mmopane Botswana 3,641

Nkange Botswana 3,641

Ramokgonami Botswana 3,641

Mogoditshane Botswana Defence Force Botswana 3,545

Oodi Botswana 3,545

Tsetsebjwe Botswana 3,545

Kumakwane Botswana 3,257

Manyana Botswana 3,257

Maunatlala Botswana 3,257

Masunga Botswana 3,161

Mopipi Botswana 3,161

Water Util-Dukwe Refugee Camp Botswana 3,161

Borolong Botswana 3,066

Pitsane Botswana 3,066

Chadibe Botswana 2,970



Good Hope Botswana 2,970

Sowa Botswana 2,970

Sebina Botswana 2,874

Digawana Botswana 2,778

Morwa Botswana 2,778

Radisele Botswana 2,778

Etsha Botswana 2,682

Mandunyane Botswana 2,682

Moiyabana Botswana 2,682

Ranaka Botswana 2,682

Thebephatshwa Botswana 2,682

Lecheng Botswana 2,587

Ramotswa Station-Taung Botswana 2,587

Senete Botswana 2,587

Modipane Botswana 2,491

Rasesa Botswana 2,491

Malolwane Botswana 2,395

Mookane Botswana 2,395

Thabala Botswana 2,395

Kalamare Botswana 2,299

Lesetlhane Botswana 2,299

Ratholo Botswana 2,299

Serule Botswana 2,299

Lesenepole Botswana 2,203

Shashe Mooke Botswana 2,203

Khakhea Botswana 2,108

Machaneng Botswana 2,108

Mmathubudukwane Botswana 2,108

Mogobane Botswana 2,108

Mogorosi Botswana 2,108

Paje Botswana 2,108

Shashe-Semotswane Botswana 2,108

Sojwe Botswana 2,108

Etsha 13 Botswana 2,012

Nlakhwane Botswana 2,012

Werda Botswana 2,012

Charles Hill Botswana 1,916

Dukwi Botswana 1,916

Khudumelapye Botswana 1,916

Mathathane Botswana 1,916

Ditshegwane Botswana 1,820

Mabeleapudi Botswana 1,820

Mogapi Botswana 1,820

Mokobeng Botswana 1,820

Molalatau Botswana 1,820

Moroka Botswana 1,820

Mosolotshane Botswana 1,820

Nswazwi Botswana 1,820

Ntlhantlhe Botswana 1,820

Tobane Botswana 1,820

Kazungula Botswana 1,724

Kobojango Botswana 1,724

Lehututu Botswana 1,724



Mabutsane Botswana 1,724

Majwaneng Botswana 1,724

Matshelagabedi Botswana 1,724

Mosetse Botswana 1,724

Nshakashokwe Botswana 1,724

Salajwe Botswana 1,724

Seronga Botswana 1,724

Tsamaya Botswana 1,724

Mabule Botswana 1,629

Makwate Botswana 1,629

Mapoka Botswana 1,629

Marapong Botswana 1,629

Mmashoro Botswana 1,629

Nokaneng Botswana 1,629

Pandamatenga Botswana 1,629

Pitshane Molopo Botswana 1,629

Sikwane Botswana 1,629

Takatokwane Botswana 1,629

Xhumo Botswana 1,629

Artisia Botswana 1,533

Dagwi Botswana 1,533

Makopong Botswana 1,533

Morope Botswana 1,533

Motokwe Botswana 1,533

Ramokgwebana Botswana 1,533

Sehithwa Botswana 1,533

Sepopa Botswana 1,533

Sese Botswana 1,533

Tshesebe Botswana 1,533

Tshimoyapula Botswana 1,533

Zwenshambe Botswana 1,533

Gootau Botswana 1,437

Kgomokasitwa Botswana 1,437

Matsiloje Botswana 1,437

Mogapinyana Botswana 1,437

Moletemane Botswana 1,437

Moshopha Botswana 1,437

Ncojane Botswana 1,437

Nkoyaphiri Botswana 1,437

Senyawe Botswana 1,437

Themashanga Botswana 1,437

Tsootsha Botswana 1,437

Gaphatshwa Botswana 1,341

Kgagodi Botswana 1,341

Kudumatse Botswana 1,341

Lokgwabe Botswana 1,341

Makuta Botswana 1,341

Marobela Botswana 1,341

Matobo Botswana 1,341

Mohembo West Botswana 1,341

Mokoboxane Botswana 1,341

Moshaneng Botswana 1,341

Motlhabaneng Botswana 1,341



Nxamasere Botswana 1,341

Pilikwe Botswana 1,341

Seolwane Botswana 1,341

Sesung Botswana 1,341

Siviya Botswana 1,341

Topisi Botswana 1,341

Tsao Botswana 1,341

Kinshasa Democratic Republic Of Congo 5,874,688

Lubumbashi Democratic Republic Of Congo 984,609

Mbuji-Mayi Democratic Republic Of Congo 840,292

Kolwezi Democratic Republic Of Congo 745,638

Kananga Democratic Republic Of Congo 498,880

Kisangani Democratic Republic Of Congo 463,752

Likasi Democratic Republic Of Congo 343,056

Boma Democratic Republic Of Congo 324,886

Tshikapa Democratic Republic Of Congo 308,880

Bukavu Democratic Republic Of Congo 212,669

Matadi Democratic Republic Of Congo 203,670

Kikwit Democratic Republic Of Congo 202,200

Uvira Democratic Republic Of Congo 191,557

Mwene-Ditu Democratic Republic Of Congo 188,443

Mbandaka Democratic Republic Of Congo 187,751

Butembo Democratic Republic Of Congo 138,953

Goma Democratic Republic Of Congo 138,607

Isiro Democratic Republic Of Congo 124,504

Bunia Democratic Republic Of Congo 121,389

Gemena Democratic Republic Of Congo 111,266

Kindu Democratic Republic Of Congo 109,622

Bandundu Democratic Republic Of Congo 107,805

Ilebo Democratic Republic Of Congo 97,423

Kalemie Democratic Republic Of Congo 95,087

Beni Democratic Republic Of Congo 90,934

Gandajika Democratic Republic Of Congo 83,839

Bumba Democratic Republic Of Congo 79,426

Mbanza-Ngungu Democratic Republic Of Congo 78,648

Kipushi Democratic Republic Of Congo 75,792

Kamina Democratic Republic Of Congo 64,372

Lisala Democratic Republic Of Congo 63,939

Lodja Democratic Republic Of Congo 61,689

Binga Democratic Republic Of Congo 54,768

Kabinda Democratic Republic Of Congo 53,297

Kasongo Democratic Republic Of Congo 46,548

Kalima Democratic Republic Of Congo 46,462

Mweka Democratic Republic Of Congo 46,116

Gbadolite Democratic Republic Of Congo 46,029

Bulungu Democratic Republic Of Congo 44,126

