22
e African Statistical Journal, Volume 14, May 2012 83 3. An alternative approach for determining air transportation costs in the International Comparison Program Abdoulaye Adam 1 Abstract In the International Comparison Program (ICP) the cost of air transportation is compared across countries. The cost of air transportation between two cities varies depending on the quality of service and the air carrier. The quality of service (aircraft type, meals and refreshments, on-board entertainment, flight schedule, etc) is reflected in the price of the ticket. The date of issuing the ticket before travel is also a price-determining factor. Precisely capturing all the price- determining characteristics in the product description is difficult and may not be feasible. Therefore, airfare prices constitute a challenge for ICP price collection if like is to be compared like with like. This paper examines air transportation structured product descriptions (SPDs) from the 2005 and in 2011 ICP rounds and notes their deficiencies for purposes of comparison. It proposes a number of improvements: (i) using a geographic coordinate system (latitude and longitude) to determine orthodromic distances between departure and destination points; and (ii) basing comparisons on unit (kilometer or mile) costs of these orthodromic distances. It would then be possible for air transportation price data to be collected directly by Regional Coordination teams or by the Global Office through travel agencies, using the major Computer Reservation System (CRS) vendors. Key words: Airfare prices, Structured Product Descriptions, Latitude, Longitude, Orthodromic Distances, Computer Reservation System Résumé Les coûts du transport aérien sont comparés entre les pays dans le Programme de comparaison internationale (PCI). Le coût du transport aérien entre deux villes varie en fonction de la qualité du service et de la compagnie aérienne. La qualité du service (type d’aéronef, les repas, les rafraîchissements et le divertissement à bord, l’horaire de vol, etc.) est répercutée sur le prix du billet. La date d’émission du billet avant le voyage est aussi un facteur déterminant le prix. Capter avec précision toutes les caractéristiques déterminant le prix dans la description du produit est difficile et peut ne pas être réalisable. En conséquence, les prix des billets d’avion constituent un défi pour la collecte des prix du PCI en vue de comparer des choses comparables. 1 Abdoulaye ADAM, International Statistical Consultant BP 12965 Niamey NIGER, Email:[email protected]

3. An alternative approach for determining air

  • Upload
    others

  • View
    6

  • Download
    0

Embed Size (px)

Citation preview

The African Statistical Journal, Volume 14, May 2012 83

3. An alternative approach for determining air transportation costs in the International Comparison Program

Abdoulaye Adam1

AbstractIn the International Comparison Program (ICP) the cost of air transportation is compared across countries. The cost of air transportation between two cities varies depending on the quality of service and the air carrier. The quality of service (aircraft type, meals and refreshments, on-board entertainment, flight schedule, etc) is reflected in the price of the ticket. The date of issuing the ticket before travel is also a price-determining factor. Precisely capturing all the price-determining characteristics in the product description is difficult and may not be feasible. Therefore, airfare prices constitute a challenge for ICP price collection if like is to be compared like with like.

This paper examines air transportation structured product descriptions (SPDs) from the 2005 and in 2011 ICP rounds and notes their deficiencies for purposes of comparison. It proposes a number of improvements: (i) using a geographic coordinate system (latitude and longitude) to determine orthodromic distances between departure and destination points; and (ii) basing comparisons on unit (kilometer or mile) costs of these orthodromic distances. It would then be possible for air transportation price data to be collected directly by Regional Coordination teams or by the Global Office through travel agencies, using the major Computer Reservation System (CRS) vendors.

Key words: Airfare prices, Structured Product Descriptions, Latitude, Longitude, Orthodromic Distances, Computer Reservation System

RésuméLes coûts du transport aérien sont comparés entre les pays dans le Programme de comparaison internationale (PCI). Le coût du transport aérien entre deux villes varie en fonction de la qualité du service et de la compagnie aérienne. La qualité du service (type d’aéronef, les repas, les rafraîchissements et le divertissement à bord, l’horaire de vol, etc.) est répercutée sur le prix du billet. La date d’émission du billet avant le voyage est aussi un facteur déterminant le prix. Capter avec précision toutes les caractéristiques déterminant le prix dans la description du produit est difficile et peut ne pas être réalisable. En conséquence, les prix des billets d’avion constituent un défi pour la collecte des prix du PCI en vue de comparer des choses comparables.

1 Abdoulaye ADAM, International Statistical Consultant BP 12965 Niamey NIGER, Email:[email protected]

Journal statistique africain, numéro 14, mai 201284

Abdoulaye Adam

Ce document examine les descriptions structurées de produits (DSP) du transport aérien des deux cycles 2005 et 2011 du PCI et met en exergue leurs lacunes en termes d’exhaustivité pour des fins de comparaison. Il propose un certain nombre d’améliorations et recommande de: (i) utiliser les coordonnées géographiques (latitude et longitude) pour déterminer les distances orthodromiques entre les points de départ et de destination et ; baser les comparaisons sur les coûts uni-taires (km ou mile) de ces distances orthodromiques. Alors il est possible de faire la collecte des prix du transport aérien directement par les équipes régionales de coordination ou par le Bureau mondial à travers des agences de voyages en utilisant les systèmes informatiques majeurs de réservation.

Mots clés : Tarifs aériens, Descriptions structurées de produits, Latitude, Lon-gitude, Distances orthodromiques, Système informatique de réservation

1. INTRODUCTION

The qualityof Purchasing Power Parities (PPPs), which are used for country comparisons, depends on the capacity to separate pure price levels from other factors, and to measure them accordingly. One of the most difficult problems in constructing those indices is accurately describing products so as to capture and treat quality change and/or differences across countries. A product is the smallest entity on which price measurements may be made and compared. It should be defined by a “complete description.”

In the 2005 International Comparison Program (ICP) round, Structured Product Descriptions (SPDs) were used to describe products, the prices of which were collected and compared among countries. An SPD is a coherent and structured set of price-determining characteristics or parameters aimed at describing goods and services in a rationalized fashion in order to develop an item list and harmonize item identification for price surveys in different countries. SPDs provide all the relevant characteristics of products, whereby each product represents a particular configuration of those characteristics.

Airfare prices were collected during the 2005 ICP round from two main sources: (i) airline companies and (ii) travel agencies using Computer Reser-vation Systems and/or airlines. In addition to airfare, surcharges, and taxes, the price of a ticket includes the quality of the service (aircraft type, meals and refreshments, on-board entertainment, flight schedule, etc). The date of issuing the ticket before travel is also a price-determinant.

