Winners or Losers? The “new” East African Community: Welfare implication of Regional Trade Agreement in East Africa

Winners or Losers?

The “new” East African Community: Welfare

implication of Regional Trade Agreement in East

Africa

By

Abraham Girma Nida

Jacobs University Bremen Universität Bremen

MA thesis for conferral of a Master of Arts degree in International Relations: Global Governance and Social Theory

Supervisor: Prof. Dr. Welf Werner Second Supervisor: Prof. Dr. Peter Mayer

July – 2011

School of Humanities and Social Sciences

i

Acknowledgments

I would like to express my at most appreciation and gratitude to all individuals and

organizations that supported me in realizing this MA thesis project. Specially, I would like to

thank the whole MAIR 2011 team, friends and colleagues at Jacobs University/University of

Bremen for their support, useful feedbacks and comments regarding my research. I would also

like to thank my direct supervisor Prof. Dr. Welf Werner for his insightful comments and

advice without those the projects would not have been realized. Also a special thanks to Mr.

Alessandro Nicita and Mr. Hiroaki Kuwahara from the Trade Information Section of

UNCTAD for their support regarding the WITS/SMART simulations. I am also indebted to

Heinrich Böll Stiftung for its financial support and ideal stipend throughout my Masters

study. But most importantly I would like to thank my family for being there for me

unconditionally and to my little daughter Zoe; you are my source of resilience!

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Abstract

In recent years, the international economic order seems to be rapidly changing. Until the

early 1990s, multilateralism was dominant form of trading system and regionalism remained

marginal. But, since the end of the Uruguay Round, the world trading system has experienced

the emergence of a large group of regional blocs. On this regard, African is no exception. It is

a region with the most regional organizations in the world. Among the well established

regional integration arrangements (RTAs) in Africa, the East African Community (EAC) is

the most interesting one. It was first established almost a hundred years ago but collapsed in

1977 for political and economic reasons. Then it was re-established in 1999 with a final aim

of creating a federation of States in East Africa. Recently it has succeeded in setting up a

custom union among member states and this MA thesis investigates the static welfare gains

from the re-establishment of the EAC. The research applies both descriptive statistic (Ex-post)

and WITS/SMART trade simulation (EX-Ante) model analyses to investigate trade diversion

and Trade Creation effects of RTA formation in Eastern Africa. The results from both

analyses demonstrate that there are trade gains from the establishment of EAC. The regional

trade arrangement seems to promote intra-regional trade and more importantly intra-

industrial trade hence encouraging industrialization in the region. Furthermore, the

empirical investigation portrays that Kenya benefits the most out of the regional trade

arrangement as EAC will expand markets for Kenya’s manufactured good exports.

Keywords: East Africa Community, Trade Creation, Trade Diversion, Regional Trade

Arrangement, Custom Union

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Declaration of Authenticity I hereby confirm that I wrote this thesis independently based on my own study of the cited materials only. Bremen, 26th July 2011

Abraham Girma Nida

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Table of Contents

Acknowledgments......................................................................................................i Abstract.....................................................................................................................ii Declaration of Authenticity......................................................................................iii List of Tables............................................................................................................vi List of figures...........................................................................................................vii List of Abbreviation .................................................................................................vii

Chapter I

Introduction

1.1 Brief overview of the East African Community ................................................................................. 3

1.2 Objective, Research Question and Methodology of the Thesis ...................................................... 10

1.3 Preliminary Results .......................................................................................................................... 13

Chapter II

Literature Review

2.1 Theories of Regional Integration.....................................................................................................15

2.2 Theory of trade creation and trade diversion ................................................................................. 22

2.2.1 Trade Creation .......................................................................................................................... 24

2.2.2 Trade Diversion ........................................................................................................................ 25

2.3 Similar studies on welfare analysis concerning the EAC ................................................................. 26

Chapter III

Descriptive Statistics Analysis

3.1 Tariff Regimes in EAC and Common External Tariffs (CET) ............................................................. 32

3.2 Trade patterns, Direction, composition and Intensity in the EAC ................................................... 37

3.2.1 Compositions of Exports and Imports in EAC & Revealed Comparative Advantage (RCA)

analysis .............................................................................................................................................. 41

3.2.1.1 Revealed Comparative advantage analysis of EAC.................................................................... 44

3.2.2 Trade Intensity in EAC .............................................................................................................. 46

3.3 Dynamic welfare gains .................................................................................................................... 49

3.3.1 Expansion ................................................................................................................................. 49

3.3.2 Peace and Security ................................................................................................................... 51

3.4 Discussion .................................................................................................................................... 52

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Chapter IV

A Partial Equilibrium Model welfare analysis

4.1 The partial equilibrium approach and WITS/SMART analysis ......................................................... 54

4.1.1 The WITS/SMART simulation ................................................................................................ 55

4.2 Results of the simulation ................................................................................................................. 58

4.2.1 Kenya ........................................................................................................................................ 58

4.2.2 Uganda ..................................................................................................................................... 62

4.2.3 Tanzania .................................................................................................................................... 64

4.3 Discussion .............................................................................................................................67

Chapter V

Conclusion..........................................................................................................................69

Reference............................................................................................................................73

Appendix I...........................................................................................79

Appendix II..........................................................................................80

Appendix III……………………………………………....………......85

Appendix IV..........................................................................................97

Appendix V.........................................................................................139

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List of Tables

Table 1.1 East African Community timeline..............................................................................7

Table 3.1 Tariff Changes within EAC......................................................................................20

Table 2.1 Shares of Intra-Regional Exports in Total Exports of EAC Countries, 1970-97…..21

Table 2.2 Trade pattern between Kenya, Uganda and Tanzania (2003)……………………...33

Table 3.2 Tariff Changes on imports from EU-27....................................................................35

Table 3.3 Trade flows for EAC, 2003-2007 in US $Millions…………………………….…..37

Table 3.4 Overlapping RTA membership by member states in East Africa……………….…38

Table 3.5 Intra-EAC trade 2005-2008 (US$ Millions)……………………………………….39

Table 3.6 Regional Trade by Commodity composition 2009 in (1000 US$)……………...…42

Table 3.6 Regional Trade by Commodity composition 2009 in (1000 US$)……………...…48

Table 4.1 Tariff reduction simulation results for Kenya………………………………….......59

Table 4.2 Kenya Trade Creation and Trade Diversion Effects (disaggregated) ……………..60

Table 4.3 Tariff reduction simulation results for Uganda………………………………….....62

Table 4.4 Uganda Trade Creation and Trade Diversion Effects (disaggregated)…………….63

Table 4.5 Tariff reduction simulation results for Tanzania…………………………………...65

Table 4.6 Tanzania Trade Creation and Trade Diversion effects (disaggregated)…………...66

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List of Figures

Figure 1.1 Map of the original three members of the EAC........................................................8

Figure 2.1 Trade Creation.........................................................................................................24

Figure 2.2 Trade Diversion.......................................................................................................26

Figure 3.1 Net barter terms of trade index (2000 = 100) for Uganda.......................................36

Figure 3.2 Intra-EAC trade 2005-2008 (US$ Millions)………………………………………40

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List of Abbreviations

APEC East Pacific Economic Cooperation

CET Common External Tariff

COMESA Common Market for Eastern and Southern Africa

DRC Democratic Republic of Congo

CU Custom Union

EADB East African Development Bank

EFTA European Free Trade Area

EPA Economic Partnership Agreement

EU European Union

FTA Free Trade Agreement

GDP Gross Domestic Product

GATT General Agreement on Trade and Tariff

GTAP Global Trade Analysis Project

IMF International Monetary Fund

IUCEA Inter University Council for East Africa

LVFO Lake Victoria Fisherie Organization

Mercosor Economic and Political cooperation agreement in South America

NAFTA North American Free Trade Area

PTA Preferential Trade Agreement

RTA Regional Trade Agreement

SACU Southern Africa Custom Union

SPS Sanitary and Phytosanitary measures

UNECA United Nations Economic Commission for Africa

TBT Technical Barrier to Trade

WITS World Integrated Trade Software

WTO World Trade Organization

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Chapter I: Introduction

Regional trading arrangements are occupying a significant portion of the recent world

trading system. Since the end of the Uruguay Round, the world trading system has

experienced the emergence of a large group of regional blocs ranging from the NAFTA and

the Mercosur to the APEC and significant enlargements of the EU. Some latest figures show

up to 60% of the total world trade takes place within regional trade blocs or arrangements

(Khorana, Kimbugwe & Perdikis 2008). Economic experts on this matter proposed variety of

explanations for this current trend of regionalization that seems to spread like a “wide fire”

(Baldwin 1997, Winters 1996, Krugman 1991, Bhagwati 1993, Grossman & Helpman 1992,

Baier et.al 2007). Some mention the high costs of multilateral trading system as reasons while

others employ political economy models of market forces to explain the current trend.

Whatever the case, it’s an undeniable fact that regional trading blocs are becoming pertinent

issues that needs to be dealt with.

On this regard, African is no exception. Africa is the region with the most regional

organizations in the world. The number of the organizations admitted by African Union has

reached 8, including Arab Maghreb Union, East African community (EAC), Economic

Community of West African States, Southern African Development Community, Community

of Sahel - Saharan States, Inter-Governmental Authority on Development, Common Market

for Eastern and Southern Africa, Economic Community of Central African States. In addition,

there are other six organizations that deal with regional cooperation. One of the unique

features of regionalism in Africa is fact that many African nations belong to overlapping

regional organizations that sometimes have diverging interests. It is also true that most of the

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regional integration projects in Africa fail to attain a deep integration, higher intra-regional

trade and liberalization in the flow of goods, labor, service and capital.

The East African Community is among these persistent ventures of regional blocs in

Africa that aim to establish the highest form of integration i.e. political federation through

some gradual stages of integration. From the conventional regional integration theories we

know that regional trade arrangements can take a form of Free Trade Area (FTA), Preferential

Trade Area (PTA), custom union or even a deep integration where countries will form a

common market, economic union and political federation. In the case of shallow integration,

countries form FTAs and PTAs to eliminate barriers and liberalize trade among members.

Whereas, custom unions go one step further as they not only aim to reduce internal tariffs but

also set Common External Tariffs on imports from non-member states. As the integration

process deepens member states can sign treaties to establish a common market. common

market extends custom unions to allow for free movement of factors of production such as

labor and capital. The most advanced forms of integration, economic and political union

permits free factor mobility, harmonization of economic policy, common currency and in

some theoretical cases to political union. And the EAC aims to run the whole distance.

Accordingly, a regional integration protocol was signed in 1999 by the original partner

states of the “new” East Africa Community, Kenya, Uganda and Tanzania to establish a

regional organization. The Republic of Burundi and the Republic of Rwanda acceded to this

East African Community on 18th June 2007 and became full members of the Community

since 1st July 2007. The treaty to establish the East African Community (EAC) envisaged

integration a bit differently than what Balassa (1961) outlined as stages of regional economic

integration. The process of integration will progress from a custom union to a common market

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then a monetary union and ultimately a political Federation1. Hence, the time plan was to

form a Custom Union by 2005 skipping one phase of the conventional stages of regional

integration i.e. the formation of Free Trade Area (FTA). On the 1st of January 2010, EAC's

full-fledged customs union has taken effect following the end of a five-year transitional

period. In the coming few years the organization plans to establish common currency,

common market and eventually a political federation. With the successful establishment of a

custom union in 2010, it is an ideal time to analyze the welfare effects of the formation of the

East African Community Custom Union (EAC-CU). Also assessing the benefits of the

regional organization. On this regard, this thesis will investigate the welfare implications of

the formation of a Custom Union on the three original partner states of EAC (Kenya, Uganda

and Tanzania).