Buta Democratic Republic Of Congo 41,876

Basoko Democratic Republic Of Congo 40,059

Lusambo Democratic Republic Of Congo 37,464

Nioki Democratic Republic Of Congo 37,117

Inongo Democratic Republic Of Congo 36,598

Tshela Democratic Republic Of Congo 35,387

Mangai Democratic Republic Of Congo 33,916



Kenge Democratic Republic Of Congo 33,743

Bukama Democratic Republic Of Congo 33,397

Yangambi Democratic Republic Of Congo 32,618

Manono Democratic Republic Of Congo 32,359

Aketi Democratic Republic Of Congo 32,272

Luebo Democratic Republic Of Congo 32,013

Kambove Democratic Republic Of Congo 31,580

Lubao Democratic Republic Of Congo 30,196

Mushie Democratic Republic Of Congo 30,196

Kabare Democratic Republic Of Congo 29,850

Boende Democratic Republic Of Congo 29,244

Kampene Democratic Republic Of Congo 28,033

Yakoma Democratic Republic Of Congo 27,773

Kongolo Democratic Republic Of Congo 27,514

Yandongi Democratic Republic Of Congo 26,822

Simba Democratic Republic Of Congo 26,648

Titule Democratic Republic Of Congo 26,562

Kutu Democratic Republic Of Congo 26,475

Businga Democratic Republic Of Congo 26,389

Kabalo Democratic Republic Of Congo 25,697

Moba Democratic Republic Of Congo 25,697

Bolobo Democratic Republic Of Congo 25,437

Kasangulu Democratic Republic Of Congo 25,437

Kaniama Democratic Republic Of Congo 25,351

Libenge Democratic Republic Of Congo 24,658

Gwane Democratic Republic Of Congo 24,572

Watsa Democratic Republic Of Congo 22,495

Faradje Democratic Republic Of Congo 22,149

Demba Democratic Republic Of Congo 20,246

Basankusu Democratic Republic Of Congo 19,640

Shinkolobwe Democratic Republic Of Congo 19,640

Kasongo-Lunda Democratic Republic Of Congo 18,256

Idiofa Democratic Republic Of Congo 17,737

Tshilenge Democratic Republic Of Congo 17,650

Mobayi-Mbongo Democratic Republic Of Congo 17,218

Niangara Democratic Republic Of Congo 17,218

Bodalangi Democratic Republic Of Congo 16,439

Bondo Democratic Republic Of Congo 16,352

Kahemba Democratic Republic Of Congo 16,352

Kama Democratic Republic Of Congo 16,179

Itoko Democratic Republic Of Congo 16,006

Wamba Democratic Republic Of Congo 15,920

Yumbi Democratic Republic Of Congo 15,574

Dilolo Democratic Republic Of Congo 15,314

Katako-Kombe Democratic Republic Of Congo 15,228

Lubefu Democratic Republic Of Congo 15,141

Lusanga Democratic Republic Of Congo 15,141

Aba Democratic Republic Of Congo 14,968

Kole Democratic Republic Of Congo 14,622

Mambasa Democratic Republic Of Congo 14,622

Muanda Democratic Republic Of Congo 14,622

Kimpese Democratic Republic Of Congo 14,536

Tshofa Democratic Republic Of Congo 14,016



Bosobolo Democratic Republic Of Congo 13,238

Mongbwalu Democratic Republic Of Congo 13,065

Bafwasende Democratic Republic Of Congo 12,459

Kazumba Democratic Republic Of Congo 12,459

Kibombo Democratic Republic Of Congo 12,372

Nyunzu Democratic Republic Of Congo 12,372

Gungu Democratic Republic Of Congo 12,286

Makanza Democratic Republic Of Congo 12,199

Madimba Democratic Republic Of Congo 12,113

Kiri Democratic Republic Of Congo 11,940

Zongo Democratic Republic Of Congo 11,853

Ikela Democratic Republic Of Congo 11,680

Ubundu Democratic Republic Of Congo 10,296

Djugu Democratic Republic Of Congo 10,209

Poko Democratic Republic Of Congo 10,209

Banalia Democratic Republic Of Congo 10,036

Sakania Democratic Republic Of Congo 9,950

Le Marinel Democratic Republic Of Congo 8,739

Mwanza Democratic Republic Of Congo 8,479

Malemba-Nkulu Democratic Republic Of Congo 7,614

Lubudi Democratic Republic Of Congo 7,527

Mulongo Democratic Republic Of Congo 7,441

Kikondjo Democratic Republic Of Congo 7,354

Dibaya Democratic Republic Of Congo 4,153

Bongandanga Democratic Republic Of Congo 3,720

Maseru Lesotho 132,168

Mafeteng Lesotho 26,653

Maputsoa Lesotho 24,122

Teyateyaneng Lesotho 21,508

Hlotse Lesotho 17,712

Mohale's Hoek Lesotho 15,519

Quthing Lesotho 11,386

Butha Buthe Lesotho 7,928

Qacha's Nek Lesotho 6,241

Mokhotlong Lesotho 5,651

Thaba-Tseka Lesotho 4,723

Antananarivo Madagascar 1,161,056

Toamasina Madagascar 187,057

Antsirabe Madagascar 167,563

Fianarantsoa Madagascar 150,667

Mahajanga Madagascar 141,755

Toliary Madagascar 106,200

AntsiranìˆAna Madagascar 76,772

Antanifotsy Madagascar 66,561

Ambovombe Madagascar 64,704

Amparafaravola Madagascar 47,159

TaolanìˆAro Madagascar 43,724

Ambatondrazaka Madagascar 39,454

Soavinandriana Madagascar 38,061

Mananara Madagascar 37,690

Nosy Varika Madagascar 37,226

Mahanoro Madagascar 36,483

Soanierana Ivongo Madagascar 35,926



Morondava Madagascar 35,648

Manakara Madagascar 35,555

Faratsiho Madagascar 35,369

Amboasary Madagascar 34,998

Antalaha Madagascar 34,162

Vavatenina Madagascar 33,791

Ikongo Madagascar 32,491

Sambava Madagascar 31,563

Fandriana Madagascar 31,470

Ambanja Madagascar 30,635

Ambositra Madagascar 30,449

Betioky Madagascar 30,171

Manjakandriana Madagascar 29,985

Marovoay Madagascar 29,799

Tsihombe Madagascar 28,871