The African Statistical Journal, Volume 14, May 2012 85

3. An alternative approach for determining air transportation costs in the International Comparison Program

The air transportation products in 2005 were not directly comparable. The SPDs failed to capture differences in the quality of services. As well, the distances involved differed considerably.

This paper examines the 2005 and in 2011 air transportation SPDs and notes their shortcomings for comparative purposes. To make the prices of air transportation more comparable, improvements are proposed for the 2011 ICP product list: (i) use of a geographic coordinate system (latitude and longitude) to determine orthodromic distances between the points of departure and destination, and (ii) basing the comparisons on the unit (kilometer or mile) cost of these orthodromic distances. This would make it possible for price data for air transportation to be collected directly by Regional Coordination teams or by the Global Office through travel agen-cies, using the major Computer Reservation System (CRS) vendors.

2. DEsCRIPTIONs UsED IN 2005 AND 2011 ICP-AfRICA ROUNDs

Structured Product Descriptions (SPDs) were used in 2005 to define prod-ucts in the ICP-Africa list, including transportation by air. An example is provided in Table 1.

Journal statistique africain, numéro 14, mai 201286

Abdoulaye Adam

Table 1: Example of air transportation product description in 2005 ICP-Africa

Basic heading: Passenger transport by air

Position élémentaire : Transport de voyageurs par air

Product name: Airfare to johannesburg Product code: 088.01

Nom du produit : Tarif vol aérien pour johannesburg

Code du produit : 088.01

Preferred quantity and unit of meas-urement:

1 service Quantité de référence et Unité de Mesure :

1 Service

Product description:

• Quantity: 1 service

• Type : Scheduled service

• Discounts/Type of ticket : Weekend rule (night Saturday/Sunday must be spent at destination)

• Discounts/Type of ticket : Minimum stay (of _7__ days)

• Discounts/Type of ticket : Maximum stay (of __60_ days)

• Discounts/Type of ticket : Advance reservation ( _14_ days)

• Discounts/Type of ticket : Advance payment ( _14_ days)

• Taxes : Airport tax included

• Type of Trip : Round trip

• Luggage : Included up to_25_kg

• Other item features : Cheapest non-rebookable Economy class fare

• Other item features : Exclude airport or departure tax

A problem with the description in Table 1 is that a major price-determining factor—the distance between the points of departure and destination—is not considered, so the product is not directly comparable across countries. And because the data source (airline or travel agency) is not indicated, the difficulty of product comparability is compounded. Furthermore, as

The African Statistical Journal, Volume 14, May 2012 87

3. An alternative approach for determining air transportation costs in the International Comparison Program

pointed out earlier, the quality of the service, and thus, the cost depends on the airline. One of the characteristics of the product is “Cheapest non-rebookable Economy class fare,” but this does not cover other restrictive conditions like date fixity or date change penalties. A better way of taking conditions of ticket usage into account would be to include the type of Economy class ticket.

The descriptions of Transportation by air products have been improved in the 2011 ICP product list. An example is presented in Table 2.

Table 2: Example of air transportation product description in 2011 ICP-Africa

Basic heading 1107331 Passenger transport by air

Product 110733106 Flight, International, return ticket – Long Distance

Number of units: 1 Unit of measurement: Ticket

Product specifications:

Transportation Type: International flight; round trip

Ticket type: Return ticket; not changeable after issue; non refundable

Starting point: Major airpoirt of the country

Destination: Most popular international destination

Distance: Approximately 14,000 km

Class: Economy adult passenger

Departure date: On or about last Wedneysday of April

Issued before departure: 42 - 56 days

Payment: When issued

Price includes: All additional taxes, fees, surcharges and charges included in the ticket, e.g. departure tax, passenger service charge, fuel surcharge

Price excludes: Price reductions, e.g. discount or special offer only for best customers

Purchasing place: Travel agent

Comments: Specify destination

The 2011 SPD is an improvement over 2005, but the description still does not properly address the distance issue, which is a major price determinant. The most popular international destinations vary in different countries and can be far less than 14,000 km away. The 2011 SPD requires that the destination, distance in km, additional taxes, fees, surcharges and charges be

Journal statistique africain, numéro 14, mai 201288

Abdoulaye Adam

specified. However, these data, all of which are important in determining the price of a ticket, may not be collected unless the it is clearly specified that they be included. Thus, the data collection instruments should have fields for these elements, just as there is for the price of the ticket. Also, it should be clear that distance refers to flying distance based on orthodromic distance.

3. sUggEsTED APPROACh fOR COllECTION Of AIR TRANsPORTATION PRICEs

3.1 Data sources

Airline companies and travel agencies are the two main sources of air trans-portation price data. Tariffs can be classified into two groups: (i) public domain information, which is accessible worldwide, provided by the three major global Computer Reservation System vendors—Amadeus, Sabre and Travelport (including Galileo and Worldspan); and (ii) market tariff, which is accessible in countries or regions only for the points of departure. For example, a travel agency in Tunis, Tunisia, does not have access to the U.S. market prices, and American travel agencies do not have access to price information for North Africa. To ensure comparability, it is essential that the same source be used to determine the price of air transportation products. This can be done if prices are determined globally.

3.2 Class types

In addition to the different data sources, prices vary within the same class depending on the class type:

• First Class: F, A and P• Business Class: J, C, D and Z• Economy Class: Y, L, K, Q, V, T, H, S and B

Each class type has different own conditions of ticket usage (e.g., date fixity, date change penalties, reimbursement, and validity).

3.3 geographic coordinate system

A location can be identified based on its latitude and its longitude, which Wikipedia defines as:

The African Statistical Journal, Volume 14, May 2012 89

3. An alternative approach for determining air transportation costs in the International Comparison Program

• The latitude of a location is the angular distance of that location south or north of the Equator. It is an angle and is usually measured in degrees. The Equator has a latitude of 0°, while the North and South Poles have, respectively, a latitude of 90° north (written 90° N or +90°), and a latitude of 90° south (written 90° S or −90°). The latitude of point A is the angle φ between the normal of the point and the Equator.

Figure 1: Definition of the latitude of a point A

• longitude specifies the east-west position of a point on the Earth’s surface. Points with the same longitude lie in lines running from the North to the South Pole, known as meridians. By convention, the position of zero degrees longitude is the position of the Prime Meridian, which passes through the Royal Observatory, Greenwich, England. The longitude of other places is measured as an angle east or west of the Prime Meridian. Specifically, it is the angle between a plane containing the Prime Meridian and a plane containing the North Pole, South Pole and the location in question. It ranges from 0° at the Prime Meridian to +180° eastward and −180° westward.