The introductory chapter will proceed by giving a brief description of the East African

Community. Then, I will outline my objectives in undertaking this study together with the

research question and methodology. Thereafter, I will conclude the chapter by providing the

preliminary result of entire study.

1.1 Brief overview of the East African Community

The recently resurrected East African Community is partly a relic of the historical

integration project that was erected in the early 20th century. It began as a colonial project to

integrate the colonies of England (Kenya, Uganda and Tanzania) in East Africa under

coordinated and cooperative administrations (Detter Delupis 1970). At the beginning Kenya

and Uganda established a Custom Union in 1917 making tariff administration relatively easier

as goods flow freely across the borders. Common external tariff was also applied on goods

from external sources to strengthen the Custom Union and bilateral trade (Ng’ang’a 2006).

1 Article 5(2) of the EAC Treaty 1999 states the ultimate goal of the regional setup.

4

Tanzania also joined the customs union in 1927 making the East African Community a full

regional trading bloc (Ng’ang’a 2006). This historical economic cooperation has resulted in

the formation of many regional and shared institutions, infrastructures and ties that lasted till

the independence of the three nations in the 1960’s.

After independence, The East African Community is properly launched in 1967 with a

signing of a treaty among the three member states. It took over nearly the entire range of joint

services institutions belonging to the former EACSO, comprised of six major administrative

organs: 1) East African Authority, 2) Committee of East African Ministers, 3) Secretariat, 4)

East African Legislative Assembly, 5) Ministerial Councils (five), and 6) East African

Developmental Bank (Katembo 2008). According to the treaty the objective of the

organization was:

“Strengthen and regulate industrial, commercial and other

relations to promote harmonious and balanced development of

economic activities where the benefits whereof shall be

equitably shared” (Ng’ang’a 2006:7).

There are many explanations as to why these countries decided to form the regional

organization right after independence. On way of looking at this phenomenon could be the

historical ties that pre-existed that facilitated further economic and political cooperation after

liberation. Others also put forward the ideology of Pan-Africanism as a central force driving

the process regional integration (Ngambi & Katembo 2006, Katembo 2008). Katembo

(2008), for example, states the role of former Tanzanian President Julius Nyerere (1922-1999)

in crystallizing the formation the EAC as part of his Pan-African ideology to unite the whole

of Africa by firstly uniting small fragmented states into regional blocs (Katembo 2008). He

was even willing to delay the independence of Tanganyika (later known as Tanzania) for the

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sake of united political entity comprised of the Kenya, Uganda and Tanganyika (Mwakikagile

2006). Tanganyika and Zanzibar was successful joined to form Tanzania, but immediate

political union with Kenya and Uganda was not successful at that time. However, this move

has led to the signing of the Treaty for the East African cooperation in 1967 (Mwakikagile

2006).

Later in 1977, The “Old” East African Community crumbled due to variety of

economic and political reasons. Some of the issues include; lack of political will, insufficient

information distribution and confederation concept buy-in amongst tri-state rank & file

citizenry, inequitable fiscal redistribution of gains, inter-territorial imbalances in trade,

currency system disharmony and constitutional impediments (Katembo 2008). But the final

blow came with Idi Amin Dada’s seizure of power in Uganda by overthrowing the Obote

regime. This exacerbated regional tensions and strained political communication amongst the

tri-partner governments. “Adding fuel to fire, President Amin’s egomaniacal personality,

bullying, confrontational theatrics, and open assertion that power in East Africa revolved

around him created a hostile political climate for meetings of the East African Authority - the

main body that helped keep the territorial administrative structure operational; as a result, the

East African Authority ceased meetings and operation in 1971” (Katembo 2008: 110). Soon,

the demise of the 10-year old organization was culminated in June 1977 when the partner

states withheld approval for the general fund services budget for the year beginning July 1,

1977.

The period after the demise of the “old” East African Community is said to have been

a difficult period for Kenya, Uganda and Tanzania. The oil crisis in the 1970’s and structural

adjustments programs in the 80’s has seriously affected the economies of the member states

and led to slumped economy in all of the three states (Ng’ang’a 2006). Following the

dissolution of the former East African Community in 1977, the member states negotiated a

6

mediation agreement for the division of assets and liabilities, which they signed in 1984.

However, as one of the provisions of the mediation agreement, the three States agreed to

explore areas of future co-operation and to make concrete arrangements for such co-operation.

Subsequent meetings of the three Heads of State led to the signing of the agreement for the

establishment of the permanent tripartite commission for East African Co-operation on

November 30, 1993. Full East African Co-operation operations started on March 14, 1996

when the Secretariat of the Permanent Tripartite Commission was launched at the

headquarters of the EAC in Arusha, Tanzania. Considering the need to consolidate regional

co-operation, the East African heads of state, at their 2nd Summit in Arusha on 29 April 1997,

directed the permanent tripartite commission to start the process of upgrading the agreement

establishing the permanent tripartite commission for East African Co-operation into a Treaty.

The treaty-making process, which involved negotiations among the member states as

well as the wide the public, was successfully concluded within 3 years. The treaty for the

Establishment of the East African Community was signed in Arusha on 30th of November

1999. The Treaty entered into force on 7th of July 2000 following the conclusion of the

process of its ratification and deposit of the instruments of ratification with the secretary

general by all the tree partner states (Eat African Community 2011).

The Treaty also established The EAC's main institutions; the Summit of Heads of

State and/or Government; Council of Ministers; Coordination Committee; sectoral

committees; East African Court of Justice; East African Legislative Assembly; and the

Secretariat (based in Arusha, Tanzania). In addition, the EAC Protocol established the

Committee on trade remedies to handle: rules of origin; contingency trade remedies; dispute

settlement mechanism; and any other matter referred to it by the Council. The EAC currently

has the following autonomous institutions: Lake Victoria Development Programme; the East

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African Development Bank (EADB); Lake Victoria Fisheries Organization (LVFO); and the

Inter-University Council for East Africa (IUCEA).

Table 1.1 East African Community timeline

Year Event

1917 Kenya and Uganda form a customs union

1927 Tanzania joins customs union and common external tariff is in place

1931 Kenya-Uganda railway opened as major inter-territorial service

1948 Inter-territorial co-operation formalized with East African High Commission

1962 Uganda gains independence from Britain

1963 Kenya gains independence from Britain

1964 Tanzania (formerly Tanganyika) gains independence from Britain

1967 Treaty for East African co-operation signed and EAC formed

1971-1985 Uganda goes through a period of civil unrest and political instability

1977 East African Community is dissolved

1996 Launching of the Tripartite commission for East African Co-operation

1999 Treaty for the establishment of the EAC is signed

2001 EAC officially inaugurated in January with headquarters in Arusha, Tanzania

2005 Establishment of the EAC customs union & Introduction of common

external tariff (CET)

Source: Na’ang’a (2006)

The current thesis will analyze this latest attempt to establish a regional integration

arrangement which will be from now on referred to as the “new” East African Community.

As already mentioned I will investigate the welfare gains from trade as a result of the

establishment of custom union between the original three members, Kenya, Uganda and

Tanzanian. I acknowledge that the Republic of Rwanda and the Republic of Burundi acceded

8

to the organization on the 18th of June 2007. Taking into consideration the fact that Rwanda

and Burundi acceded recently and also due to limitations in acquiring the appropriate data and

resources on those countries my analysis will only focus of the original three member states of

the EAC.

The combined population of EAC member states as it currently stands is 133.5

million. This number includes both the populations of Rwanda and Burundi. Kenya with a

population of 39.8 million, Uganda with 32.7 million and Tanzania with 43.7 million2 make

up over 85 % of the population size in the East African Community. They are relatively small

economies with nominal GDP of 32.4 billion, 17.1 billion and 22.4 billion dollars3 for Kenya,

Uganda and Tanzania respectively. However they are among the fastest growing economies in

the whole of Africa with a real GDP growth rate of 4.9 %, 5.1% and 6.5%4. These three

countries are not new for trade liberalization as they have been active members to the World

Trade Organization since the 1990’s. The Custom Union they created is also attained through

duty free and custom free trade regime based on principles of the WTO.

Figure 1.1 Map of the original three members of the EAC

Source: eac.int 2 Population numbers are taken from World Bank database and they are 2010 estimates.

3 The source of the nominal GDP values is IMF for the year 2010.

4 Real GDP growth rates are from IMF and they are estimates for the year 2010.

9

According to the EAC treaty, The aim of the “new” East African Community is

widening and deepening co-operation among the Partner States in, among others, political,

economic and social fields for their mutual benefit. To this extent the EAC countries

established a customs union in 2005 and are working towards the establishment of a common

market in 2010, subsequently a monetary union by 2012 and ultimately a political federation

of the East African states.

The custom union is expected to reduce internal tariffs in progressive stages. In 2005,

it imposed the lowest rates on Agricultural and capital goods, medium rates on intermediate

goods and highest rates on capital goods. But these tariffs were subsequently further reduced

to 0 level by 2010. This stage of the EAC is the start of the regional integration process and its

success or failure will have critical effect on the whole endeavour. As we will see later, these

reductions in tariff and the custom union in general have their share in enhancing intra-

regional trade and economic development in the region.

Besides internal tariff reduction the custom union will impose Common External

Tariff (CET) on imports from non-member states and also establishes laws related to rules of

origin5, national treatment, anti-dumping measures, subsidies, countervailing measures and

other safe guard measures (East African Community Secretariat 2004). The protocol is

carefully crafted to address development imbalances among the member states and to avoid

revenue losses due to mismanagement of the custom union rules. The East African

Development Bank is also established and designed to assist the less developed members of

the EAC in order to narrow the developmental gap and maintain equitable gain from regional

integration. In this thesis all these aspects of Custom Union will be analyzed to investigate the

benefits of regional trade integration and whether gains are equitably distributed among the

5 Rules of origin are the criteria used to define where a product is made. They require that sufficient

transformation occurs when processing causes a product to shift from one tariff classification to another.

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members. In what follows I will briefly introduce the objective, method and preliminary result

of my study.

1.2 Objective, Research Question and Methodology of the Thesis

Regionalism and the benefit from trading regionally is still being debated. As some

mainstream pro-multilateralism economists argue, regional agreements allow for

discriminatory trade policies and thus may restrict further trade liberalization. Others on the

other hand, took a more moderate position in which the benefit from regional trade

arrangement is evaluated based on its overall gains from integration. It is indeed an open

question as to whether regional trading blocs create more trade than they divert. It can also be

true that, the lowering of trade barriers among members may lead to greater competition and

then opening up larger markets for producers in member countries. Indeed, a well crafted

trade bloc can increase competition in domestic industries and spur productive efficiency

gains which improve the quality and quantity of inputs and goods available to the economy

(Baldwin 1997).

Previous researches on the European Union and NAFTA have shown that the regional

mechanism in Europe and America have positive impacts on the living standards of the

member states and inconsequential effect on non-members states living standards (Baldwin

1997, Dollar 1992). Similarly, it will be useful to explore the regionalism in a variety of its

forms (North/South, South/South) and in different cultures to get a better insight into the

regionalization process around the world.