Ambalavao Madagascar 28,128

Betafo Madagascar 28,035

Mananjary Madagascar 27,757

Ambatolampy Madagascar 26,829

Moramanga Madagascar 26,736

Ambatofinandrahana Madagascar 26,086

Tsiroanomandidy Madagascar 25,529

Ankazoabo Madagascar 25,158

Ampanihy Madagascar 24,879

Farafangana Madagascar 24,786

Anosibe An'ala Madagascar 24,136

Marolambo Madagascar 23,951

Vangaindrano Madagascar 23,579

Vohibinany Madagascar 23,208

Belon'i Tsiribihina Madagascar 23,115

Antsirambazaha Madagascar 22,651

Beloha Madagascar 22,280

Maroantsetra Madagascar 21,816

Ambato Boina Madagascar 21,444

Sakaraha Madagascar 21,166

Andapa Madagascar 20,794

Arivonimamo Madagascar 20,702

Antsohihy Madagascar 20,330

Miandrivazo Madagascar 19,959

Vondrozo Madagascar 19,959

Fenoarivo Atsinanana Madagascar 19,216

Manandriana Madagascar 19,031

Fenoarivo Madagascar 18,474

Andilamena Madagascar 18,102

Beroroha Madagascar 18,010

Anjozorobe Madagascar 17,917

Ifanadiana Madagascar 17,545

Ihosy Madagascar 16,988

Bealanana Madagascar 16,153

Tsaratanana Madagascar 15,967

Ikalamavony Madagascar 15,596

Ankazobe Madagascar 14,853

Ambilobe Madagascar 14,668



Ambodifototra Madagascar 10,861

Andevoranto Madagascar 9,562

Blantyre Malawi 520,101

Lilongwe Malawi 474,232

Mzuzu Malawi 94,698

Zomba Malawi 69,729

Karonga Malawi 30,241

Mangochi Malawi 29,408

Kasungu Malawi 28,391

Salima Malawi 22,102

Nkhotakota Malawi 21,085

Nsanje Malawi 18,403

Liwonde Malawi 17,109

Dedza Malawi 16,554

Balaka Malawi 15,629

Rumphi Malawi 15,167

Mzimba Malawi 15,074

Mulanje Malawi 13,687

Mchinji Malawi 12,485

Mponela Malawi 10,820

Chilumba Malawi 10,728

Nkhata Bay Malawi 10,265

Luchenza Malawi 9,618

Monkey Bay Malawi 9,525

Mwanza Malawi 8,785

Ntcheu Malawi 8,785

Chitipa Malawi 7,768

Chikwawa Malawi 7,398

Ntchisi Malawi 5,826

Thyolo Malawi 5,826

Livingstonia Malawi 5,179

Dowa Malawi 4,901

Phalombe Malawi 2,774

Chipoka Malawi 2,404

Chiradzulu Malawi 1,665

Machinga Malawi 1,387

Port Louis Mauritius 140,310

Beau Bassin-Rose Hill Mauritius 108,164

Vascoas-Phoenix Mauritius 102,008

Curepipe Mauritius 78,070

Quatre Bornes Mauritius 74,748

Triolet Mauritius 21,594

Goodlands Mauritius 19,933

Bel Air Mauritius 17,295

Central Flacq Mauritius 16,708

Le Hochet Mauritius 16,611

Saint Pierre Mauritius 14,950

Mahebourg Mauritius 14,852

Baie Du Tombeau Mauritius 14,266

Bambous Mauritius 12,604

Rose Belle Mauritius 11,823

Chemin Grenier Mauritius 11,725

Surinam Mauritius 11,725



Grand Baie Mauritius 11,627

Pailles Mauritius 11,432

Plaine Magnien Mauritius 11,041

Riviere Du Rempart Mauritius 10,553

Terre Rouge Mauritius 10,455

New Grove Mauritius 10,064

Lalmatie Mauritius 9,673

Petit Raffray Mauritius 9,185

Riviere Des Anguilles Mauritius 8,892

Grand Bois Mauritius 8,208

Pointe Aux Piments Mauritius 8,208

Montagne Blanche Mauritius 7,914

Moka Mauritius 7,817

Beau Vallon Mauritius 7,719

L'escalier Mauritius 7,719

Pamplemousse Mauritius 7,719

Dagotiere Mauritius 7,426

Plaines Des Papayes Mauritius 7,328

Bon Accueil Mauritius 7,230

Nouvelle France Mauritius 7,035

Grand Gaube Mauritius 6,937

Medine-Camp De Masque Mauritius 6,937

Long Mountain Mauritius 6,644

Brisee Verdiere Mauritius 6,449

Laventure Mauritius 6,351

Poste De Flacq Mauritius 6,253

Quatre Cocos Mauritius 6,253

Quartier Militaire Mauritius 6,156

Ecroignard Mauritius 6,058

Port Mathurin Mauritius 5,960

Trou D'eau Douce Mauritius 5,960

Morcellement Saint Andre Mauritius 5,569

Fond Du Sac Mauritius 5,374

Poudre D'or Mauritius 5,374

Roches Noires Mauritius 5,374

Cap Malheureux Mauritius 5,276

Sebastopol Mauritius 5,276

Chamouny Mauritius 5,179

Calebasses Mauritius 4,983

Camp Diable Mauritius 4,983

Piton Mauritius 4,983

Midlands Mauritius 4,788

Mare D'albert Mauritius 4,690

D'epinay Mauritius 4,495

Belle Vue Maurel Mauritius 4,397

Petite Riviere Mauritius 4,397

Richelieu Mauritius 4,397

Camp Ithier Mauritius 4,299

Notre Dame Mauritius 4,201

Camp De Masque Pave Mauritius 4,104

Trois Boutiques Mauritius 4,006

Union Park Mauritius 4,006

Souillac Mauritius 3,908



Tamarin Mauritius 3,908

Lataniers-Mont Lubin Mauritius 3,811

Plaine Des Roches Mauritius 3,811

Bois Cheri Mauritius 3,615

Petit Gabriel Mauritius 3,615

Saint Hubert Mauritius 3,615

Olivia Mauritius 3,518

The Vale Mauritius 3,518

Cottage Mauritius 3,420

Roche Terre Mauritius 3,420

Quatre Soeurs Mauritius 3,322

Albion Mauritius 3,224

Saint Julien D'hotman Mauritius 3,224

Riviere Des Creoles Mauritius 3,127

Providence Mauritius 3,029

Old Grand Port Mauritius 2,931

Riviere Cocos Mauritius 2,931

Dubreuil Mauritius 2,834

Gros Cailloux Mauritius 2,834

Mangues-Quatre Vents Mauritius 2,834

Plaine Corail-La Fouche Corail Mauritius 2,834

Ripailles Mauritius 2,834

Port Sud-Est Mauritius 2,736

Saint Julien Mauritius 2,736

Arsenal Mauritius 2,638

Creve Coeur Mauritius 2,638

Mare Tabac Mauritius 2,638

Oyster Bay Mauritius 2,638

Amaury Mauritius 2,540

Camp De Masque Mauritius 2,540

Cascavelle Mauritius 2,540