To precisely locate points on Earth, latitude and longitude are expressed in degrees, minutes, and seconds. A one-degree variation in latitude is about 69 miles; a minute of latitude, approximately 1.15 miles; and a second of latitude, approximately 0.02 miles. The magnitude of a difference induced by a longitude variation depends on the latitude. At the Equator, it is ap-proximately 69 miles, the same as a degree of latitude. At latitude of 45 degrees, a degree of longitude is approximately 49 miles. The size gradually decreases to zero as the meridians converge at the poles.

North Pole

φ Equator

Normal

Tangent

A

Journal statistique africain, numéro 14, mai 201290

Abdoulaye Adam

3.4 Central angle

A central angle is an angle whose vertex is the center of a circle and whose sides pass through a pair of points on the circle. The sides subtend an arc between the two points whose angle is (by definition) equal to the central angle itself.

Figure 2: Definition of a central angle

The angle AOB forms a central angle, with center O and sides OA and OB.

Let ffss λφλφ ,;, be the geographical latitude and longitude of the two points A and B (a point of departure and a point of destination of a journey), and let λφ ΔΔ , be, respectively, their differences; then , the central angle be-tween them, is given by the spherical law of cosines defined in Wikipedia as:

)coscoscossincos(sinˆ λφφφφσ Δ+=Δ fsfsar (1)

When the distance is small (the two points are not far apart), the above formula can have large rounding errors. In that case, the harversine formula below is more numerically stable.

⎟⎟⎠

⎞⎜⎜⎝

⎛⎟⎠

⎞⎜⎝

⎛ Δ+⎟⎠

⎞⎜⎝

⎛ Δ=Δ2

sincoscos2

sinarcsin2ˆ 22 λφφ

φσ fs (2)

If the points are on opposite ends of the sphere (antipodal points), the following more complicated formula, which is accurate for all distances, should be used:

O

B A

The African Statistical Journal, Volume 14, May 2012 91

3. An alternative approach for determining air transportation costs in the International Comparison Program

⎟⎟⎟

⎜⎜⎜

Δ+

Δ−+Δ=Δ

λφφφφ

λφφφφλφσ

coscoscossinsin

)coscossinsin(cos)sin(cosarctanˆ

22

fsfs

fsfsf

(3)

3.5 Orthodromic distance

In Euclidean geometry, the shortest distance between two points is the straight line joining them. In spherical geometry, distances are generally measured along a path on the surface of a sphere. The orthodromic distance, or the great-circle distance, between two points is the shortest distance between the two points on the surface of a sphere.

Geodesics/Great circles are defined as circles on the sphere whose centers are coincident with the center of the sphere. Geodesics/Great circles possess two essential features of Euclidean geometry:

• A point that moves along the surface of a sphere without turning will follow a great circle.

• The shortest distance between two points on a sphere lies along a great circle.

The distance d between two points on a sphere of radius r, and central angle σ̂Δ (expressed in radians) is given by:

σ̂Δ= rd (4)

The shape of the earth resembles a flattened sphere. The average radius for that approximation is 6371.01 km, while the quadratic mean or root mean square approximation of the average great circle circumference gives a radius of about 6372.8 km

Example of the computation of the orthodromic distanceTo calculate the orthodromic distance between Niamey, Niger and Paris, their latitudes and longitudes are converted into decimal degrees:

Niamey (Lat: 13.5167 / Long: 2.1167)

Paris (Lat: 48.8667 / Long: 2.3333)

Journal statistique africain, numéro 14, mai 201292

Abdoulaye Adam

Based on the above notation and the first equation:

φN = 13.5167 λN = 2.1167 φP = 48.8667 λN = 2.33333 Δφ = - 35.35 Δλ = - 0.2166 Cos φN = 0.9723 Cos φP = 0.6580 Cos Δλ = 0.9999 Sin φN = 0.0368 Sin φP = 0.0407

σ̂Δ = arcos{(0.2337)(0.7532) + (0.97237)(0.65780)(0.9999)} = 0.616981789

Orthodromic Distance Niamey-Paris = (0.616981789)(6372.8) = 3,931.9 km

Other orthodromic distances calculated using the above three expressions are presented in Annex 1. The same values of σ̂Δ , and thus, of distances were found with all three expressions.

An easier way to find the orthodromic distance between two cities is through Internet websites:

www.travelmath.com www.mapcrow.info www.infoplease.com www.globefeed.com www.worldatlas.com

However, because the latitude and longitude and the formulae used differ slightly from one site to another, these sites do not give exactly the same distances. For the ICP, it is important to use the same source for distances on which prices will be determined in order to control variations that are not due to price differences.

4. PROCEDURE TO DETERMINE ORThODROMIC AND CRs-BAsED AIRfARE PRICE

The price of air transportation products can be determined by ICP regional or global coordinates using orthodromic distances between points of depar-ture and destination and prices obtained from one of the main Computer Reservation System (CRS) vendors—Amadeus, Sabre and Travelport (in-cluding Galileo and Worldspan). The procedure is:

1. For each participating country, determine the geographical coordinates of the departure and destination points of the air transportation products and calculate orthodromic distances between them using one of the

The African Statistical Journal, Volume 14, May 2012 93

3. An alternative approach for determining air transportation costs in the International Comparison Program

central angle formulae. These distances can be obtained from one of websites listed above. However, it is important to use the same method to determine all the distances.

2. Obtain the cost of such journeys from one of the main CRS vendors. These prices are more comparable than those from airline companies, which differ globally and across categories like airfare, surcharges and taxes.

3. Calculate the price per kilometer (km) of each product. These prices will then be used to compute PPPs for the basic headings after converting them in local currencies if necessary.

For ICP-Africa, the air transportation PPPs could be calculated based on the price per km of round-trip tickets from the capital cities of participat-ing African countries to selected destinations—London, Washington DC, New York, Johannesburg, Nairobi, Cairo and Dakar—and to cities where the implementing agencies for other ICP regions are located—Tunis (ICP-Africa), Manila (ICP-Asia), Moscow (CIS-Rosstat), Santiago, Chile (ICP-LAC), Beirut, Lebanon (ICP-Western Asia), and Paris (OECD). The final list of destinations for Africa may be decided based on the information in Amadeus, which is the most common CRS in Africa.