The EAC is among the regional integration blocs among developing countries that aim

to boot trade and assist economic growth in the region. As part of this effort it has already

established custom union among the member states to reduce internal tariffs and to set up

Common External Tariffs on outsiders. My main objective in here is to empirically

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investigate the welfare benefits from the establishment of this custom union. Hence my

research question in this regard is: what is the trade welfare implication of the formation

of custom union in the East African Community? The null hypothesis in this respect is; the

regional arrangement will lead to welfare losses as previous literature on the south-south

regional blocs suggest, regional integration arrangements between developing countries

usually result in failure. North-North and North-South RTAs are more likely to be welfare

enhancing than South-South (Jackson 2007). With current investigation this hypothesis will

be tested.

In order to answer this question and test the hypothesis I will employ two kinds of

methods. First I will utilize a descriptive statistic model with clear analytical framework to

measure the effects of tariff changes on welfare gains in the East African Community. These

ex-post analysis will integrate variety of indices to evaluate welfare implications of the

current changes due to the formation of a custom union among the three member states. A

well designed ex-post descriptive statistics assessment will allow for some important

conclusions to be drawn regarding the current state of a regional integration arrangement. It

also further allows for recommendations on how to improve the gains from regional

integration project. Besides the descriptive statistics model, there are a number of

sophisticated methods that can be used to model the impact of regional integration, including

econometric, gravitational model and Computable General Equilibrium (CGE) models.

Setting up and analyzing the results from these models require considerable technical

knowledge and considerable amount of data. This data is especially hard to find for some

developing countries in Africa.

Therefore, I have chosen the partial equilibrium technique as a second method of

analysis, a simplified but effective technique to analyze the effect of tariff alterations. The

Partial equilibrium model only required some trade data and few import and export elasticities

12

to generate an ex-ante predictions about possible outcomes of tariff changes. The simulation

model in this study apply The WITS/SMART software from the world bank to calculate trade

creation and diversion effects, net welfare effects and revenue effects of the EAC-CU.

But before I go ahead and reveal the preliminary results, I would like to acknowledge

some of the limitations in undertaking my study. One outstanding limitation in analyzing

trade effects among developing countries is lack of sufficient data to undertake sophisticated

analysis that takes into consideration multiple aspects of reality on the ground. Simplified

models like the Partial equilibrium miss out on some relevant variables for welfare analysis.

Furthermore, it should also be acknowledged that there are quite a few reasons why the

available African trade data must be interpreted with caution. It is by and large recognized

that high African trade barriers and restrictive exchange controls provide incentives to falsify

customs vouchers that are applied for the tabulation of trade statistics (Yeats 1998). Also, it is

commonly known that some African trade goes through "unofficial" channels and is not

recorded in the obtainable statistics. For example, Hardy (1992) found that more than half of

Uganda’s exports take place outside of official channels. This suggests a high degree of

caution when analyzing the statistics in once study.

In addition when running simulation on the WITS/SMART software the results are

susceptible to biases due some assumptions. This assumptions sometimes do not match the

reality on the ground. For example, changes in import and export amounts are assumed

constant when I simulate the effects of tariff reduction based on the 2004 UNCTAD data.

This might not completely match the reality in 2009. But still the results are worth

considering as the EAC intra-regional trade and its trade with the rest of the world grows in

almost similar amount (Khorana, Kimbugwe & Perdikis 2008).

However, despite these limitations the combined and systematically framed

descriptive statistic analysis and the detailed partial equilibrium model will give results worth

13

considering. Furthermore, similar techniques have been used in a number of policy studies

from renowned institution on trade matter, such as IMF and UN Economic commission for

Africa (UNECA) (McIntyre 2005, Lang 2006, Khorana, Kimbugwe & Perdikis 2008,

DeRosa, Obwona & Roningen 2002, Busse & Shams 2005, Stahl 2005). With this note of

acknowledgment I will move to the short description of the preliminary results.

1.3 Preliminary Results

The East African Community had made a remarkable progress in reducing regional

tariff to the lowest level in 2010. On the same time the custom union has imposed common

external tariffs on imports from the non-member trade partners. This arrangement will

significantly reduce Kenya’s tariff on imports from Uganda and Tanzania. As the same time,

the common external tariff will also reduce the tariff on imports from the rest of the world, as

Kenya’s previous trade tariffs were higher. This suggests an overall tariff reduction on the

side of Kenya. Therefore, the custom union will likely have trade creating effect in the case of

Kenya. The same is true for Tanzania. However, the descriptive statistics analysis shows the

reverse in the case of Uganda. Uganda’s import tariffs were lower even before the formation

of the EAC-CU, thus the custom union will inflict a common external tariff that will

significantly increase the tariff on imports from the rest of the world. Suggesting a higher

probability for trade diversion. But this assumption is overruled by the simulation results in

chapter four, that portrays high amount of trade creation as a result of tariff reduction. This is

related to the magnitude of regional imports for Uganda. Uganda depended on the region for

significant portion of its imports, even before the formation of RTA. This is also disclosed by

the trade intensity ratios that illustrate exceptional high values. Even before RTA formation

the region trades 1,000 times higher than what is normally expected. Therefore, tariff

reduction on the intense regional trade outweighs the effect of the common external tariff.

14

Concerning the pattern, composition and direction of trade in the region, the study

finds the majority of the intra-regional trade takes place in the manufacturing sector. Assisting

member states specially Kenya in improving its comparative advantage in manufacturing

certain products. This conclusion is drawn based the trade pattern and composition and the

revealed comparative advantage assessments. This implies that the EAC is contributing for

the industrialization of the region as one of its aims states in the treaty.

The partial equilibrium simulation results show a positive trade effects for each East

African Community member state. The custom union in aggregate will contribute to more

trade creation than trade diversion. This means that both the EAC members and the rest of the

world are well off with the formation of a regional trading arrangement in the Eastern Africa.

It is also an undeniable fact that Kenya remains to gain more from the regional trade than the

rest. However, there still remains a room for improving on how countries trade regionally,

especially issues of illicit trade activities and non-tariff barriers to trade.

15

Chapter II: Literature Review

This chapter will give a theoretical background for the analysis section that will follow

in the next two chapters. It will deal with concept of regional integration and some theoretical

explanations for the rapidly spreading regionalization in recent times. Hence, the first section

will deal with a discussion of some theories of regional integration that can potentially explain

Regional Trade Agreement (RTA) in the East African Community. In the second section I

will deal with theory of trade creation and trade diversion. This theory is used though out the

study evaluate welfare implications due to RTA. The last section will give a brief description

of previous studies that relate to my thesis. And finally, I will conclude by summarizing the

chapter.

2.1 Theories of Regional Integration

After being deemed to be a failure during the 1960’s and the 1970’s, regionalism

seems to be on the rise in the recent history of global economic integration. Until the early

1990s, multilateralism was dominant form of trading system and regionalism remained

marginal. There seems to be variety of factors for this current phenomenon as suggested by

renowned writers on the subject.

The recent frustration towards the multilateral trading system has been cited by the

mainstream economists as the main reason behind the burgeoning regionalism from Asia to

Europe and Africa (Bhagwati 1993, Krugman 1993, Bhagwati and Panagariya 1996).

Krugman (1993) pointed out that the recent move towards regionalism is caused by irritation

as a result of long and tiring negotiation processes under the GATT/WTO due to high cost

related to large number of negotiators. There seems to be a paradoxical relationship between

16

the recent opening up of economies around the world and the decline in the multilateral

trading system. Furthermore, he also points out that countries want to avoid the cost of non-

cooperation when such mechanisms fail. In addition, Bhawati’s assertion that “the US’s

conversion from devoted multilateralist to adherent regionalist” (Baldwin 1997: 866) as a

main cause for the worrying trend that seems to have drifted multilateralism (“Gold Laying

goose”) to a more manageable bilateral and regional systems. This has been contested by

Baldwin (1993). With this disagreement Baldwin (1993) sets out to develop his alternative

explanation of regionalism that is the domino theory of the spread of regionalism in the global

trading system.

Baldwin identified a strong correlation between the fraction of the population voting

for EU membership, the amount of the manufactured exports by non-member state to EU plus

European Free Trade Area (EFTA) as a share of the total export. His assertion is that the firm

owners and labor unions support the regional economic integration as it maximizes their

benefits. Hence, they will consistently lobby and put pressure on their respective governments

to take measures that will facilitate the accession into the nearby regional organization. Given

this assumption Baldwin demonstrates how a domino type of spread of regionalism could

materialize in a neighborhood where regional form of integration is present.

With the neighboring state joining the regional project, there is a likelihood that intra-

regional trade for the member state will increase as the cost of engaging in economic activity

with similar member states declines. “Thus although the fundamental cause of enlargement is

the exogenous deepening of the regional integration, this initial shock is amplified by the way

enlargement makes non-membership even more costly” (Baldwin 1993: 32). As more and

more states join the regional group the firms in the non-member state loss out from an even

larger number of markets that they could have benefited if the country had joined the regional

17

arrangement. These firms eventually put pressure on their respective governments though

lobbying mechanism so that the country joins the regional group.

In his second analysis Baldwin borrows a political economy model from Grossman &

Helpman (1992) to show how the firms in the non-member courtiers will put pressure on their

respective governments. Given that the priority interest of governments in liberal democratic

states is reelection, they cannot afford to miss out on the huge donation from big domestic

firms which are mainly interested in maximizing their profit. As described above, with the

number of countries falling in to the regional arrangement, these firms will consolidate their

lobbying power in order to push the government to apply for membership. This phenomenon

entails a domino effect that seems to appear like regionalism is spreading like a wildfire.

The domino theory barely explains regional integration agreement in the East Africa

Community or RTA in among developing countries for that matter. The historical context of

the RTA formation diverges from Baldwin’s assumption. In this context, it is really hard to

establish the link between the private sector and politics. Furthermore, domino theory starts

from exogenously given regional arrangement that pre-exists to give explanation for the wide

expansion (Baier et.al 2007).

“While such a framework can help to explain European Community

enlargement, it is not as useful here to help explain conceptually the

proliferating formation of new bilateral Free Trade Agreements (FTAs);

Baldwin' domino theory addresses only enlargement of existing

agreements. Nor does Baldwin's domino theory allow for the effects of

FTAs among other countries on the same or other continents” (Baier et.al

2010: 6).

18

Baier and Bergstrand (2004), however, propose a different view using an extended

model of Krugman (1991), Frankel, Stein, and Wei (1995), and Frankel (1997). Employing a

simple N-country Krugman monopolistic competition model, Baier and Bergstrand (2004)

showed the probability of FTA formation. Accordingly, The probability of FTA formation

and the utility gains from FTA are greater the larger the two countries' economic sizes, the

more similar the two countries' economic sizes, the closer the two countries are to each other,

the farther the pair is from the rest of the world, the larger the two countries' relative factor

endowment differences, and the smaller the difference in the two countries' relative factor

endowments relative to the rest-of-the-world. These conditions facilitate an endogenous

formation of FTAs as natural trading partners.

Empirically, Baier and Bergstrand (2004) utilized a probit statistics model to assess

the importance of the above mentioned variables in determining the subsequent formation of

FTAs in the year 1996. They have documented that their model can predict 85 percent of the

286 country pairs with FTAs in existence in their sample using 53 countries in 1996 and 97

percent of the 1145 countries pairs without FTAs. Their study strengthens the natural trade

partners theory, which has a potential to explain regional arrangements even in developing

south.