Queen Victoria Mauritius 2,540

Bel Ombre Mauritius 2,443

L'avenir Mauritius 2,443

Amitie-Gokhoola Mauritius 2,247

Baie Du Cap Mauritius 2,247

Riviere Du Poste Mauritius 2,247

Villebague Mauritius 2,247

Benares Mauritius 2,150

Grand River South East Mauritius 2,150

Grand Sable Mauritius 2,150

Camp Thorel Mauritius 2,052

Clemencia Mauritius 2,052

Esperance Trebuchet Mauritius 2,052

Flic En Flac Mauritius 2,052

Poudre D'or Hamlet Mauritius 2,052

Roche Bon Dieu-Trefles Mauritius 2,052

Coromandel-Graviers Mauritius 1,954

Grande Riviere Noire Mauritius 1,954

Mare La Chaux Mauritius 1,954

Maputo Mozambique 1,060,424

Matola Mozambique 483,997

Beira Mozambique 452,940



Nampula Mozambique 345,726

Chimoio Mozambique 194,994

Nacala Mozambique 180,395

Quelimane Mozambique 168,120

Tete Mozambique 115,118

Xai-Xai Mozambique 113,351

Garue Mozambique 111,305

Maxixe Mozambique 106,656

Lichinga Mozambique 97,729

Pemba Mozambique 96,799

Dondo Mozambique 70,019

Angoche Mozambique 66,393

Cuamba Mozambique 65,184

Montepuez Mozambique 64,347

Mocuba Mozambique 61,371

Inhambane Mozambique 59,419

Chokwe Mozambique 56,722

Chibuto Mozambique 52,631

Mocambique Mozambique 48,353

Manica Mozambique 22,689

Quissico Mozambique 19,620

Lumbo Mozambique 17,110

Nazombe Mozambique 16,645

Inharrime Mozambique 16,087

Panda Mozambique 13,576

Macia Mozambique 12,925

Marrupa Mozambique 12,181

Chongoene Mozambique 10,694

Homoine Mozambique 10,136

Manhica Mozambique 10,136

Bela Vista Mozambique 10,043

Guija Mozambique 9,950

Magude Mozambique 9,485

Zumbo Mozambique 9,206

Jangamo Mozambique 9,020

Maniamba Mozambique 9,020

Marracuene Mozambique 9,020

Moamba Mozambique 9,020

Mandimba Mozambique 8,927

Namaacha Mozambique 8,927

Chidenguele Mozambique 8,741

Manjacaze Mozambique 8,648

Windhoek Namibia 245,334

Rundu Namibia 46,675

Walvis Bay Namibia 44,146

Oshakati Namibia 29,658

Swakopmund Namibia 26,352

Katima Mulilo Namibia 23,824

Rehoboth Namibia 22,365

Otjiwarongo Namibia 20,615

Grootfontein Namibia 17,309

Keetmanshoop Namibia 16,336

Okahandja Namibia 14,878



Gobabis Namibia 14,586

Tsumeb Namibia 13,808

Luderitz Namibia 12,544

Mariental Namibia 10,988

Ondangwa Namibia 10,696

Khorixas Namibia 10,599

Oranjemund Namibia 10,016

Bethanien Namibia 9,043

Ongwediva Namibia 8,363

Omaruru Namibia 6,515

Karasburg Namibia 6,321

Outjo Namibia 6,321

Arandis Namibia 5,834

Opuwo Namibia 5,737

Karibib Namibia 5,543

Okakarara Namibia 5,056

Otavi Namibia 4,765

Usakos Namibia 4,570

Otjimbingwe Namibia 3,792

Aranos Namibia 3,501

Eenhana Namibia 3,403

Ongandjera Namibia 3,014

Outapi Namibia 2,820

Oshikango Namibia 2,723

Maltahohe Namibia 2,625

Warmbad Namibia 2,431

Henties Bay Namibia 2,139

Okombahe Namibia 2,139

Victoria Seychelles 26,974

Anse Royal Seychelles 3,914

Cascade Seychelles 2,539

Takamaka Seychelles 2,327

Anse Boileau Seychelles 2,116

Cape Town South Africa 2,901,473

Durban South Africa 2,461,210

Johannesburg South Africa 1,920,800

Pretoria South Africa 1,432,992

Soweto South Africa 1,424,630

Port Elizabeth South Africa 754,319

Benoni South Africa 474,196

Vereeniging South Africa 449,985

Pietermaritzburg South Africa 445,027

East London South Africa 411,774

Tembisa South Africa 366,172

Bloemfontein South Africa 339,336

Boksburg South Africa 338,461

Vanderbijlpark South Africa 328,641

Newcastle South Africa 300,833

Krugersdorp South Africa 264,857

Welkom South Africa 239,286

Brakpan South Africa 222,367

Carltonville South Africa 214,297

Springs South Africa 208,658



Uitenhage South Africa 193,295

Witbank South Africa 193,004

Alberton South Africa 191,934

Botshabelo South Africa 180,753

Paarl South Africa 168,599

Midrand South Africa 164,029

Kimberley South Africa 161,501

Klerksdorp South Africa 158,195

Verwoerdburg South Africa 148,666

Westonaria South Africa 148,666

Somerset West South Africa 135,151

Bisho South Africa 134,082

Randfontein South Africa 127,373

Middelburg South Africa 120,275

Rustenburg South Africa 119,594

Nigel South Africa 119,011

Potchefstroom South Africa 118,719

George South Africa 113,080

Nelspruit South Africa 109,288

Phalaborwa South Africa 106,079

Emnambithi South Africa 103,551

Pietersburg South Africa 101,120

Potgietersrus South Africa 98,009

Epumalanga South Africa 94,995

Mabopane South Africa 93,925

Worcester South Africa 92,370

Embalenhle South Africa 89,939

Kroonstad South Africa 88,286

Richards Bay South Africa 84,397

Orkney South Africa 84,299

Louis Trichardt South Africa 84,202

Umtata South Africa 76,813

Sasolburg South Africa 75,160

Stellenbosch South Africa 71,659

Garankuwa South Africa 66,312

Oudtshoorn South Africa 64,367

Standerton South Africa 63,589

Lichtenburg South Africa 63,492

Grahamstown South Africa 62,520

Virginia South Africa 61,936

Vryheid South Africa 61,839

Stilfontein South Africa 59,992

Atlantis South Africa 59,019

Bethlehem South Africa 58,144

Kutlwanong South Africa 57,950