Orthodromic distances between each capital city and the above destina-tions, obtained from www.worldatlas.com, are presented in Annex 2. Prices of an Economy class Y, one-way ticket from African capital cities to those destinations were obtained by the World Bank Travel Agency (American Express) from the Amadeus database. These prices were converted into costs per km, as presented in Annex 3. The prices per km of all products will be converted into local currencies and used to compute the PPPs.

5. CONClUsION

Air transportation between any two cities is a product whose quality (aircraft type, meals and refreshments, on-board entertainment, flight schedule, etc.) depends on the services the air carrier offers. The quality of the serv-ice is reflected in the price of the ticket and is not entirely captured in the product description. Consequently, products of different qualities are being compared. In addition, the distance between the departure and destination points should be considered in the comparison. This study demonstrates that it is possible to collect airfare prices globally, or at least regionally, us-

Journal statistique africain, numéro 14, mai 201294

Abdoulaye Adam

ing one of the major CRS vendors, and to take the distance of the trip into consideration. Ideally, distance should be orthodromic, and comparisons should be based on prices per unit distance (kilometer or mile).

REfERENCE

African Development Bank (2005), Product Catalogue for ICP Price Survey in African Countries Vol 2.

Gade, K (2004), NavLab, a Generic Simulation and Post-processing Tool for Navigation- European,” Journal of Navigation 2 51-59

Longley, PA Goodchild, M.F, Maguire,D.J and Rhind,D.W (2003). Geo-graphic Information Systems and Science, John Wiley and Sons 2nd Edition

The World Bank, ICP Global Office, DECDG (2011). Product Catalogue for ICP Price Surveys Global Core List 2011

Wikipedia, the free Encyclopedia. Available at: http://en.wikipedia.org/wiki/Great-circle_distance

The African Statistical Journal, Volume 14, May 2012 95

3. An alternative approach for determining air transportation costs in the International Comparison Program

AN

NE

X 1

: DE

TE

RM

INAT

ION

Of

OR

Th

OD

RO

MIC

DIs

TA

NC

Es

UsI

Ng

CE

NT

RA

l A

Ng

lE

fO

RM

Ul

AE

Nia

mey

-Lon

don

13.5

251

.50

2.12

-0.1

22.

23-1

8.99

1.12

0.66

370.

6637

0.66

37N

iam

ey-N

ew Y

ork

13.5

240

.71

2.12

-74.

0176

.12

-13.

6038

.06

1.23

531.

2353

1.23

53N

iam

ey-P

aris

13.5

248

.87

2.12

2.33

-0.2

2-1

7.68

-0.1

10.

6170

0.61

700.

6170

Nia

mey

-W

ash

DC

13.5

238

.90

2.12

-77.

0479

.15

-12.

6939

.58

1.27

741.

2774

1.27

74T

unis

-Lon

don

34.0

051

.50

9.00

-0.1

29.

12-8

.75

4.56

0.32

640.

3264

0.32

64T

unis

-New

Yor

k34

.00

40.7

19.

00-7

4.01

83.0

1-3

.36

41.5

01.

1138

1.11

381.

1138

Tun

is-P

aris

34.0

048

.87

9.00

2.33

6.67

-7.4

33.

330.

2735

0.27

350.

2735

Tun

is-

Was

h D

C34

.00

38.9

09.

00-7

7.04

86.0

4-2

.45

43.0

21.

1640

1.16

401.

1640

Nai

robi

-Lon

don

-1.2

851

.50

36.8

2-0

.12

36.9

3-2

6.39

18.4

71.

0702

1.07

021.

0702

Nai

robi

-New

Yor

k-1

.28

40.7

136

.82

-74.

0111

0.82

-21.

0055

.41

1 .85

871.

8587

1.85

87N

airo

bi -

Par

is-1

.28

48.8

736

.82

2.33

34.4

8-2

5.08

17.2

41.

0178

1.01

781.

0178

Nai

robi

- W

ash

DC

-1.2

838

.90

36.8

2-7

7.04

113.

85-2

0.09

56.9

31.

9057

1.90

571.

9057

Jobu

rg-L

ondo

n-2

6.20

51.5

028

.08

-0.1

228

.20

-38.

8514

.10

1.42

351.

4235

1.42

35Jo

burg

-New

Yor

k-2

6.20

40.7

128

.08

-74.

0110

2.09

-33.

4651

.04

2.01

582.

0158

2.01

58Jo

burg

-Par

is-2

6.20

48.8

728

.08

2.33

25.7

5-3

7.53

12.8

81.

3704

1.37

041.

3704

Jobu

rg-W

ash

DC

-26.

2038

.90

28.0

8-7

7.04

105.

12-3

2.55

52.5

62.

0481

2.04

812.

0481

7097

.948

317

42.8

094

7417

.643

5

1305

2.04

62

1184

5.42

3864

86.3

451

1214

4.96

3490

71.8

909

1284

6.06

7887

33.1

164

6820

.195

2

4229

.502

378

72.4

912

3931

.901

6

Est

imat

ed F

lyin

g D

ista

nce

(km

)

8140

.910

020

80.1

855

Δλ

ΔØ

/2Δλ/

2D

ista

nce

Øs

Øf

λ sλ f

ΔσE1

ΔσE2

ΔσE3

Journal statistique africain, numéro 14, mai 201296

Abdoulaye Adam

AN

NE

X 2

: OR

Th

OD

RO

MIC

DIs

TA

NC

Es

BE

TW

EE

N A

fRIC

AN

CA

PIT

Al

CIT

IEs

AN

D s

El

EC

TE

D D

EsT

INAT

ION

s

Des

tina

tion

Cai

roD

akar

jobu

rgN

airo

bi l

ondo

nW

ash-

ingt

on

DC

New

yo

rkTu

nis

Man

ila M

osco

wsa

ntia

goB

eiru

tPa

ris

Dep

artu

re P

oint

Alg

iers

- A

lger

ia27

03.3

831

79.0

7376

.653

97.2

1687

.068

77.9

6547

.968

2.1

1145

6.1

3367

.110

829.

529

78.9

1335

.6

Luan

da -

Ang

ola

4643

.25

4166

.725

41.6

2725

.966

85.1

1057

7.7

1034

5.0

4575

.812

125.

373

62.6

8948

.451

31.3

6318

.1

Cot

onou

- B

enin

4026

.59

2337

.345

05.9

3896

.550

09.4

8674

.784

24.5

3091

.112

880.