The natural trading partner thesis has been advocated by many . Even, Eicher, Henn

and Papageorgiou (2008) agree that Historical ties such as; Common language, Common

Colonizer, geographical proximity are variable which need to be considered when dealing

with effects of PTA. Common language and culture reduces inability to communicate and to

overcome cultural differences. Furthermore, “Common historical ties lead to similar

institutions and similar levels of development, implying reliable contractual and legal

standards, as well as trust in shared values” (Eicher, Henn & Papageorgiou 2008:8). This is

also the case for the three original members of the East African Community. Kenya, Uganda

19

and Tanzania have enjoyed a historical closeness emanating from their unique colonial

experience. Even prior to independence, the East African Economic Community had achieved

a degree of economic integration unique in Africa. The essential elements of this unity were

the existence of a common market, common currency, a similar tax structure and an

integrated system of railways, harbors, airways, post and telecommunications. There was thus

free movement not only of goods, but also of labor and capital, which flowed back and forth

across perfunctory frontiers. The East African community also protected nascent industries

with common industrial tariffs (Detter Delupis 1970).

The fact that Kenya, Uganda and Tanzania were under the same colonial power,

Britain, with similar colonial administrations adds to their close economic ties. Britain

inadvertently set in motion the integration process when it was decided to construct the

common railroad between Uganda and Kenya. This facilitated movement of factors of

production between the colonies. Later on, there were even efforts to promote and advance

common administrative mechanisms in areas of justice, postal union in 1911 and the East

African common currency board in 1920 (Ojo et al. 1985).

East Africa is also a place of common cultural heritage, peoples and shared

geographical features. This common culture contributes to the natural regional

interdependence and furthers economic relations. English and Kiswahili are the most widely-

spoken and widely-understood languages in the region with over 40 million people in Kenya,

Uganda and Tanzania speaking both of these languages (Kawoya & Makokha 2009).

Furthermore, their common location makes the East African community countries

share similar geographical features and climatic conditions. Kenya, Tanzania and Uganda

share Lake Victoria which provides huge water mass for inland transportation. In addition to

its socio-economic benefits Lake Victoria is a symbol of the strong unity the three nations

20

strive to achieve. With future strong regional economic integration and increased intra-

regional trade, it is expected that the Lake Victoria will be highly utilized to handle higher

volumes of cargo to facilitate trade. Besides, the Lake Victoria posses unique potential for

joint investment in fishing, tourism, water and energy and hence crucial to facilitate regional

ties.

Table 2.2 Trade pattern between Kenya, Uganda and Tanzania (2003)

Source: UN COMTRADE (2003)

Imports (% of Total Exports of Uganda &Tanzania)

Exports (% of Total Imports of Uganda &Tanzania)

Kenya

Uganda

Tanzania

Uganda

Tanzania

Food Products 79.8 21.6 8.4 18.8

Agricultural Material 6.1 19.3 8.4 2.8

Textile fibers 2.4 2.0 0.0 0.0

Ores, minerals and metals 0.1 2.0 26.4 15.7

Energy 0 2.0 26.4 15.7

Manufacturing 11.5 43.4 52.9 59.1

Imports (% of Total Exports of Kenya &Tanzania)

Exports (% of Total Imports of Kenya &Tanzania)

Uganda

Kenya

Tanzania

Kenya

Tanzania

Food Products 3.6 18.3 64.5 34.6




Energy 52.4 1.4 12.9 26.4

Manufacturing 33.8 71.3 3.3 38.2

Imports (% of Total Exports from Kenya &Uganda)

Exports (% of Total Imports from Kenya &Uganda)

Tanzania

Kenya

Uganda

Kenya

Uganda

Food Products 10.8 23.1 68.4 20.0




Energy 26.7 60.0 0.5 11.8

Manufacturing 56.8 16.6 13.9 58.8

21

In addition to their important communalities, the East African Community members

also share differences that facilitate interdependence. Uganda for example is a landlocked

country and therefore relies heavily on Kenya (Port of Mombasa) and Tanzania (Port of Dar-

es-Salaam) for its access to the Indian Ocean. Differences in the level of industrialization

among the EAC countries are also reflected in the trade patterns presented in the table below.

Kenya has relatively more advanced manufacturing sector with relatively more advanced

skilled labor availability, while Uganda and Tanzania specialize in the production of

agricultural goods and agricultural exports. Furthermore, while there is a potential for Kenya

to export capital and services to the other two EAC members, Tanzania posses large amount

of available land and huge amount of unskilled labor.

Some others also suggest these important differences had contributed to the collapse of

the “old” East African Community in 1977. One of the reasons advanced for the collapse of

EAC in 1977 was that Kenya was receiving a disproportionate share of the benefits from

integration. Various measures were tested to redistribute the gains from the common market,

but failed to produce the results Uganda and Tanzania wanted (Kasekende and Ng’eno, 2000).

As we will see in the coming sections equtable gains remain to be a problem in the region.

Table 2.1 Shares of Intra-Regional Exports in Total Exports of EAC Countries, 1970-97

Trading Partner

Exporter Kenya Tanzania Uganda Regional

Kenya — 4.5 % 9.7 % 14.2 %

Tanzania 2.1 % — 1.0 % 3.1 %

Uganda 1.9 % 0.5 % — 2.4%

EAC 0.8 % 2.7 % 5.9 % 9.5 %

Source: IMF, Direction of Trade Statistics

22

For instance,

“The East African development bank, which was to promote industrial

development with the states contributing equally to its capital base, was

required to ensure that Tanzania and Uganda each got 38.75 per cent of

its investments, against 22.5 per cent in Kenya. However, under a risk-

adverse clause in its statutes, it could only finance ‘viable’ projects,

most of which were in Kenya, especially during the 1971-1973 period.

This greatly limited its role as a redistributive institution” (Ndung’u

2003:48).

To summarize, the natural Trading partners hypothesis argues that regional trade agreement is

more likely to improve welfare if the participating countries trade disproportionally with each

other before the formation of the regional bloc. Trade integration with "natural trading

partners" is likely to raise welfare because the likelihood and extent of trade diversion is

minimized when the volume of trade between prospective partners is large from the start. Of

course one needs to be careful in making such generalizations a priori. Hence, there is the

need for an empirical investigation of the matter. And the theory of trade creation and trade

diversion provides us with the framework to empirically investigate whether RTA formation

is really beneficial.

2.2 Theory of Trade Creation and Trade Diversion

The empirical investigation of the welfare assessment of the East African Community

in the current study employs the theory of trade creation and trade diversion at the core of its

analysis. The theory was first developed by Jacob Viner, Canadian economist, in 1950. In this

23

section I will give a brief description of the theory and the conceptual framework behind

assessing welfare gains through measuring trade creation and trade diversion.

Regional Trade Arrangements (RTAs) have been controversial right from the onset in

the 1950’s. Especially with regards to the benefits and costs related to Preferential Trade

Arrangements (PTAs). Before, Jacob Viner (1950), the conventional belief was that all forms

of PTAs are welfare enhancing since they liberalize trade among member states. But Viner

showed that custom unions do not necessarily improve welfare, since the tariff reduction

occurs in a world of second best (Clausing 2001). By second best one understands a policy

that would be optimal without such constraints (such as a zero tariff in a small country) may

not be second-best optimal if other policies are constrained (Lipsey and Lancaster, 1956).

According to Viner (1950), whether the increase of trade due to custom union will be

welfare enhancing depend on the nature of the trade expansion. This is concerning possible

trade creation among the members and trade diversion from the non-members. If trade is

created, a more competitive producer from within the Custom Union (CU) replaces a less

competitive domestic producer. Therefore, increasing efficiency of resource allocation, thus

reduce consumer price and as a result increase welfare. On the contrary the formation of

custom union can also reduce efficiency of resource allocation when the trades between CU

members increase as a result of preferential market access that replaces imports from a

cheaper and efficient producer from the rest of the World. This is what Viner named trade

diversion. At a first glance it seems all Custom Unions are trade diverting as they reduce

tariffs between member states and impose a Common External tariff on the non-members. But

as an end effect the balance between trade creation and trade diversion is an important

determinate of the overall benefits from establishing custom union.

24

2.2.1 Trade Creation

In general, trade creation connotes the phenomenon where a custom union creates

trade that would not have existed otherwise. To elaborate let us assume that there exist three

countries in the world, country A, B and C and only one product6. Other factors are kept

constant. Here. The focus will be country A which is smaller than the two countries B and C

which are bigger. Therefore, country A takes international price as given and imports and

exports a product desired from country B or C depending on the price that prevails in those

markets. In what follows the first scenario describes what will happen if certain tariff is

imposed on both countries B and C by country A. Afterwards, county A will form a Free

Trade Area (FTA) with country B and I will describe in what circumstances this will result in

trade creation.

Figure 2.1 Trade Creation

Source: International Trade theory and Policy7

6 The graphical display and the related description is taken from International Trade theory and Policy by

Steven M. Suranovic (http://internationalecon.com/Trade/Tch110/T110-2A.php) 7 (http://internationalecon.com/Trade/Tch110/T110-2A.php)

25

The above diagram demonstrates the case of trade creation. D and S show the demand

and supply curve for country A. The lines PB and PC represent the supply price for a certain

product when trade is made free with both country B and C. And the lines PTB

and PTC represent

the supply price when certain tariff is imposed on both the imports from country B and C.

Note that the country C can still provide the product with lower price if tariff is eliminated as

a whole. But if Tariff is imposed on both countries B and C the product will not be imported

as supply price from a domestic product (PA) will be lower than the prices from B and C

including tariff (PTB

& PTC). Hence, cheaper supply from the rest of the world will be replaced

by costly domestic product.

But when we assume that country A forms a FTA with country B, the tariff level on imports

from B will be reduced to zero and the tariff levels on imports from C will remain the same.

Therefore, now the supply price from country B and C will be PB and PTC respectively. And

since PB is lower than PA the product is imported from country B rather than from expensive

domestic supply. Since lower supply is attained as a result the formation of FTA one can say

trade is created.

2.2.2 Trade Diversion

Basically what trade diversion means is that due to FTA formation trade is diverted

from more efficient supplier outside the PTA to a less efficient supplier within the FTA. The

diagram below demonstrates how trade diversion leads to welfare losses. Taking all the

assumptions from the above trade creation section, we can see that the country C is the most

efficient suppler of the product. Since, with the tariff, the good is cheaper from country C,

country A will buy the product from country C and will not trade initially with country B.

Even with the absence of free trade and with the imposition of tariff on all suppliers, the

product from the country C is cheaper.

26

Figure 2.2 Trade Diversion

Source: International Trade theory and Policy

However, when we assume that A and B form FTA and A eliminates tariffs on imports

from B we will have a different picture. When tariff on imports from B is reduced to zero and

the tariffs on imports from C remain the same the supply lines will be PB and PTC respectively.

Taking in to consideration losses in tariff revenue and lower surplus gains for consumers, one

can say trade is diverted from a more efficient supplier C to a more expensive supply B.

Hence, the larger is the difference between the non-distorted prices in the FTA partner

country and in the rest of the world, the more likely that trade diversion will reduce national

welfare.