Brits South Africa 57,269

Heidelberg South Africa 54,255

Queenstown South Africa 54,255

Saldanha South Africa 53,574

Mosselbay South Africa 52,408

Upington South Africa 52,213

Mmabatho South Africa 49,491

Bethal South Africa 49,393



Temba South Africa 45,504

Parys South Africa 44,143

Ermelo South Africa 43,365

Thohoyandou South Africa 42,684

Phuthaditjhaba South Africa 42,587

Delmas South Africa 41,809

Esikhawini South Africa 38,212

Vryburg South Africa 38,212

Thaba Nchu South Africa 37,726

Kgotsong South Africa 37,142

Knysna South Africa 37,045

Warmbad South Africa 36,170

Ekangala South Africa 35,684

Stanger South Africa 35,684

Beaufort-West South Africa 34,420

Graaff-Reinet South Africa 34,420

Siyabuswa South Africa 34,420

Harrismith South Africa 34,225

Port Shepstone South Africa 33,739

Butterworth South Africa 33,545

Margate South Africa 33,156

Mondlo South Africa 32,961

Piet Retief South Africa 31,795

Fochville South Africa 31,308

Richmond South Africa 31,211

Wembezi South Africa 29,947

Schweizer Reneke South Africa 29,461

Cradock South Africa 29,364

Secunda South Africa 29,364

Dundee South Africa 28,975

Barberton South Africa 28,683

Empangeni South Africa 28,683

Ceres South Africa 27,225

Malmesbury South Africa 26,252

Bronkhorstspruit South Africa 25,961

Lulekani South Africa 25,863

Phola South Africa 25,863

Fort Beaufort South Africa 25,669

De Aar South Africa 25,572

Lebohang South Africa 24,988

Wolmaranstad South Africa 24,794

Heilbron South Africa 24,599

Lady Frere South Africa 24,502

Lebowakgomo South Africa 24,502

Kokstad South Africa 24,405

Viljoenskroon South Africa 24,405

Balfour South Africa 24,113

Cullinan South Africa 24,113

Hermanus South Africa 24,016

Duiwelskloof South Africa 23,822

Wesselsbron South Africa 23,822

Volksrust South Africa 23,335

Scottsburgh South Africa 23,044



Aliwal North South Africa 22,655

Giyani South Africa 22,558

Hennenman South Africa 22,266

Robertson South Africa 21,099

Pampierstad South Africa 21,002

Theunissen South Africa 20,710

Lydenburg South Africa 20,613

Ekuphumleni South Africa 20,516

Mpophomeni South Africa 20,516

Frankfort South Africa 20,321

Stutterheim South Africa 20,224

Nylstroom South Africa 19,932

Allanridge South Africa 19,738

Bulfontein South Africa 19,738

Senekal South Africa 19,641

Umkomaas South Africa 19,641

Messina South Africa 19,543

Nkowakowa South Africa 19,349

Grabouw South Africa 19,252

Kruisfontein South Africa 18,571

Plettenberg Bay South Africa 18,571

Ezibeleni South Africa 17,891

Middelburg South Africa 17,696

Howick South Africa 17,599

Port Alfred South Africa 17,502

Warrenton South Africa 17,404

Ncotshane South Africa 17,307

Postmasburg South Africa 17,210

Zeerust South Africa 17,113

Christiana South Africa 16,918

Ladybrand South Africa 16,821

Ballitoville South Africa 16,627

Bloemhof South Africa 16,529

Tzaneen South Africa 16,432

Reitz South Africa 16,238

Somerset East South Africa 15,751

Randvaal South Africa 15,168

Ventersdorp South Africa 15,168

Witrivier South Africa 15,168

Hendrina South Africa 15,071

Ellisras South Africa 14,876

Ulundi South Africa 14,779

Eshowe South Africa 14,293

Kriel South Africa 14,293

Vrede South Africa 14,293

Bredasdorp South Africa 14,196

Sundumbili South Africa 14,196

Vredendal South Africa 14,099

Ekuvukeni South Africa 13,807

Swellendam South Africa 13,710

Empuluzi South Africa 13,418

Greytown South Africa 13,418

Needscamp South Africa 13,321



Jan Kempdorp South Africa 13,126

Letsopa South Africa 13,126

Glencoe South Africa 13,029

Hoopstad South Africa 12,348

Burgersdorp South Africa 12,251

Mankweng South Africa 12,154

Zastron South Africa 12,154

Clocolan South Africa 12,057

Colesberg South Africa 12,057

Deneysville South Africa 12,057

Adelaide South Africa 11,959

Breyten South Africa 11,862

Brandfort South Africa 11,765

Whittlesea South Africa 11,765

Koster South Africa 11,668

Elliot South Africa 11,570

Jeffreys Bay South Africa 11,473

Barkly West South Africa 11,279

Belfast South Africa 11,279

Thulamahashe South Africa 11,279

Koppies South Africa 11,182

Mogwase South Africa 11,182

Villiers South Africa 10,987

Prieska South Africa 10,890

Winburg South Africa 10,793

Ilinge South Africa 10,598

Marquard South Africa 10,598

Ventersburg South Africa 10,404

Vredefort South Africa 10,404

Springbok South Africa 10,112

Thabazimbi South Africa 10,015

Kirkwood South Africa 9,918

Koffiefontein South Africa 9,918

Mooreesburg South Africa 9,918

Danielskuil South Africa 9,820

Molteno South Africa 9,820

Mooi River South Africa 9,723

Ritchie South Africa 9,723

Alice South Africa 9,529

Dordrecht South Africa 8,945

Kathu South Africa 8,945

Wepener South Africa 8,945

Kuruman South Africa 8,848

Paulpietersburg South Africa 8,265

Heidelberg South Africa 8,070

Victoria-West South Africa 7,973

Calvinia South Africa 7,876

Vredenburg South Africa 7,487

Inyala South Africa 7,390

Barkly East South Africa 7,292