262

83.6

8808

.845

47.5

4670

.2

Gab

oron

e -

Bot

swan

a60

31.5

363

17.7

309.

728

14.4

8721

.612

710.

712

504.

365

71.4

1113

8.3

8855

.191

44.0

6419

.183

44.6

Oua

gado

ugou

-

Bur

kina

Fas

o39

25.2

317

25.8

5300

.544

74.5

4338

.579

25.9

7666

.025

93.0

1305

0.4

5864

.888

52.5

4427

.040

19.3

Buj

umbu

ra -

B

urun

di36

74.9

354

83.0

2561

.385

8.0

6624

.611

646.

011

358.

645

13.3

1026

1.4

6493

.810

747.

440

54.7

6248

.0

Yaou

ndé

- C

amer

oon

3651

.26

3394

.836

82.9

2847

.254

47.4

9675

.594

11.9

3342

.212

015.

662

41.9

9453

.541

65.7

5080

.2

Prai

s - C

ape

Ver

de58

61.5

666

6.7

7132

.468

46.8

4619

.258

80.0

5678

.839

50.4

1501

7.1

6912

.872

27.4

6291

.444

68.0

Ban

gui -

Cen

tral

A

fric

an R

epub

lic31

84.2

140

88.6

3489

.121

03.9

5508

.610

222.

099

39.5

3358

.111

232.

959

24.1

1016

8.0

3673

.551

31.2

Ndj

amen

a - C

had

2607

.63

4173

.344

53.5

2805

.445

49.4

9369

.390

73.7

2401

.511

355.

951

70.4

1032

9.1

3128

.041

73.3

Mor

oni -

C

omor

os47

36.6

772

34.8

2309

.013

19.7

8061

.613

399.

613

103.

660

58.8

9006

.273

57.8

1147

6.7

4961

.376

97.7

Kin

shas

a -

Con

-go

, Dem

. Rep

.41

44.4

4118

.127

98.3

2413

.362

90.0

1048

5.7

1023

4.2

4158

.711

804.

268

74.6

9380

.246

31.5

5918

.2

Bra

zzav

ille

-Con

go41

45.2

241

16.2

627

99.3

2415

.36

6289

.510

484

1023

2.57

4158

.45

1180

6.21

6875

.193

78.3

946

32.4

259

17.8

3

The African Statistical Journal, Volume 14, May 2012 97

3. An alternative approach for determining air transportation costs in the International Comparison Program

Des

tina

tion

Cai

roD

akar

jobu

rgN

airo

bi l

ondo

nW

ash-

ingt

on

DC

New

yo

rkTu

nis

Man

ila M

osco

wsa

ntia

goB

eiru

tPa

ris

Dep

artu

re P

oint

Abi

djan

-

Cot

e D

’ivoi

re46

24.8

117

68.1

4881

.92

4585

.38

5127

.881

79.2

679

50.5

534

16.2

813

590.

7966

83.5

581

65.3

151

39.0

148

19.7

9

Djib

outi

-

Djib

outi

2444

.95

6557

.12

4426

.57

1506

.66

5923

1175

8.67

1142

442

09.2

8416

.86

4916

.54

1287

4.6

2568

.02

5590

.64

Cai

ro -

Egy

pt0

5270

.86

6236

.25

3497

.24

3487

.494

09.6

490

68.6

720

81.5

192

08.3

828

25.7

212

776.

3652

2.72

3167

.98

Mal

abo

- E

quat

o-ri

al G

uine

a38

22.2

131

16.8

838

33.5

531

47.6

354

02.1

9436

.03

9179

.14

3336

.77

1230

7.36

6338

.06

9200

.86

4341

.750

41.5

6

Asm

ara

- E

ritr

ea18

43.4

760

40.6

947

08.5

1794

.18

5302

.411

120.

9810

786.

435

73.1

487

74.1

4449

.23

1270

7.94

2031

.23

4965

.04

Add

is A

baba

-E

thio

pia

2461

.82

6123

.04

4060

.111

32.3

258

6411

566.

2811

238.

8740

11.7

8934

.84

5115

.94

1234

8.05

2689

.49

5514

.34

Libr

evill

e - G

abon

4055

.84

3333

.98

3511

.89

3044

.557

42.6

9700

.06

9450

.93

3669

.44

1232

5.26

6629

.94

9078

.27

4570

.553

81.2

4

Ban

jul -

Gam

bia

5252

.25

138

6488

.56

6088

.99

4478

.865

45.4

463

24.5

234

58.1

414

458.

0565

88.7

957

07.9

157

07.9

142

67.8

1

Acc

ra -

Gha

na43

11.6

821

27.2

345

99.0

741

64.9

451

1585

13.3

882

73.6

632

72.9

413

190.

7365

02.6

685

07.9

948

31.0

347

87.5

3

Con

akry

-

Gui

nea

5210

.36

683.

8159

55.6

957

02.3

148

32.7

7067

.15

6853

.34

3577

.16

1439

5.8

6800

.55

7611

.34

5692

.04

4590

.55

Bis

sau

- G

uine

a-B

issa

u52

71.0

338

3.08

6260

.66

5945

.05

4665

.367

64.7

6549

3544

.07

1447

7.74

6719

.78

7602

.157

39.1

4441

.62

Nai

robi

- K

enya

3497

.24

6190

.21

2934

.25

067

49.9

1214

5.82

1183

8.75

4739

.91

9403

.56

6227

.35

1155

8.34

3783

.17

6383

.72

Mas

eru

- Le

soth

o65

72.6

567

83.6

133

8.19

3267

.192

99.1

1313

412

946.

2771

48.9

411

088.

4693

90.4

989

75.2

6945

.64

8922

.12

Mon

rovi

a -

Libe

ria

5139

.78

1141

.35

5496

.42

5342

.72

5100

.675

23.3

373

1236

65.2

714

247.

4169

31.7

776

40.7

256

38.6

148

33.9

7

Trip

oli -

Lib

ya17

33.7

736

88.4

6639

.07

4432

.55

2377

.579

07.8

375

76.1

735

9.88

1079

3.55

3193

.84

1136

3.53

2091

.11

1999

.73

Journal statistique africain, numéro 14, mai 201298

Abdoulaye Adam

The African Statistical Journal, Volume 14, May 2012 99

3. An alternative approach for determining air transportation costs in the International Comparison Program

Des

tina

tion

Cai

roD

akar

jobu

rgN

airo

bi l

ondo

nW

ash-

ingt

on

DC

New

yo

rkTu

nis

Man

ila M

osco

wsa

ntia

goB

eiru

tPa

ris

Dep

artu

re P

oint

Ant

anan

ariv

o -

Mad

agas

car

5615

.19

7951

.09

2193

.46

2223

.389

64.5

1423

1.41

1394

7.17

6960

.288

00.4

581

71.4

311

338.