2.3 Similar studies on welfare analysis concerning the EAC

Different authors have used variety of methods to analyze the static welfare gains as a

result of the establishment of the East African Community. In this section I will discuss some

of these studies which have a direct link to my study. I will categorize this studies based on

the method they used to reach their conclusions. I will first discuss the literatures that used

gravitational model for their investigation (Kirkpatrick and Wantabe 2005, Ng’ang’a 2006)

27

then I will give a brief description of a study that attempted to apply general equilibrium

modelling (Okello 2008) and finally I will discuss the scholarly texts that utilized the partial

equilibrium model in order to assess the RTA formation in the East African Community

(McIntyre 2005, Khorana, Kimbugwe & Perdikis 2008).

The gravitational model regional trade integration analysis was undertaken by

Kirkpatrick and Waranbe (2005) to examine the pattern of trade in the EAC over some range

of years, 1970 till 2001. According to them, the standard gravitational model between any two

countries is the function of the country’s trade potential and their mutual trade attraction. The

country’s trade potential include economic size (GDP), level of development, geographical

size and population size. The relative attraction between the two countries can include

geographical proximity, cultural similarities and historical ties. Also attraction can also be

artificially enhanced through a policy to establish bilateral trade. Besides the factors from the

standard gravitational model, the Kirkpatrick and Waranbe (2005) model further add

differences in GDP per capita between two trading partners to test whether two countries with

similar living standards will share a broader range of goods to trade. The main aim of their

analysis is to investigate if the policy to establish regional cooperation coincides with increase

in intra-regional trade. The results from their studies indicate that almost all of the core

variables coincide with increase in regional trade. But most importantly they found out that

intra-regional trade was stronger during the 1970’s and then dropped with the decline of the

“old” EAC in 1977. Their robust analysis indicates that regional cooperation agreement has a

positive relationship with increase in intra-regional trade in the East African Community.

Ng’ang’a (2006), on the other hand, investigated the trade, welfare and production

effects of the establishment of the “new” EAC using a gravitational model. The aim of his

investigation is to find out whether the volume of trade within the EAC has grown as a result

of the formation of the regional trading bloc. Moreover he set out to analyze whether there are

28

signs of trade diversion due to Regional Trade Agreement (RTA). Besides dummy variables

from Kirkpatrick and Waranbe (2005) study, Ng’ang’a further adds other dummy variables

such as overall imports and exports by RTA members. This is done in order to measure the

openness of the RTA to imports and exports to the rest of the world, as a result measuring

trade creation and Trade diversion. The fundamental logic to the investigation was that a sign

of trade creation is identified when increase in intra-regional trade is coincided with increase

in overall imports. And trade diversion will be identified when an increase in intra bloc trade

coincides with a decrease in overall bloc imports from non-members. Also in the case of

exports, if decrease in exports to the rest of the world is witnessed as intra-regional trade

increases then this could be sing of trade diversion.

His analysis investigated the EAC trade in the years from 1994 to 2004. Note that

these are the years before the implementation of the custom union in January, 2005. The result

of his analysis shows that there is no significant change in the intra-regional trade due to RTA

formation. This is due to the time period of the analysis, which is before the implementation

of EAC-CU. Furthermore, he found out that the EAC intra-regional trade is reversely related

to exports to the rest of the world. So, he concludes that the increase in the intra-regional trade

must have diverted some of the regions exports to the rest of the world. But from Kirkpatrick

and Waranbe (2005) analysis we have seen that intra-regional trade has been in decline since

the collapse of the “Old” East African Community. This only suggests that there is a decline

in intra-regional trade but exports to the rest of the world has been increasing ever since due

to increase in export performance of the individual member countries. The reverse relation

only entails the situation where intra-regional trade decreased while exports to the rest of the

world were increasing. It could also be the case that there is an increase in overall world

exports such that world trade is growing much faster than EAC trade (Ng’ang’a 2006).

29

Therefore, it will be difficult to reach a conclusion that EAC is trade diverting only based on

Ng’ang’a (2006)’s gravitational model analysis.

The Computable General Equilibrium Model (CGE) analysis of Okello (2008) utilizes

the GAMS software to simulate the welfare gains for Uganda due to membership in the East

African Community. The CGE modelling also include factors of production in its analysis and

also captures interdependence among the various markets and sectors of the economy besides

some trade data. This makes it more sophisticated hence better capable to capture reality. The

short coming in this model is the lack of appropriate and available data to do the simulation.

The simulation results generated by a detailed CGE model depend potentially on thousands of

data items, elasticity values and behavioral assumptions. This makes it difficult, even

impossible to apply for all the members of the East African Community. This is especially

true for Kenya where the data is not available (Khorana, Kimbugwe & Perdikis 2008). As

demonstrated in Okello (2008) study, there is a positive welfare gain for Uganda due to

membership in the EAC. The other interesting finding from this study is that the welfare

benefit from the EAC is not evenly distributed within the Ugandan society. There is reduction

of welfare for the poorest households and significant welfare improvements for the rich urban

and rural households. These results support the theory that links trade liberalization and

unequal welfare gains in certain society, gains between the rich and the poor (Goldberg and

Pavcnik 2007, Tarasov 2010).

Besides the gravitational model and computable general equilibrium model analyses of

the welfare impact of the EAC, there are also similar studies that employed the partial

equilibrium model to find out the extent of welfare enhancement as a result of the formation

of the EAC. Both of the studies from McIntyre (2005) and Khorana, Kimbugwe & Perdikis

2008 use the WITS/SMART simulation model to probe the EAC welfare gains for Uganda

and Kenya respectively. McIntyre (2005), through his analysis found out that the simulation

30

results provide preliminary evidence for possible trade benefits from the EAC Customs Union

for Kenya. This is because of the adoption of the EAC Common External Tariff that will lead

to increased flows of cheaper intra-regional imports that are likely to lower consumer prices

with positive welfare effects. In the case of Khorana, Kimbugwe & Perdikis 2008, similar

results were obtained for Uganda. They simulated two scenarios, one with partial tariff

liberalization in 2005 and the other with a full elimination of tariffs in 2010. The highest

welfare change occurred with the full implementation of the EAC-CU in 2010, but still the

analysis of tariff reductions in Scenario I and II show, in both cases, there is a positive net

trade effect with small trade diversionary effects for Uganda under the EAC-CU.

My investigation differs from the two studies that applied the Partial Equilibrium

method as it takes into consideration the effect of the Custom Union formation on the

patterns, direction and composition of trade in the EAC as a whole. Also it will analyze the

effect of the custom union in all of the three major partners. With this in mind I will employ

both systematic descriptive statistical method together with WITS/SMART simulation to

capture the wider implication of the regional bloc in Eastern African on trade and welfare. In

the next chapter I will begin my analysis using a descriptive statistics modelling with a well

structured analytical framework to assess welfare effects of the EAC.

31

Chapter III: A Descriptive Statistics Analysis

This Chapter deals with a descriptive empirical assessment of the regional integration

arrangement and pattern in the East African Community. The expectation here is that through

the lowering of tariff and removal of non-trade barriers economic welfare will likely be

enhanced through promotion of trade among member states. Moreover, tariff reductions will

likely promote specialization in production hence enhancing efficiency and quality on the

supply side while increasing the purchasing power of consumers and encouraging

consumption through lowering of import price on the demand side.

As already mentioned in the introductory part, the relationship between regional tariff

liberalization and welfare gains are still debatable. As Krugman in his 1989 seminal article

argues “A naive view would be that since free trade is better than protection, any movement

towards freer trade will be a good thing” (1989: 3). Therefore, all forms of preferential trading

systems and regional arrangements are at any rate a step in the right direction. In the much

celebrated analysis of Viner (1950), it has been shown that some Custom Unions may cause

welfare losses as they might lead to trade diversion instead of trade creation. Some Custom

Unions can result in blocking and substituting products from an efficient non-member

countries hence leading to loss of efficiency instead of specialization.

In what follows, the trade welfare implication of the formation of custom union

between the three original members of East African Community, Kenya, Uganda and

Tanzania will be assessed. The current chapter employs a descriptive statistic method to

analyze trade creation and trade diversion effects of the EAC-CU. Of course, there are much

to be learnt from using descriptive statistics systematically based on clear analytical

framework and appropriate indices. This approach can be used to asses both ex-ante

32

predictions as well as ex-post analyses. However, since the method allows an ex-post

assessment to draw some important conclusion regarding regional integration agreement, I

will utilize it to investigate welfare effects.

The first section of this chapter deals with tariff changes and its trade creation/trade

diversion effects and implications. The assumption here is that the higher the pre-RTA tariffs,

and the lower the post-RTA common external tariff (CET), the more likely a RTA will be

welfare enhancing (Kemp & Wan 1976). Taking this concept as a spring board the tariff

changes in the EAC-CU will be analyzed together with their effects. The second section of the

chapter will evaluate the changes in trade intensity, patters, composition and direction. The

following section will dig deeper into the impact of regional integration agreement to assess

more fluid and dynamic gains from integration such as overcoming smallness, improving

good governance and promoting peace and security. Finally the last section of this chapter

will conclude with a discussion of the main findings.

3.1 Tariff Regimes in EAC and Common External Tariffs (CET)

According to the custom union protocol that was enacted in 2004 by the three member

states of East African Community, the establishment of the custom union was progressive in

the course of transitional period of five years from coming into force in 2005. In its first stage

of tariff reduction, the “cascading tariff” structure lowers rates to the lowest (0%) on raw

materials and capital goods, and imposes moderate rates (10%) on intermediate good and

higher rates (25%) on consumer goods8. The second stage, which came into force in 2010,

imposes a complete tariff reduction and elimination of all import duties and quotas. The intra-

EAC tariff elimination process over a period of five years was designed in order not to cause

disruption and unfair competitiveness in the manufacturing sector. A five year progressive

8 The first stage was implemented in 2005 and aims a tariff reduction to 0% for raw materials and capital goods,

reduction to 10% on intermediate goods and to 25% on consumer goods (for more info see CU protocol 2004).

33

phase tariff structure was mainly adopted to target trade of some products from Kenya

exported to Uganda and Tanzania. This asymmetrical tariff regime was intended to cushion

the manufacturing sector in Uganda and Tanzania which was still nascent and therefore would

be vulnerable to competition from established Kenya manufacturers. A free tariff regime that

lowered tariffs to 0% on all products was attained on 1st January 2010.

Table 3.1 Tariff Changes within EAC9

2001 2004 2005 2010

Kenya

Simple Average 18.16 15.57 0 0

Weighted Average 23.16 16.93 0 0

Maximum Rate 40 60 0 0

2001 2004 2005 2010

Uganda

Simple Average 3.96 3.57 0.21 0

Weighted Average 3.07 3.30 0.43 0


200110 2004 2005 2010

Tanzania

Simple Average 15.32 2.89 1.12 0

Weighted Average 13.29 1.37 1.5 0


Source: UNCTAD

The table 3.1 above demonstrates that remarkable progress has been made towards

lowering tariff and liberalizing trade in the East African Community. Kenya already in 2005

lowered tariffs to 0% on 90 percent of the products from the two member states (Ng’ang’a

2006). While the maximum tariff was registered in Tanzania after the establishment of the

custom union, it was progressively lowered to 0% in 2010. Uganda had low tariffs before the

formation of the Regional Integration Arrangement (RTA) and was even reduced to 0% 9 The tariff rates shown in the table are the actual applied tariff levels in respective years.

10 The tariff rates for Tanzania for 2001 and 2004 are substituted by 2000 and 2003 as there was no data

available for the respective years from UNCTAD.