Ixopo South Africa 7,195

Velddrif South Africa 7,098

Willowmore South Africa 6,903



Keimoes South Africa 6,709

Hertzogville South Africa 6,223

Mandeni South Africa 5,931

Umzimvubu South Africa 5,834

Carnarvon South Africa 5,639

Matatiele South Africa 5,639

Komga South Africa 5,542

Tarkastad South Africa 4,959

Manzini Swaziland 87,492

Mbabane Swaziland 64,453

Matsapha Swaziland 19,839

Big Bend Swaziland 10,422

Mhlume Swaziland 8,502

Malkerns Swaziland 8,228

Nhlangano Swaziland 7,222

Hluti Swaziland 6,491

Simunye Swaziland 6,217

Pigg's Peak Swaziland 5,120

Siteki Swaziland 4,663

Ngomane Swaziland 4,297

Lobamba Swaziland 4,023

Vuvulane Swaziland 4,023

Kwaluseni Swaziland 3,017

Mondi Swaziland 3,017

Bhunya Swaziland 2,926

Mhlambanyatsi Swaziland 2,834

Thabankulu Swaziland 2,834

Bulembu Swaziland 2,743

Tshaneni Swaziland 2,468

Mpaka Swaziland 2,377

Hlatikulu Swaziland 2,286

Kubuta Swaziland 1,920

Sidvokodvo Swaziland 1,737

Ezulwini Swaziland 1,554

Lavumisa Swaziland 1,280

Mankayane Swaziland 1,189

Nsoko Swaziland 1,097

Ngwenya Swaziland 914

Dar Es Salaam Tanzania 2,419,179

Mwanza Tanzania 381,544

Zanzibar Tanzania 354,951

Arusha Tanzania 285,181

Mbeya Tanzania 258,874

Morogoro Tanzania 223,227

Tanga Tanzania 210,550

Dodoma Tanzania 160,605

Kigoma Tanzania 146,117

Moshi Tanzania 145,545

Tabora Tanzania 136,395

Songea Tanzania 109,707

Musoma Tanzania 109,135

Iringa Tanzania 107,610

Uvinza Tanzania 106,466



Katumba Tanzania 100,080

Shinyanga Tanzania 93,694

Mtwara Tanzania 93,408

Kilosa Tanzania 88,833

Ushirombo Tanzania 88,547

Sumbawanga Tanzania 81,017

Bagamoyo Tanzania 71,867

Bukoba Tanzania 62,145

Mpanda Tanzania 60,811

Singida Tanzania 58,618

Uyovu Tanzania 56,712

Kalangalala Tanzania 52,900

Makambako Tanzania 51,470

Mishoma Tanzania 50,517

Sengerama Tanzania 50,231

Buseresere Tanzania 49,564

Mererani Tanzania 48,420

Bunda Tanzania 46,609

Katoro Tanzania 46,418

Ifakara Tanzania 46,037

Utengule Usongwe Tanzania 44,512

Siha Kati Tanzania 42,796

Njombe Tanzania 42,701

Lindi Tanzania 41,938

Nkome Tanzania 39,270

Kiranyi Tanzania 39,174

Nkololo Tanzania 39,079

Vwawa Tanzania 38,126

Gairo Tanzania 35,934

Kidadu Tanzania 35,552

Nguruka Tanzania 35,171

Tunduma Tanzania 34,790

Masasi Tanzania 34,504

Korogwe Tanzania 34,409

Kidodi Tanzania 34,123

Kasulu Tanzania 33,932

Mafinga Tanzania 33,932

Newala Tanzania 33,646

Isagehe Tanzania 33,360

Mikindani Tanzania 33,265

Missungwi Tanzania 33,265

Mlimba Tanzania 33,169

Igunga Tanzania 33,074

Chalinze Tanzania 32,788

Kahama Tanzania 32,598

Lusaka Zambia 1,210,941

Ndola Zambia 418,345

Kitwe Zambia 406,047

Kabwe Zambia 197,374

Chingola Zambia 164,578

Mufulira Zambia 136,582

Luanshya Zambia 129,083

Livingstone Zambia 108,886



Kasama Zambia 82,889

Chipata Zambia 81,589

Chililabombwe Zambia 60,892

Kalulushi Zambia 58,892

Mazabuka Zambia 52,593

Kafue Zambia 51,193

Mongu Zambia 49,493

Mansa Zambia 45,794

Choma Zambia 45,094

Kansanshi Zambia 37,995

Kapiri Mposhi Zambia 30,396

Mpika Zambia 28,896

Monze Zambia 27,496

Nchelenge Zambia 23,097

Kawambwa Zambia 19,997

Samfya Zambia 19,697

Mbala Zambia 18,898

Mumbwa Zambia 17,798

Petauke Zambia 16,298

Sesheke Zambia 15,498

Siavonga Zambia 14,598

Chambishi Zambia 14,498

Kaoma Zambia 13,798

Maamba Zambia 12,898

Chinsali Zambia 12,798

Isoka Zambia 12,798

Kalomo Zambia 12,298

Mwinilunga Zambia 11,998

Mkushi Zambia 11,798

Mpongwe Zambia 11,798

Katete Zambia 11,598

Sinazongwe Zambia 11,598

Nakambala Zambia 10,999

Mwanzakombe Zambia 10,799

Nakonde Zambia 10,399

Senanga Zambia 10,299

Chilanga Zambia 10,199

Lundazi Zambia 10,199

Serenje Zambia 9,599

Kalabo Zambia 8,399

Limulunga Zambia 8,399

Mpulungu Zambia 8,399

Itezhi-Tezhi Zambia 7,699

Zambezi Zambia 7,499

Kalengwa Zambia 7,299

Mungwi Zambia 6,699

Kabompo Zambia 6,499

Luwingu Zambia 5,999

Mufumbwe Zambia 5,999

Chongwe Zambia 5,799

Kasempa Zambia 5,499

Namwala Zambia 4,499

Harare Zimbabwe 2,265,437



Bulawayo Zimbabwe 1,150,485

Chitungwiza Zimbabwe 485,778

Mutare Zimbabwe 223,862

Gweru Zimbabwe 180,533

Kadoma Zimbabwe 126,431

Masvingo Zimbabwe 95,482

Kwekwe Zimbabwe 93,419

Marondera Zimbabwe 83,790

Zvishavane Zimbabwe 83,676

Chinhoyi Zimbabwe 69,806

Hwange Zimbabwe 67,285

Chegutu Zimbabwe 46,079

Redcliffe Zimbabwe 41,494

Kariba Zimbabwe 39,889

Bindura Zimbabwe 30,490

Victoria Falls Zimbabwe 27,739

Sakubva Zimbabwe 27,051

Norton Zimbabwe 26,593

Karoi Zimbabwe 23,957

Rusape Zimbabwe 23,727

Shurugwi Zimbabwe 22,008

Chiredzi Zimbabwe 16,735

Plumtree Zimbabwe 15,933

Mount Darwin Zimbabwe 15,016

Chipinge Zimbabwe 14,213

Gwanda Zimbabwe 14,099

Tuli Zimbabwe 12,723

Chimanimani Zimbabwe 11,692

Nyanga Zimbabwe 11,692

Chivhu Zimbabwe 10,431

Mutoko Zimbabwe 10,316

Gaths Zimbabwe 9,972

West Nicholson Zimbabwe 9,285

Mvuma Zimbabwe 8,368

Beitbridge Zimbabwe 6,075



Appendix G Total impact per airport over the 50 year period less airport/navigational infrastructure

costs (R Millions)