3158

13.4

186

01.3

9

Lilo

ngw

e -

Mal

awi

4789

.08

6380

.41

1564

.89

1375

.54

7837

.412

708.

7612

440.

3157

26.0

310

058.

2775

69.8

510

517.

8551

18.2

7461

.1

Bam

ako

- M

ali

4507

.88

1035

.27

5749

.58

5154

.95

4395

7359

.52

7116

.69

2939

.28

1369

1.55

6199

.783

00.7

249

92.6

741

17.0

7

Nou

akch

ott -

M

auri

tani

a49

42.9

246

7.75

6823

.94

6146

.66

3927

.762

74.9

760

31.0

830

42.3

814

103.

660

90.0

481

07.1

753

71.6

637

26.7

3

Port

Lou

is -

M

auri

tius

6229

.390

10.4

930

80.0

830

85.7

396

83.3

1522

014

919.

5977

87.3

179

01.9

385

50.5

511

946.

0863

39.7

493

36.2

4

Cas

abla

nca

- M

oroc

co36

76.1

123

31.8

275

65.9

759

90.1

420

91.6

6164

.67

5851

.37

1594

.85

1245

9.09

4255

.49

9861

.79

3988

.19

1863

.84

Map

uto

- M

ozam

biqu

e61

17.3

769

33.5

246

8.6

2707

.14

9038

.813

343.

3513

123.

9168

95.6

310

501.

3589

08.5

696

42.5

764

56.6

886

60.3

1

Win

dhoe

k -

Nam

ibia

5977

.27

5486

.59

1198

.75

3164

.81

8290

.611

836.

2411

645.

5861

67.9

311

992.

2287

82.1

384

90.1

764

20.3

679

21.3

8

Nia

mey

- N

iger

3540

.44

2104

.89

5165

.33

4131

.66

4230

.381

79.3

7907

.62

2348

.21

1264

2.01

5589

.28

9236

.19

4047

.77

3891

.89

Lago

s -

Nig

eria

3951

.31

2435

.844

42.4

637

91.0

250

14.4

8759

.68

8506

.98

3068

.76

1277

8.49

6241

.47

8896

.55

4472

.98

4671

.24

Kig

ali -

Rw

anda

3449

.36

5478

.15

2788

.21

751.

3364

46.1

1156

7.1

1127

3.18

4349

.95

1013

2.39

6265

.14

1093

5.31

3823

.39

6070

.77

Sao

Tom

e -

Sa

o To

me

And

Pr

inci

pe

4226

.41

3071

.95

3685

.58

3347

.457

07.7

9461

.55

9219

.67

3681

.21

1261

7.83

6728

.888

25.5

847

45.7

153

54.0

7

Dak

ar -

Sen

egal

5270

.86

066

23.7

543

95.4

6190

.264

13.5

561

90.8

3441

1446

8.88

6540

.11

7693

.21

5719

.07

4193

.37

Journal statistique africain, numéro 14, mai 201298

Abdoulaye Adam

The African Statistical Journal, Volume 14, May 2012 99

3. An alternative approach for determining air transportation costs in the International Comparison Program

Des

tina

tion

Cai

roD

akar

jobu

rgN

airo

bi l

ondo

nW

ash-

ingt

on

DC

New

yo

rkTu

nis

Man

ila M

osco

wsa

ntia

goB

eiru

tPa

ris

Dep

artu

re P

oint

Vic

tori

a -

Seyc

helle

s45

74.4

782

68.2

838

08.5

520

96.4

180

61.8

1390

1.76

1356

9.86

6342

.23

7494

.76

6762

.92

1300

9.59

4619

.86

7736

.59

Free

tow

n -

Sier

ra

Leon

e52

30.5

380

3.52

5844

.67

5637

.38

4931

.171

74.8

769

63.6

336

34.9

714

400.

3268

71.2

275

76.3

157

17.1

4683

.94

Joha

nnes

burg

So

uth

Afr

ica

6236

.25

5844

.67

5844

.67

5844

.67

4931

.171

74.8

769

63.6

336

34.9

714

400.

3268

71.2

275

76.3

157

17.1

4683

.94

Kha

rtou

m

- Sud

an16

73.0

853

57.8

345

84.7

518

40.4

749

51.2

1061

7.51

1028

9.63

3062

.32

9444

.76

4469

.37

1211

3.41

2023

.72

4594

.38

Mba

bane

-

Swaz

iland

6226

.93

6874

.41

308.

4128

45.7

490

94.4

1327

5.52

1306

4.32

6946

.98

1066

8.22

9028

.06

9459

.62

6576

.72

8716

Dar

Es

Sala

am

-Tan

zani

a40

93.4

566

28.4

2523

.08

619.

0273

68.9

1271

0.6

1241

0.13

5352

.67

9279

.26

6784

.62

1146

0.58

4354

.88

7002

.69

Lom

é - T

ogo

4122

.23

2215

.25

4587

.28

4028

.53

5005

.385

68.4

783

21.5

131

23.3

513

007.

163

37.3

986

99.5

146

41.9

946

71.4

4

Tuni

s - T

unis

ia20

71.2

3671

.571

44.9

749

53.2

118

58.9

7434

.39

7099

.59

338.

5210

880.

3329

70.3

611

361.

123

38.3

1480

.53

Kam

pala

-

Uga

nda

3338

.83

5707

.89

2931

.68

483.

964

52.2

1171

3.4

1141

2.13

4390

.94

9833

.36

6132

.93

1123

0.4

3682

.160

80.1

9

Lusa

ka-

Zam

bia

5013

.84

5964

.212

23.4

1816

.82

7841

.312

357.

1712

109.

0756

96.9

710

686.

8978

33.2

799

03.8

153

92.0

474

62.7

8

Har

are

- Z

imba

bwe

5226

.263

31.7

310

47.8

418

87.5

981

48.5

1272

6.97

1247

9.07

6011

.52

1044

9.52

8030

.110

022.

2855

79.7

577

70.2

9

* D

ista

nce

betw

een

citi

es in

kilo

met

ers.