34

progressively. Considering the fact that pre-RTA tariffs in Uganda were already lower

compared to the two members it is likely that the net trade creation in Uganda will be lower

than the two other member countries. But now let’s consider the other aspect of the formation

of the Custom Union, Common External Tariff (CET), to have a broader overview of the

tariff change in the EAC and its welfare impacts.

As already mentioned, besides eliminating internal tariffs, the East African

Community custom union has variety of features such as establishing a common external

tariff and establishment of rules of origin, safeguard measures and custom administration.

CET refers to a uniform duty rate or customs duty adopted by a trading pact group to be

assessed on imports from countries outside that market or group (Busse & Shams 2003).

According to the Custom Union Agreement, “The Partner States hereby establish a three band

common external tariff with a minimum rate of 0 per centum, a middle rate of 10 per centum

and a maximum rate of 25 per centum in respect of all products imported into the

Community” (East African Community Secretariat 2004:15). The overall average applied rate

of the CET is 12.9 percent. The average tariff on agricultural goods is 19.7 percent and 11.9

percent on non-agricultural products (East African Community Secretariat 2010).The

maximum rate of tariff which is imposed due to Common External Tariff (CET) is subjected

to change during the course of the process. The council may even review the common

external tariff structure and approve measures designed to remedy any adverse effects which

any of the Partner States may experience by reason of the implementation of this part of the

Protocol or, in exceptional circumstances, to safeguard community interests. But under no

circumstances should the internal tariff exceed the Common External Tariff (CET).

In what follows I will analyze the impact of the setting up of the common external

tariff as result of the establishment of the EAC-Custom union. The statistics looks into the

imports from EU-27 countries to display changes due to common external tariff. Also changes

35

in tariffs on imports from China11 will be considered as China is the next major trade partner

to the EAC member countries (McIntyre 2005). Furthermore, looking into import tariffs on

trade between EAC and China serves as a control to avoid bias. The table below displays the

tariff change on imports from non-EAC member trade partners in terms of effectively applied

rates.

Table 3.2 Tariff Changes on imports from EU-27

2001 2004 2005 2010

Kenya

Simple Average 17.41 15.02 11.84 11.93

Weighted Average 14.13 11.38 7.86 6.83


2001 2004 2005 2010

Uganda

Simple Average 7.32 5.95 12.88 12.29



200112 2004 2005 2010

Tanzania

Simple Average 17.07 13.99 13.01 12.78



Source: UNCTAD

In average the tariff rates of the EAC on imports from the European Union (EU-27)

seems declining after the establishment of the EAC-CU. Here it’s helpful to focus on the

simple average tariff rates and trade weighted average since the actual tariff rates are

somewhere in between this rates (Jackson 2007). Unlike the case of Kenya and Tanzania, the

Common External Tariff (CET) raises the tariff levels in Uganda, which is lower before the

11

The results for EAC-China tariff is attached as Appendix I 12

Here as well the tariff rates in 2001 and 2004 are replaced by 2000 and 2003 respectively due to lack of

available data.

36

establishment of the RTA. This is presumably due to deteriorating terms of trade that Uganda

wants to avoid that haunted its economy during structural adjustment programs (SAP) in

1980’s.

Figure 3.1 Net barter terms of trade index (2000 = 100) for Uganda13.

Source: Source: United Nations Conference on Trade and Development, Handbook of Statistics and

data files, and International Monetary Fund, International Financial Statistics.

Overall results suggest that the formation of the EAC-Custom Union has a very stark

effect in reducing internal tariff within the EAC, while at the same time reducing tariff on

imports from non-member trade partners. This is specially the case for Kenya and Tanzania

and their trade relations with the rest of the world. The common external tariff, on the other

hand, will have somewhat different effect on the trade relations of Uganda. It increases the

tariff rate of Ugandan imports from the rest of the world suggesting a probability that it will

result in trade diversion as cheap and more efficient products might be substituted by a more

expensive and lower quality products produced within the custom union. But as internal tariff

13

Net barter terms of trade index is calculated as the percentage ratio of the export unit value indexes to the import unit value indexes,

measured relative to the base year 2000.

0

50

100

150

200

250

300

350

19

77

19

82

19

83

19

84

19

85

19

86

19

87

19

88

19

89

19

91

19

95

19

99

20

01

20

03

20

05

20

06

20

07

20

08

20

09

Uganda

Uganda

Barter terms of Trade

Years

37

reductions are significant and other welfare gains from integration are under consideration,

there is still more Uganda can gain as a member of EAC.

3.2 Trade patterns, Direction, composition and Intensity in the EAC

This section evaluates the trade pattern, composition, intensity and direction in the

EAC. I will hereby appraise changes in trade that are likely resulted from the already analyzed

tariff changes in the EAC. It is already documented that since the formation of the East

African trading bloc, trade in the region has shown impressive progress both in terms of intra-

regional trade and trade with the rest of the world (Ajumbo 2010, McIntyre 2005). Of course

it is hard to say whether this trade growth is exclusively associated with the formation of the

regional bloc. However, one can depict a positive relationship between the progressive

reduction of the tariff and increase in trade volume in the region.

Table 3.3 Trade flows for EAC, 2003-2007 in US $Millions

Regional Trade 2003 2004 2005 2006 2007 2005 2006 2007

Exports Percentage

(%)

Intra-EAC total 816.9 935 1,061.10 890.1 1,148.30 17.89 16.29 13.92

To Rest of Africa 103.7 106 137.8 258.8 22.8 2.32 4.05 0.32

European Union (EU) 1,214.20 1,289.40 1,200.80 1,191.90 1,396.40 20.25 18.64 19.81

USA 61 254.4 262.7 328.1 367.80 4.43 5.13 5.22

To Rest of the World 1,027.30 1,276.20 1,584.10 1,959.00 2,263.80 26.71 30.64 32.11

Total EAC Exports 4141.3 5015.1 5,930.10 6394 7,049.50 100 100 100

Regional Trade 2003 2004 2005 2006 2007 2005 2006 2007

Imports Percentage

(%)

Intra-EAC total 562.7 591.3 786.20 727 824.50 7.31 5.16 2.26

Rest of Africa 14.3 23 14.3 122 3136.90 0.13 0.87 8.61

European Union (EU) 1,354.20 1,581.20 1,881.90 2,496.80 950.30 17.50 17.74 2.61

USA 348.90 364.6 741.7 556.8 11,166.00 6.90 3.96 30.65

Rest of the World 4,033.90 4,847.10 5,788.10 8,390.10 18,433.00 53.83 59.60 50.60

Total EAC Imports 7350.7 8727.1 10,752.40 14077.6 36,431.20 100 100 100

Total Intra-EAC 1379.6 1526.3 1847.3 1617.1 1972.8 11.07 % 7.9 % 4.53 %

Trade

Total trade 11492 13742.2 16682.5 20471.6 43480.7

Source: Partner States Revenue Authorities, Central Banks and National Statistics (Ajumbo 2010)

38

The region’s total trade volume has increased significantly while at the same time total

trade increased in an even higher pace. Even though, the intra-regional trade as portion of the

total trade has decreased from 2003 to 2007, recent reports from the director general of the

EAC directorate for customs and trade conveys that the volume of intra-regional trade

currently stands at 13% of the total trade of the region (IPP 2010). This suggests there

remains a lot of room for furthering and growing regional trade in the EAC. Still from the

data provided above one can draw a conclusion that the regional trade is not necessary

substituting imports from the rest of the world. However, the low level of regional trade

remains to be a concern for the further regional integration that the EAC aspires in the future.

At the same time trade with the rest of Africa is on the rise in the same proportion as

the rise in trade with the rest of the world. This situation can be explained by the overlapping

membership of the EAC member countries in variety of regional free trade arrangements with

in Africa itself.

Table 3.4 Overlapping RTA membership by member states in East Africa

Regional Initiatives

Kenya

Membership

Uganda

Tanzania

AU √ √ √

COMESA √ √ �

SADC � � √

EAC √ √ √

IGAD √ √ �

Source: UNECA

It’s also worthy to note that the three original member states of EAC are at the same

time members of WTO and active parts in the multilateral negotiations to liberalize trade. In

addition, Kenya, Uganda and Tanzania still enjoy free access to European markets in the same

standard as other African countries that have signed Economic Partnership Agreement (EPA)

with EU. In this manner, the implementation of the EAC Customs Union seems to have faced

39

with challenges both of policy and operational nature due to overlapping memberships and

global free trade commitments. However, it suffices to mention that these challenges are not

insurmountable as they were anticipated and will not block the integration path (East African

Community Secretariat 2010).

Looking at details into respective countries directions of imports and exports we can

notice that there are differences in trade among member states. According to the 2009 trade

report from the EAC secretariat, Kenya continues to dominate the EAC regional trade,

accounting for 44.8% of the total volume of trade and recorded a surplus in this trade (EAC

Secretariat 2010). Uganda and Tanzania accounted for 28.1 % and 27.1% of the total intra-

EAC trade respectively. The table below shows individual members states trade within the

region and how it changed from 2005 to 2008.

Table 3.5 Intra-EAC trade 2005-2008 (US$ Millions)

Source: The East African Community Trade Report 2009.

40

Imports also significantly increased during the year 2008 and were accounted by

increased imports of capital and consumer goods (EAC Secretariat 2010). Uganda continues

to be a major regional importer accounting for 48.3% of the total imports while the numbers

for Kenya and Tanzania are 36.3 and 15.4 percents respectively. Obviously the intra-regional

exports have also increased at the same level from 1,148.6 US$ million in 2007 to 1,542.2

US$ million in 2008. While exports from Tanzania show encouraging changes, the exports

from Uganda and Kenya has decreased compared to the previous year. Overall Kenya seems

to export way more than the intra-regional exports average.

Figure 3.2 Intra-EAC trade 2005-2008 (US$ Millions)

Source: Source: The East African Community Trade Report 2009.

41

The descriptive analysis of the intra-regional trade in the EAC suggests that there is

increase both in the trade within the region and with the rest of the world. This further entails

that the EAC is least likely to divert trade into the region rather it is promoting global trade

and advancing trade creation within the region. In the next chapter this results will be

compared with the outcomes of the trade simulations based on the WITS/SMART model.

3.2.1 Compositions of Exports and Imports in EAC & Revealed Comparative

Advantage (RCA) analysis

The composition of imports and exports in the EAC is consistent with the level of

development in respective member countries. Majority of their exports are primary

agricultural goods mainly Coffee, Tea, Tobacco and Cotton. The region's major imports are

machinery and other capital equipment, industrial supplies and raw materials, motor vehicles

and motor vehicle parts, fertilizer, crude and refined petroleum products. In recent years,

there is a decrease in the share of agricultural sector in the economies of Kenya and Uganda,

while Tanzania has maintained large agricultural sector with no significant growth in the other

sectors (Ng’ang’a 2006).

Looking at the intra-regional trade composition, one can quickly notice that trade

within the EAC has somewhat different pattern. The main intra-regional imports of Kenya are

manufactured goods from Tanzania. Furthermore, agricultural goods from Tanzania and crude

material (Crude Petroleum) from Uganda take significant portion of Kenya’s regional

imports. In return Kenya mainly exports manufactured goods to Uganda and Tanzania. It is

also interesting to see that the majority of trade exchanges between Kenya and Tanzania are

manufactured goods. Uganda on the other hand exports mainly primary goods such as food

and energy materials. The intra-regional trade within the ECA demonstrates both comparative

advantage (in the case of Uganda) and competitive advantage between the industries in Kenya

and Tanzania.