Location 5 Years 10 Years 15 Years 20 Years 25 Years 30 Years 35 Years 40 Years 45 Years 50 Years TOTAL

Cabinda -3.41 -3.41 -3.41 -1555.07 -380.12 -2985.60 -2369.01 -4391.83 -1576.26 -4464.42 -17732.55

Catumbela -3.03 -3.03 -3.03 786.63 701.61 -883.63 -935.52 -3005.74 -325.72 -3002.72 -6674.16

Dundo 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Huambo 7.85 7.85 17.34 -577.23 60.07 -2373.49 -2945.19 -2697.68 -2573.37 -2779.25 -13853.10

Kuito 8.63 8.63 8.63 -424.35 684.54 -2371.07 -2098.33 -3403.71 -1589.07 -3483.26 -12659.37

Luanda 2034.37 2034.37 2038.57 2242.34 3053.54 983.09 2508.28 1497.87 2421.35 1522.48 20336.26

Lubango 683.08 683.08 683.08 1128.09 2237.11 -804.10 -445.62 -1665.40 153.34 -1741.87 910.80

Luena 784.40 784.40 784.40 2537.35 2772.99 1563.33 1487.84 -1026.67 1152.78 -852.84 9988.00

Malanje 335.97 335.97 335.97 1280.29 2597.23 -468.04 -8.15 -1676.01 560.87 -1754.25 1539.83

Menongue 813.28 813.28 813.28 2418.22 3866.02 1011.59 1575.99 -997.29 2226.29 -1045.76 11494.90

Namibe 739.40 739.40 1234.06 3778.53 4658.83 2051.70 1704.46 1776.21 2194.78 1699.74 20577.13

Ondjiva 936.77 936.77 936.77 3738.74 5643.66 3426.84 3971.10 955.87 4540.65 979.89 26067.06

Saurimo 800.76 800.76 800.76 5897.83 7118.67 4605.51 4851.32 2402.59 5534.29 2322.46 35134.95

Soyo 298.54 298.54 298.54 6448.73 8292.71 5855.36 6478.95 4211.64 7253.61 4164.63 43601.25

Uíge 0.00 0.00 216.68 4945.03 6660.87 3987.02 4795.89 2232.08 5270.35 2224.04 30331.95

Francistown 7.13 7.13 -157.54 -776.65 -141.47 14158.03 16080.64 16010.69 15984.09 16021.93 77193.97

Gaborone 429.29 429.29 429.29 466.31 2756.95 21836.15 21780.30 22453.88 21685.41 22469.22 114736.08

Kasane 779.36 779.36 1114.65 1274.34 1138.14 3261.45 10578.56 14905.53 10887.11 14814.82 59533.32

Maun 1431.80 1431.80 1431.80 1513.70 2403.98 12533.81 14244.64 14578.59 14330.77 14485.71 78386.60

Bukavu 0.00 0.00 0.00 0.00 22.27 -1231.81 5008.61 21032.85 23867.52 22425.68 71125.11

Buta-Zega 0.00 0.00 0.00 0.00 18.90 -800.48 4445.29 17524.50 24589.82 26410.83 72188.86

Gbadolite 16.03 16.03 16.03 16.03 16.03 -1051.33 5824.68 20717.28 26128.99 26933.68 78633.44

Gemena 0.00 0.00 0.00 0.00 13.47 -356.26 7768.70 22958.63 26508.32 24723.14 81616.00

Goma 0.00 0.00 0.00 0.00 23.48 939.59 8271.83 24135.17 28072.84 25685.91 87128.82

Isiro-Matari 0.00 0.00 0.00 0.00 23.61 1029.36 9439.06 27545.71 31309.00 29368.43 98715.18

Kananga 0.00 0.00 0.00 0.00 26.42 3247.67 10757.33 18278.27 22661.60 18319.06 73290.35

Kindu 0.00 0.00 0.00 0.00 16.96 1860.49 8620.85 21789.45 25073.49 23130.04 80491.27

Kinshasa 1036.57 1036.57 1036.57 1036.57 8816.88 15585.23 26360.21 27478.42 27832.52 27404.36 137623.91

Kisangani 1059.34 1059.34 1059.34 1059.34 1096.60 5374.53 13754.03 29045.85 31120.41 29147.73 113776.53

Lubumbashi 1401.39 1401.39 1401.39 1401.39 3513.78 13948.75 22247.96 29247.69 31956.38 29231.47 135751.60



Mbandaka 0.00 0.00 0.00 0.00 1886.95 6517.25 13732.70 26030.37 29799.95 26331.77 104299.00

Mbuji-Mayi 796.11 796.11 796.11 796.11 2167.66 7376.35 15821.63 22395.55 27079.87 22431.27 100456.76

Maseru -4.62 -4.62 -4.62 -4.62 1.12 2703.74 13514.55 34730.50 50640.41 49578.30 151150.16

Antanànarìvo 26.00 26.00 26.00 26.00 249.97 14290.87 54041.04 77559.25 77367.97 77479.66 301092.75

Mahajanga 309.03 309.03 309.03 309.03 373.12 5371.20 21127.29 52829.00 67420.96 66531.44 214889.13

Nosy Be 0.00 0.00 0.00 0.00 623.64 99.78 14787.69 50160.31 69519.63 68093.99 203285.05

Toamasina 164.64 164.64 164.64 164.64 1192.46 7777.80 42703.68 71554.37 76224.14 76396.59 276507.60

Toliara 565.42 565.42 565.42 565.42 2738.42 6124.57 19340.62 49468.13 69202.73 67162.89 216299.03

Blantyre 36.33 36.33 36.33 36.33 108.07 4062.34 22534.33 46544.15 49257.69 49829.11 172481.01

Lilongwe 169.25 169.25 169.25 169.25 267.18 4536.03 25507.92 45154.77 50486.87 48124.81 174754.57

Port Louis 1265.37 1265.37 1265.37 1438.94 15548.12 84419.78 121950.90 122102.56 121872.83 122134.97 593264.22

Beira 15.88 15.88 15.88 15.88 175.83 5358.12 30068.20 51392.45 54724.95 55133.79 196916.86

Chimoio 0.00 0.00 0.00 10.79 -340.17 2914.28 11695.73 34957.00 50340.81 47596.54 147174.97

Cuamba 0.00 0.00 0.00 0.00 525.75 -213.44 6141.83 31797.32 50863.46 48643.72 137758.65

Lichinga 14.29 14.29 14.29 14.29 1002.50 2011.79 12167.71 38209.56 51652.98 48946.13 154047.81

Maputo 1986.45 1986.45 1986.45 2662.00 3899.75 12546.66 44782.34 69101.47 68832.98 69017.50 276802.06