Journal statistique africain, numéro 14, mai 2012100

Abdoulaye Adam

The African Statistical Journal, Volume 14, May 2012 101

3. An alternative approach for determining air transportation costs in the International Comparison Program

AN

NE

X 3

: PE

R K

IlO

ME

TE

R P

RIC

Es

IN U

s$ f

OR

AN

EC

ON

OM

y C

lA

ss y

, ON

E-W

Ay T

ICK

ET

fR

OM

AfR

ICA

N

CA

PIT

Al

CIT

IEs

TO

sE

lE

CT

ED

Ch

OsE

N D

EsT

INAT

ION

s2

Des

tina

tion

Cai

roD

akar

jobu

rgN

airo

bi l

ondo

nW

ash-

ingt

on

DC

New

yo

rkTu

nis

Man

ila M

osco

wsa

ntia

goB

eiru

tPa

ris

Dep

artu

re

Alg

iers

- A

lger

ia0.

344

0.72

00.

385

0.17

40.

615

0.16

90.

168

0.28

30.

114

0.19

20.

199

0.45

90.

362

Luan

da-A

ngol

a0.

229

0.53

40.

279

1.43

90.

502

0.46

70.

364

0.25

80.

107

0.17

10.

405

0.19

10.

404

Cot

onou

-Ben

in0.

168

1.33

50.

457

0.38

70.

604

0.38

90.

400

0.78

10.

247

0.43

70.

823

0.61

70.

527

Gab

oron

e -

Bot

swan

a0.

103

0.20

00.

478

0.22

40.

236

0.22

60.

227

0.34

90.

251

0.27

20.

216

0.23

80.

173

Oua

gado

ugou

-

B. F

aso

0.11

70.

285

0.44

50.

492

0.69

70.

126

0.07

90.

129

0.20

50.

468

0.43

20.

127

0.61

3

Buj

umbu

ra -

B

urun

di0.

277

0.18

20.

309

0.52

30.

245

0.08

60.

143

0.59

20.

213

0.18

50.

609

0.16

80.

188

Yaou

ndé

- C

amer

oon

0.53

70.

906

0.48

40.

515

0.27

70.

284

0.12

50.

479

0.31

10.

164

0.84

30.

145

0.46

3

Prai

s -

Cap

e V

erde

0.65

50.

336

0.17

60.

283

0.65

10.

289

0.17

30.

379

0.46

70.

113

0.22

30.

131

0.16

0

Ban

gui -

C A

r1.

409

0.18

20.

200

1.73

00.

511

0.40

30.

415

0.13

10.

493

0.55

20.

436

1.06

80.

562

Ndj

amen

a - C

had

0.23

90.

348

0.18

20.

451

0.66

00.

394

0.40

71.

312

0.24

50.

609

0.41

90.

926

0.63

0

Mor

oni -

C

omor

os0.

365

0.27

20.

487

0.52

10.

274

0.42

40.

175

0.38

30.

808

0.44

20.

310

0.49

30.

125

2 A

ir F

ares

wer

e ob

tain

ed fr

om th

e IC

P G

loba

l Offi

ce th

roug

h th

e W

orld

Ban

k Tr

avel

Age

ncy

Journal statistique africain, numéro 14, mai 2012100

Abdoulaye Adam

The African Statistical Journal, Volume 14, May 2012 101

3. An alternative approach for determining air transportation costs in the International Comparison Program

Des

tina

tion

Cai

roD

akar

jobu

rgN

airo

bi l

ondo

nW

ash-

ingt

on

DC

New

yo

rkTu

nis

Man

ila M

osco

wsa

ntia

goB

eiru

tPa

ris

Dep

artu

re

Kin

shas

a -

Con

go, D

em.

Rep

.

0.18

10.

349

0.86

90.

646

0.56

70.

114

0.32

60.

399

0.13

00.

383

0.43

10.

961

0.42

9

Bra

zzav

ille

- C

ongo

0.18

10.

345

0.76

60.

523

0.19

10.

095

0.35

30.

387

0.48

60.

529

0.45

70.

641

0.51

1

Abi

djan

- C

ote

D’iv

oire

0.32

90.

492

0.46

10.

389

0.21

50.

413

0.42

40.

706

0.13

00.

172

0.63

10.

217

0.65

3

Djib

outi

-

Djib

outi

0.16

30.

198

0.12

50.

200

0.11

20.

085

0.12

40.

352

0.28

40.

389

0.29

20.

144

0.12

3

Cai

ro -

Egy

pt0.

000

0.44

30.

109

0.12

00.

137

0.07

40.

053

0.09

20.

153

0.82

80.

382

0.41

70.

306

Mal

abo

-

E. G

uine

a0.

221

0.46

10.

384

0.46

70.

689

0.10

60.

237

0.88

40.

352

0.62

00.

535

1.02

30.

797

Asm

ara

- E

ritr

ea1.

323

0.15

60.

266

2.69

10.

330

0.20

10.

207

0.58

70.

203

0.51

60.

435

0.35

90.

219

Add

is A

baba

-

Eth

iopi

a0.

195

0.23

20.

151

0.40

60.

102

0.07

80.

101

0.17

40.

140

0.29

00.

350

0.23

40.

109

Libr

evill

e -

Gab

on0.

315

0.27

00.

615

0.42

00.

623

0.33

10.

340

0.42

40.

363

0.56

10.

864

0.91

80.

633

Ban

jul -

Gam

bia

0.17

81.

014

0.16

40.

305

0.17

20.

356

0.29

80.

287

0.24

70.

361

0.65

00.

166

0.42

0

Acc

ra -

Gha

na0.

181

0.40

00.

306

0.30

00.

205

0.27

30.

285

0.21

10.

121

0.34

40.

502

0.10

50.

380

Journal statistique africain, numéro 14, mai 2012102

Abdoulaye Adam

The African Statistical Journal, Volume 14, May 2012 103

3. An alternative approach for determining air transportation costs in the International Comparison Program

Des

tina

tion

Cai

roD

akar

jobu

rgN

airo

bi l

ondo

nW

ash-

ingt

on

DC

New

yo

rkTu

nis

Man

ila M

osco

wsa

ntia

goB

eiru

tPa

ris

Dep

artu

re

Con

akry

-

Gui

nea

0.32

10.

781

0.21

40.

184

0.16

60.

392

0.40

80.

641

0.22

50.

494

0.47

10.