42

Table 3.6 Regional Trade by Commodity composition 2009 in (1000 US$)

Kenya Imports from: Exports to:

Uganda Tanzania Uganda Tanzania

Food and live animals

21378.8

15548.41

46534.64

43869.39

Beverages and tobacco

14406.68

4296.32

47824.69

7093.936

Crude materials, inedible,

except fuels

14488.19

12973.13

22760.72

8763.138

Mineral fuels, lubricants

and related materials

88.864

6277.607

55924.62

21251.23

Animal and vegetable oils,

fats and waxes

2216.233

314.023

3281.597

21156.76

Chemicals and related products

788.279

2232.359

130007.6

83775.42

Manufactured goods

2509.304

54764.33

177166.6

102879.5

Machinery and transport equipment

709.161

3045.246

65499.09

52851.89

Miscellaneous manufactured articles

739.832

1687.371

49311.75

47659.71

Commodities and transactions

not classified elsewhere in the SITC

- - 4.216

0.747

Uganda Imports from: Exports to:

Kenya Tanzania Kenya Tanzania


37213.41

9823.137

85985.91

505.489


43076.92

1903.705

18488.2

3521.15


except fuels

20840.61

3436.751

9395.543

219.934



62999.09

9901.824

9027.569

4314.719


fats and waxes

3343.186

210.52

2049.017

3799.719


94974.75

1726.031

951.002

4396.999

Manufactured goods

149627.8

10096.79

4196.21

7104.394


50780.3

1816.854

50780.3

543.224


39740.7

1881.681

16637.86

102.286



62.458

1.026

64.197

0

43

Tanzania Imports from: Exports to:

Kenya Uganda Kenya Uganda


21237.32

855.459

59334.62

3488.196


5551.673

3111.155

4325.523

2357.98


except fuels

6234.411

117.766

18688.89

117.766



64272.48

903.071

7786.492

785.075


fats and waxes

3417.38

471.973

382.081

225.73


59503.32

1520.255

8856.314

1742.013

Manufactured goods

101679.5

1103.365

67057.88

28058.97


64435.21

3694.836

18894.28

4374.904


19321.57

341.955

2270.185

7415.826



619.051

14.858

5307.664

1339.182

Source: UN COMTRADE

The EAC trade with the rest of the world is better explained by comparative

advantage. The three member states export mainly Coffee, Tea, Cotton and Tobacco to

destinations in Europe and Asia while importing heavy manufactured goods and fuel from the

rest of the world.

The data here also confirms that Kenya remains to find favorable market for its

manufactured products, while Uganda enjoys low tariff imports of manufactured goods

mainly from Kenya. The fact that the manufacturing sector plays an important role in the

EAC intra-regional trade entails the future potential of the RTA to promote industrialization

in the region. Overall the trade composition statistics disconfirms the hunch that EAC remains

to be welfare reducing. Rather it is promoting industrialization and intra-industrial trade14

among member states.

14

The intra-industrial trade potential of the EAC will be analyzed in the dynamic welfare gains section of this

chapter

44

3.2.1.1 Revealed Comparative advantage analysis of EAC

The argument Makower and Morton (1959) put forward that stated RTA will be more

likely to be welfare improving when there are wide differences in relative costs has been

challenged by Vernables (2003). Vernables rather considers comparative advantage between

members and the rest of the world. He claims that countries with ‘extreme’ comparative

advantage (i.e. the country which have a comparative advantage most different to the rest of

the world) will be more likely to experience trade diversion since their exports will be based

on the intra-regional consideration not on global comparative advantage. However, the

country with ‘intermediate’ comparative advantage will enjoy more gains from internal tariff

reduction and trade in RTA in a greater extent than it does with the rest of the world. Custom

union will provide the ‘intermediate’ state a unique opportunity to export more of its products

within the region. Further, the RTA formation though time will support the ‘intermediate’

state in creating its own comparative advantage in the more productive industries. But this

also suggests that if there are countries within the RTA that have ‘extreme’ comparative

advantages in certain products they will likely gain less as they export cheaper products

(Compared to the rest of the World) to the ‘intermediate’ state and import less efficient

products from the ‘intermediate’ state. Therefore, it would seem that if there are wide

differences in relative costs between members this would indicate the RTA is likely to be

welfare improving for the members with comparative advantage close to the world average.

The index to measure the extent of country’s comparative advantage has its base in

Balassa (1965) work. He suggested that different patterns of trade reflect different relative

costs and non-price factors between countries, thus revealing their comparative advantage.

Therefore he proposed that revealed comparative advantage indices could be used to measure

such trade patterns.

45

The Revealed Comparative Advantage (RCA) is measure as follows:

RCA = (XiA/XA)/(XiB /XB)

Where

XiA : Country A’s export of commodity i

XA : Country A’s total export

XiB : Country/Region B’s export of commodity i

XB : Country/Region B’s total export

Positive RCA value, which is greater than one might be interpreted as an indication of comparative advantage compared to the rest of the world.

Digging deeper into the structure of Kenyan exports, the Revealed Comparative

Advantage (RCA) results show that Kenya has been gaining a moderate comparative

advantage in some manufacturing products such as outer garments, Leathered manufactures,

Inorganic Chemicals, fish products and sugar confectionary. But the fact remains that Kenya

still retains its extreme comparative advantages in the production of Coffee and tea, Tobacco

and Tobacco manufactures and vegetable materials15.

Taking a look at the Ugandan exports, a moderate assessment entails that Uganda has

more products with higher RCA index. Fish products, sugar and sugar preparation, coffee and

tea, Tobacco, Vegetable materials and processed Animal and Vegetable oil are the products

with extreme RCA. In the case of Tanzanian exports, Coffee and Tea, Tobacco, Textile fibers

and Metalliferous ores are with high numbers of RCA index.

Similarly, Tanzania has an “extreme” comparative advantage in producing Coffee, tea

and tobacco, fish and other primary goods. However, in somewhat smaller extent compared to

Uganda or Kenya to that matter. Tanzania also has a well developed mining sector and really

high comparative advantage in producing some precious metal ores. Also similar to Kenya it 15

Look at Appdenix II for more detail RCA results.

46

is improving its comparative advantage in producing some manufactured products such as

textile fibers, manufactured fertilizers and processed animal and vegetable oils. This

observation also match the intra-trade results that show a significant amount of trade in

manufacturing sector between Kenya and Tanzania, which as a result is encouraging

improvements in efficiently producing processed goods.

The results16 indicate there is a chance that the formation of regional integration

arrangement might lead to trade diversion if the trade of primary and agricultural goods is

redirected to regional market. But the direction of the East African trade as analyzed above

demonstrates, majority of agricultural products are exported to industrial countries outside of

the region. Significant portion of the intra-regional trade consist of processed industrial

products which member countries have ‘intermediate’ comparative advantage. This is

especially true for Kenya, a country which is slowly but surely gaining comparative

advantages in producing certain processed industrial goods. Reestablishment of the “new”

EAC has helped Kenya in gaining export diversification in certain manufactured products

with ‘intermediate’ Revealed Comparative Advantage. Leading to a conclusion that Kenya

cleaves more advantage from the formation of EAC than the other members. But in general

we can observe that the formation of EAC is facilitating the transformation of the member

states economies into industrialization which has been difficult for much of developing

nations in the recent past.

3.2.2 Trade Intensity in EAC

The trade intensity index is an alternative method to gravity model to measure and

analyze the condition of custom union and its trade effects. It was first introduced by Brown

(1947) and developed and popularized by Kojima (Kojima 1964, Drysdale &Garnaut 1982).

16

The data and the RAC index results in this section are calculated with WITS web-based software from the

World Bank. The time period of the acquired data under analysis starts from 2003 till 2009.

47

The main concept behind measuring trade intensity is that we can compare the amount of

trade between a country and its partner/s in relation to the size of their economies. “The trade

intensity (concentration) index (TI) is used to determine whether the value of trade between

two countries is greater or smaller than would be expected on the basis of their importance in

world trade” (Ng’ang’a 2006: 51).The assumption here is there will be more trade between

big economies than between small once. If the relative sizes of the economies are

disproportional to the intensity of trade they have between them one can suspect that there

might be trade diversion due to RTA. But unlike gravity model, the Trade Intensity index

abstracts from many other variables that can affect trade intensity between partner countries.

It only looks at size of economy compared to the intensity of trade. However this abstraction

can be useful in order to take a glance at the complex reality which otherwise would be very

difficult to comprehend.

The trade intensity is calculated as follows:

TIij = (xij/Xit)/(xwj/Xwt)

Where xij and xwj are the values of country i’s exports and of world exports to country j and

where Xit and Xwt are country i’s total exports and total world exports respectively.

TI result close to a unit is interpreted as absence of preferential agreement between

partner states. Partner states are trading in the same extent as their trade with non-members,

hence no trade diverting effects. And if the results are greater or lesser than one that indicates

partners are having more or lesser amount of trade than expected. If there is a significantly

higher number of TI between partner states that might be a sign of trade diversion due to

bilateral agreement among them. This section uses UN COMTRADE data to calculate the

trade intensity rates of the EAC countries.

48

The table below demonstrates that trade intensity between EAC member states is very

high. The results for Kenya are especially high as the method chosen to measure TI in this

case considers exports as bases for calculation. It is by now clear that Kenya depends on the

EAC for significant portion of its exports. These very high numbers of the TI results might

suggest trade diversion but it should also be noted that trade among the EAC has always been

high indicating interdependence even before the formation of RTA. It will be hard to associate

the high trade intensity with the establishment of the EAC. The other possible explanation for

very high TI could be the fact that the three member countries are “natural trading Partners”

(Lipsey 1960, Krugman 1989, Bahgwati 1993, Panagariya 1997, Baier and Bergstrand 2004)

in which trade among them is facilitated by factors like historical ties, geographical closeness,

common culture and language, low transportational cost and others.

Table 3.7 Trade Intensity Index for EAC (1995-2009)

Kenya 1995 2000 2005 2009

TI with Uganda 960.17 1210.44 1046.02 633.20

TI with Tanzania 377.12 293.08 227.56 182.84

Source: UN COMTRADE

As Bhagwati (1993) has pointed out, one should encourage countries to enter into

preferential arrangements with countries in geographically proximity rather than with distant

ones, because the former would more likely be trade creating, lead to a larger improvement in

welfare (of the home country), and thus be “natural,” and the latter would more likely be trade

diverting. As Bhagwati further notes, this argument itself rests on a syllogism, whose first

Uganda 1995 2000 2005 2009

TI with Kenya 50 347.10 152.17 134.90

TI with Tanzania 15 55.19 55.92 45.15

Tanzania 1995 2000 2005 2009

TI with Kenya 107.05 95.46 104.14 78.62

TI with Uganda 107.83 184.78 88.07 81.81

49

premise is that geographically proximate countries have higher volumes of trade with each

other than more distant ones do and whose second is that trade blocs between countries that

already trade disproportionately are less likely to divert trade. The results from my analyses

tend to agree with his argument.

3.3 Dynamic welfare gains

3.3.1 Expansion

It is fairly clear that with the expansion of a Regional Integration Arrangement gains

from integration will be enhanced. Large number of members means a large market that

member states will have a preferential treatment. This in turn encourages further trade

liberalization, minimizes cost of negotiation and improves welfare. Of course the optimal size

of integration is the inclusion of each and every country in the world under the same free trade

agreement (Krugman 1989). But this has proven difficult given the deadlocks in the current

WTO/GATT negotiations to achieve worldwide consensus. Furthermore, trade liberalization

at the global level has not always benefited all countries in an equitable manner (Rodrik 2006,

Stiglitz 2002). Regionalism can offer an alternative to liberalize trade among members as has

been seen in the case of EAC and further promote industrialization and development though

gradual process.