Moçimboa da Praia 1587.63 1587.63 1587.63 1587.63 2553.51 3648.92 11386.06 37976.22 60575.29 59930.55 182421.06

Mueda 0.00 0.00 0.00 0.00 2428.66 3395.27 10716.64 36354.23 57121.00 57704.57 167720.35

Nampula 2011.91 2011.91 2011.91 2011.91 4815.73 11478.20 37113.11 59868.76 64279.95 63460.16 249063.56

Tete 1624.01 1624.01 1624.01 1624.01 2455.77 6949.10 14089.50 38751.64 53181.07 50177.64 172100.75

Grootfontein 0.00 0.00 -4.18 48.01 176.90 5282.55 32235.21 63212.93 62891.32 63133.15 226975.89

Karabib 0.00 0.00 0.00 237.03 -303.33 3765.55 13720.43 48537.65 67146.98 64556.87 197661.18

Katima Mulilo 0.00 0.00 15.17 798.92 925.91 4694.36 28177.42 55373.46 56333.15 55288.43 201606.82

Keetmanshoop 0.00 0.00 6.13 1215.27 1452.25 7199.55 36821.76 77893.59 79110.54 77818.75 281517.84

Mariental 0.00 0.00 0.00 1015.76 1216.69 5698.82 25077.46 66502.11 72718.36 70530.68 242759.88

Ondangwa 0.00 0.00 7.54 2104.58 2432.52 7831.16 29422.19 60570.18 65170.77 63889.69 231428.64

Rundu 0.00 0.00 8.68 2450.58 2587.75 6860.17 32837.05 61098.66 61393.78 61016.42 228253.09

Windhoek 3617.00 3617.00 6357.30 6658.80 10827.12 36606.53 74693.33 82555.89 79033.03 82469.88 386435.89

Seychelles 102.46 102.46 102.46 236.68 10266.94 60259.99 140264.25 161552.92 159863.16 161479.56 694230.88

Bisho 38.15 -1647.26 179.89 -1647.26 12825.12 64464.75 112410.19 108321.27 112325.13 108345.44 515615.41

Bloemfontein -280.00 -1292.03 325.47 972.41 17467.61 69399.41 99550.96 94970.10 99457.88 94990.75 475562.55

Cape Town 17212.70 17396.75 17396.75 21759.01 74988.69 135447.41 138013.11 135358.67 138045.44 135358.67 830977.21

Durban 2769.71 2455.64 2883.35 14698.58 62987.35 111209.99 110772.43 111110.68 110794.61 111110.68 640793.03

George 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Lanseria 15263.41 17662.18 15318.49 19411.69 48125.01 88453.01 90511.29 93564.91 90528.67 93564.91 572403.57



Johannesburg 2144.65 3453.98 3453.98 15075.88 66228.86 101775.09 101775.09 101793.12 101793.12 101793.12 599286.89

Kimberley 1489.32 1326.70 2899.43 1326.70 16027.41 63351.65 99702.98 95326.13 99612.05 95346.67 476409.03

Mafikeng 527.70 2007.42 4324.18 2007.42 13526.42 48925.35 88576.40 83824.97 88483.57 83841.70 416045.12

Nelspruit 908.73 3759.50 6298.77 3759.50 18700.07 62309.05 95784.23 90750.70 95688.43 90766.44 468725.43

Polokwane 300.68 4036.25 6572.51 4036.25 15491.01 50548.42 86533.32 81735.57 86437.42 81748.89 417440.32

Port Elizabeth 1088.46 7440.16 9094.35 15217.50 51391.24 108832.21 132010.30 129465.13 131921.00 129492.81 715953.16

Pilanesberg 0.00 3579.72 5873.56 3579.72 14968.05 47145.88 87800.81 83642.19 87707.22 83657.50 417954.66

Umtata 1372.29 5411.66 7719.39 5411.66 19750.05 63165.63 113296.58 109882.02 113210.13 109904.05 549123.46

Upington 1308.87 8212.50 10349.20 8212.50 21439.74 57166.35 105055.27 102400.43 104968.74 102421.96 521535.57

Welkom 0.00 4509.04 6874.97 4509.04 21166.99 66837.52 100729.91 95714.36 100636.52 95733.63 496711.98

Manzini 510.17 510.17 510.17 510.17 2064.23 14215.41 47651.11 81765.32 85462.82 86061.53 319261.09

Dar-Es-Salaam 3332.27 3332.27 3332.27 5570.79 29180.71 64818.11 119827.06 134255.85 133478.46 134166.97 631294.77

Dodoma 345.40 345.40 345.40 91.25 4192.22 34671.37 64264.35 103795.05 115272.77 112703.35 436026.56

Kilimanjaro -3.66 -3.66 -3.66 767.50 14710.11 52384.64 110811.12 134074.65 133405.28 133992.14 580134.45

Mtwara 356.83 356.83 356.83 1116.95 3008.64 33636.63 63939.98 104318.89 117167.73 114583.95 438843.27

Mwanza 3163.74 3163.74 3163.74 3692.37 15924.03 53018.10 101985.22 128784.99 129744.46 128703.55 571343.95

Zanzibar 642.27 642.27 642.27 1301.20 13689.13 48691.20 99145.39 127719.37 128165.44 127636.67 548275.21

Kitwe -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -77.08 -770.78

Livingstone 2525.99 2525.99 2525.99 2536.90 4640.43 21610.36 54967.69 86976.14 86805.54 86976.14 352091.17

Lusaka 2428.44 2428.44 2428.44 3523.06 21561.07 44754.28 82799.13 96355.77 94773.22 96355.77 447407.62

Mfuwe 0.00 0.00 0.00 0.00 0.00 0.00 882.18 5101.67 19585.42 61253.02 86822.29

Ndola 231.69 231.69 231.69 800.19 9881.81 34333.10 77186.75 94157.68 91932.11 94157.68 403144.39

Bulawayo 519.34 569.36 519.34 569.36 953.23 12563.28 32803.83 67823.72 85170.24 82798.67 284290.37

Harare 6022.29 6022.29 6022.29 6022.29 9762.06 25050.44 53280.88 83853.89 91076.30 88592.52 375705.24

Hwange 997.51 997.51 997.51 997.51 997.51 3934.91 16905.05 45261.05 73228.30 77412.33 221729.21

Victoria Falls 728.39 728.39 728.39 728.39 728.39 4057.69 18915.69 40772.00 72817.74 77916.00 218121.07

TOTAL 93752.97 127970.55 152841.86 211310.85 746270.63 2020195.17 3668038.46 4848948.65 5310977.47 5240560.13 22420866.74

Documents

Final Report - WordPress.com...Socio-economic Impact of an Air Transport Liberalisation Agreement in SADC: 30th August 2010 - report prepared by Graham Muller Associates Removal of