583

0.62

3

Bis

sau

- G

uine

a-B

issa

u0.

434

0.44

90.

429

0.40

20.

354

0.53

00.

545

0.27

60.

077

0.37

60.

390

0.54

10.

375

Nai

robi

- K

enya

0.24

40.

204

0.34

70.

000

0.20

30.

232

0.09

60.

197

0.12

70.

157

0.23

40.

219

0.14

4

Mas

eru

- Les

otho

0.15

20.

256

0.63

00.

306

0.29

50.

348

0.35

30.

425

0.34

40.

324

0.40

10.

094

0.22

9

Mon

rovi

a -

Libe

ria

0.22

11.

165

0.14

60.

129

0.35

50.

281

0.29

70.

752

0.26

40.

201

1.06

90.

223

0.27

1

Trip

oli -

Lib

ya0.

174

0.13

50.

136

0.19

70.

314

0.41

20.

569

0.35

30.

125

0.29

40.

333

0.25

00.

355

Ant

anan

ariv

o -

Mad

agas

car

0.33

20.

252

0.22

30.

416

0.33

60.

389

0.39

70.

176

0.74

10.

331

0.45

30.

446

0.20

4

Lilo

ngw

e -

Mal

awi

0.30

50.

161

0.52

70.

536

0.42

70.

151

0.15

50.

318

0.31

20.

275

0.35

40.

159

0.16

7

Bam

ako

- M

ali

0.17

90.

239

0.33

90.

353

0.65

10.

469

0.48

50.

230

0.43

00.

509

0.45

00.

749

0.68

9

Nou

akch

ott -

M

auri

tani

a0.

166

0.62

90.

274

0.22

30.

661

0.39

60.

412

0.07

50.

272

0.44

60.

709

0.17

30.

514

Port

Lou

is -

M

auri

tius

0.24

20.

069

0.13

60.

488

0.18

70.

238

0.18

00.

172

0.14

40.

176

0.28

50.

242

0.14

7

Cas

abla

nca

- M

oroc

co0.

113

0.48

00.

457

0.13

80.

341

0.12

50.

110

0.10

00.

083

0.33

50.

414

0.29

20.

500

Map

uto

- M

ozam

biqu

e0.

113

0.05

90.

361

0.09

00.

355

0.25

80.

153

0.09

00.

309

0.25

30.

437

0.11

60.

170

Journal statistique africain, numéro 14, mai 2012102

Abdoulaye Adam

The African Statistical Journal, Volume 14, May 2012 103

3. An alternative approach for determining air transportation costs in the International Comparison Program

Des

tina

tion

Cai

roD

akar

jobu

rgN

airo

bi l

ondo

nW

ash-

ingt

on

DC

New

yo

rkTu

nis

Man

ila M

osco

wsa

ntia

goB

eiru

tPa

ris

Dep

artu

re

Win

dhoe

k -

Nam

ibia

0.17

40.

096

0.21

30.

306

0.21

00.

330

0.31

90.

636

0.29

50.

521

0.33

90.

717

0.18

7

Nia

mey

- N

iger

0.32

80.

301

0.34

30.

559

0.75

30.

436

0.43

80.

131

0.24

90.

527

0.40

40.

319

0.59

9

Lago

s -

Nig

eria

0.20

20.

263

0.19

60.

360

0.31

00.

181

0.18

60.

269

0.08

60.

148

0.19

50.

112

0.25

3

Kig

ali -

Rw

anda

0.16

80.

305

0.34

80.

261

0.18

60.

086

0.14

40.

485

0.75

70.

180

0.06

40.

177

0.35

4

Sao

Tom

e -

Stp

0.51

80.

952

0.38

20.

488

0.41

30.

593

0.43

01.

212

0.32

00.

145

0.51

30.

320

0.75

8

Dak

ar -

Sen

egal

0.21

20.

000

0.25

70.

480

0.41

90.

155

0.16

00.

103

0.07

00.

312

0.83

30.

432

0.46

5

Vic

tori

a -

Seyc

helle

s0.

247

0.15

70.

205

0.25

20.

161

0.11

00.

113

0.28

40.

096

0.08

50.

161

0.11

30.

190

Free

tow

n -

Sier

ra L

eone

0.32

00.

266

0.18

60.

396

0.23

70.

583

0.58

50.

172

0.21

90.

298

0.96

40.

159

0.36

7

Joha

nnes

burg

So

uth

Afr

ica

0.12

60.

260

0.00

00.

100

0.26

70.

605

0.62

30.

274

0.24

90.

152

0.29

60.

316

0.34

3

Kha

rtou

m

-Sud

an0.

130

0.27

50.

089

0.32

60.

147

0.07

30.

076

0.20

30.

926

0.17

10.

260

0.24

60.

242

Mba

bane

-

Swaz

iland

0.15

70.

249

0.61

90.

332

0.28

30.

279

0.26

90.

077

0.34

90.

302

0.25

80.

292

0.21

0

Dar

Es

Sala

am

-Tan

zani

a0.

161

0.16

50.

331

0.52

30.

183

0.07

10.

067

0.09

10.

141

0.21

50.

262

0.08

20.

070

Lom

é - T

ogo

0.28

20.

349

0.26

40.

486

0.18

20.

117

0.40

50.

774

0.25

30.

434

0.60

40.

170

0.52

8

Tuni

s Tun

isia

0.09

50.

162

0.30

80.

181

0.19

80.

302

0.27

40.

000

0.06

40.

233

0.25

40.

071

0.06

7

Journal statistique africain, numéro 14, mai 2012104

Abdoulaye Adam

The African Statistical Journal, Volume 14, May 2012 105

Des

tina

tion

Cai

roD

akar

jobu

rgN

airo

bi l

ondo

nW

ash-

ingt

on

DC

New

yo

rkTu

nis

Man

ila M

osco

wsa

ntia

goB

eiru

tPa

ris

Dep

artu

re

Kam

pala

-

Uga

nda

0.16

10.

169

0.29

60.

558

0.11

20.

071

0.07

30.

213

0.13

40.

233

0.59

10.

177

0.06

8

Lusa

ka-

Zam

bia

0.35

20.

103

0.31

50.

455

0.14

50.

119

0.11

40.

471

0.36

30.

133

0.26

00.

136

0.11

1

Har

are

- Z

imba

bwe

0.08

60.

082

0.30

30.

352

0.15

10.

278

0.28

30.

422

0.27

30.

340

0.24

30.

116

0.09

6