In this section I will try to outline some of the gradual and dynamic gains from

regional integration project in the EAC. As the “new” East African Community is in its early

ages (a little more than 11 years) some of the analysis here is hence to some extent

speculative. In this respect the future prospect of the RTA will be overviewed in relation to

issues such as issues of expansion, peace and development, good governance, foreign direct

investment and others to.

50

RTAs with many union members are more likely to be trade creating rather than trade

diverting. This is a fairly simple notion as a larger number of members will mean a larger

market that members will have preferential access to, and thus enlarged possibility of trade

creation. In this regard, the East African Community expansion ambitions are already

reflected by the accession of Rwandan and Burundi into the organization in 2007. Moreover,

South Sudan and Democratic Republic of Congo (DRC) have shown interest in joining the

Community (Allafrica.com 2011). This expansion is expected to facilitate economic

interdependence among some African nations hence leading to reduction of tensions between

antagonistic neighbors (Schiff &Winters 2003).

In addition, the EAC had signed various cooperation agreements with other regional

organizations in African such as COMESA in order to implement jointly the Economic

Community (EC) project in the entire Africa (COMESA 2010). Outside of Africa, the EAC is

working to strengthen relations with its most important trade partners like EU. On 27

November 2007 the Eastern African Community (Burundi, Kenya, Rwanda, Tanzania, and

Uganda) agreed a region-to-region interim Economic Partnership Agreement (EPA) with the

EU. This interim agreement (sometimes called a Framework EPA) mainly covers trade in

goods and fisheries and is a stepping stone towards a full EPA. A commitment was taken by

both parties to continue negotiations on services, investment, agriculture, rules of origin,

Sanitary and Phyto-sanitary Standards (SPS), Technical Barriers to Trade (TBT), customs and

trade facilitation and other trade-related rules in order to conclude a full EPA (European

Commission 2009). EAC is also expected to enhancing the regions negotiating capacity in the

WTO trade liberalization negotiations. EAC can help member states to overcome smallness

marketwise, therefore facilitating its negotiation leverage as it will taken more seriously by

other negotiating parties. Besides, the EAC can help in converging interests among member

states concerning WTO negotiation stand making it easier even for other WTO members to

51

deal with EAC rather than fragmented interests from individual states. This might even

facilitates WTO negotiations by reducing negotiation costs.

3.3.2 Peace and Security

Regional trade Agreements has been known to lessen the prevalence of violent cross

country conflicts between former enemy states (Shiff & Winters 2003). As the Intra-regional

trade and relations will increase due to the formation of RTA, this will further extend into the

political realm. With an increase in economic ties and benefits from integration the cost of

going to war will be higher as a result committing states to look for other creative solutions to

deal with conflicts.

In this regards EAC partner states – Kenya, Uganda, Tanzania, Burundi and Rwanda

are set to take their defence co-operation to a higher level in recent years. In the year 2008

the member states have signed defence agreements to upgrade the excising 1998

memorandum of understanding for cooperation in defence matters. The recent protocol is said

to have been more elaborate and binding on the EAC member states (EAC 2008).

Furthermore, these countries are cooperating to strengthen their maritime defence on the

Indian Ocean coastline and Lake Victoria to work together in areas of anti-piracy and counter

terrorism.

Maintaining peace and security in the EAC is an important prerequisite in developing

the social infrastructure of the region. The social infrastructure of an economy is said to be

defined as the government policies and institutions that maintain a coherent and meaningful

structure in society (Jones, 2002). Social infrastructure is an important determinant of the

level of investment in physical capital, the accumulation of skills, output, and consumption in

a country. With the formation of the EAC, it is expected that the region will improve its social

52

infrastructure so as to boost investment. Attracting foreign Directed Investments also requires

good economic and political governance on the part of member states in the EAC.

3.4 Discussion

The aim of this chapter was to have an ex-post analysis of the state of intra-regional

trade in the East African Community. The logic behind the structure of the chapter was first to

assess the state of tariff reduction in the EAC and changes that occurred due to the

establishment of the RTA. Then try to appraise its effects on trade within the regional and

outside. And finally, support my argument with other positive changes that occurred in the

region in connection to RTA formation.

As my tariff analysis above demonstrated there is considerable tariff reduction that has been

undertaken in the recent years by the main member countries in the EAC as result of the RTA

formation. Furthermore, from the tariff analysis one can conclude that the reductions have a

positive trade creating effect in both Kenya and Tanzania as they had higher tariff rates before

the signing of the Custom Union agreement. Especially Kenya benefits from trade

liberalization in the region as the formation of the Common External Tariff (CET) reduces the

tariff rate on most of its imports from the rest of the world. At the same time the internal tariff

significantly reduces the barriers to trade within the region. Overall it is safe to say that the

region benefits from tariff changes due to EAC establishment.

The trade pattern, composition and intensity analysis shows that the trade between

EAC and the rest of the World s is based on comparative advantage. But the intra-regional

trade shows a different pattern where member states deal with competitive advantages in the

manufacturing sector. The intra-trade is encouraging, Kenya and Tanzania especially, in

developing a comparative advantage in manufacturing some industrial products. The RTA

here is to some extent serving as experimental lab where member states attempt to engineer a

53

product that will also be competitive in the global market. This in the short run can facilitate

intra-industrial trade in the regional and in the long run can encourage industrialization and

economic development. On this regard, Cooper and Massell (1965), Johnson (1965) and

Bhagwati (1968) have already independently developed an approach to welfare-improving

customs unions in the context of developing countries wanting to achieve a certain level of

industrialization. The essential idea was that if a group of developing countries wanted to

achieve an exogenous level of industrialization, they could do so at a lower cost by

specializing among themselves through a customs union.

To get back to the research question, whether the formation of the EAC is welfare

enhancing, one cannot help but to incline to say that the formation of EAC is beneficial in

many respects. The descriptive analyses results show that there is a considerable chance that

the Regional Integration Agreement is a net trade creating one. Therefore, this supports the

conclusion that there is welfare gain from the establishment of the East African Community.

Nevertheless, this will be further investigated though an ex-ante WITS/SMART simulation

analysis in the next chapter.

54

Chapter IV: Partial equilibrium Model Welfare Analysis

In this Chapter, I will further analyze the welfare effects of the establishment of

custom union in the East African Community. Using a Partial Equilibrium Model to simulate

the effect of internal tariff reduction, I will investigate the trade creation and trade diversion

impacts together with welfare implications and revenue effects. This ex-ante analysis projects

the probable outcome from RTA formation provided the level of internal tariff reduction,

Common External Tariff and certain supply and demand elasticities. The objective is to take

the trade data before the establishment of the custom union in 2004 and simulate a scenario

where tariff is reduced to zero. This method is essential to get a comprehensive idea about the

assumed complete implementation of the Custom Union protocol and its probable welfare and

revenue outcome. The chapter starts with a description of the theoretical framework for the

analysis. I will also introduce and give a description of the WITS/SMART software

application which I used in this chapter to calculate welfare implications. The rest of the

chapter deals with results from the partial equilibrium analysis for the respective member

countries. Finally I will conclude the chapter with a discussion of the overall results and based

on the outcome I will give answer to my research question.

4.1 The partial equilibrium approach and WITS/SMART analysis

While there are many approaches to analyze the welfare effects due to custom union

formation, this chapter utilizes a partial equilibrium model to access market and calculates

trade creation and trade diversion. There are a number of advantages in adopting this model

for analysis. It has also a number of limitations. Its limitations arise from the fact that it is a

“partial” analysis of the effect of a given policy on a certain market that is directly affected.

55

The analysis is conducted based on pre-determined number of economic variables. That

means the analysis does not account for some economic interactions and feedbacks such as

between various markets in a given economy. On the other hand, the general equilibrium

approach can potentially model markets and interactions between different markets

simultaneously. It also takes into consideration inter-sectoral interactions and constraints in

relation to factors of production and movement of these factors of production across sectors.

However, the majority of the African countries are not individually captured in GTAP due to

lack of data disaggregation at the country level. Only a few countries are individually

represented, while most are part of composites of countries, such as the “rest of SACU”, the

“rest of Southern Africa”, and the “rest of sub-Saharan Africa”. “Consequently, partial

equilibrium modeling framework emerges as a second-best option for those countries that are

not captured individually in the GTAP database” (Lang 2006: 8).

The main advantage of the Partial Equilibrium model is its minimal data requirement

to assess markets and changes due to certain trade policy. In fact the only required data for

calculating welfare implications are trade flows (Import/Export), policy change (tariff change)

and some basic elasticities. This will make it ideal for analyzing trade policies in developing

countries where some data concerning market interactions are missing. The other advantage

of the partial equilibrium approach is that it allows for fairly detailed17 level analysis down to

effects on the market of a single product18. Hence, countering many “aggregation biases”.

4.1.1 The WITS/SMART simulation

As I described in the literature review section of the current thesis, the World

Integrated Trade Solution (WITS/SMART) model has been extensively and successfully used

to quantify the static effects of various free trade arrangements on markets in some African

17

partial equilibrium models provide results at a very disaggregated level (HS-6 in the case of this Thesis) 18

For instance effects of trade liberalization on cotton imports by Kenya will be very difficult to analyze with a

General Equilibrium model. The Partial Equilibrium model can better estimate the effects in such cases.

56

countries (DeRosa, Obwona & Roningen, 2002; Busse & Shams, 2005; Stahl, 2005; Lang

2006; Khorana, Kimbugwe & Perdikis 2008). The current thesis also employs the

WITS/SMART model19 from the World Bank to investigate welfare effects of regional trade

liberalization. WITS/SMART allows the user to simulate the effect of a trade policy change

on trade creation effects, trade diversion effects, net trade effects, tariff revenue variations and

changes in consumer surplus.

The model uses the following formulas to calculate trade creation and trade diversion.

Trade creation is calculated as:

TCijk

= M1

ijk * η *Δtijk / ((1+ tijk ) * (1- (η / β))

TC

ijk – Trade creation on commodity i imported from country k into country j

Mijk

– Imports of commodity i to country j from exporting country k

η – Import elasticity of demand in the importing country t

ijk - Tariff

β – Export supply elasticity

Similarly, the amount of trade diversion is estimated using the equation:

TDijk

– Trade diversion on commodity i imported from country k into country j

Mke

– Imports from Kenya

Mrow

– Imports from the Rest of the world

tijk -

Tariff ( t1

& t0

refer to post and pre integration tariffs)

λ – Substitution elasticity

Here it is useful to note that the extent of trade creation is influenced by import

demand elasticity. And the extent of trade diversion depends on the elasticity of import

substitution. On this regard the study employs the import demand elasticity inputs from the

World Bank survey conducted by Kee, Nicita & Olarreaga (2004, 2005). On the other hand,

19

http://wits.worldbank.org

57

Import substitution elasticities record the rate of substitution between two goods from

different origins. The Armington (1969)20 assumption is incorporated in SMART, meaning

that similar goods from different countries are imperfectly substitutable. In SMART, the

import substitution elasticity is considered to be 1.5 for each good.

Besides calculating trade creation and trade diversion, the WITS/SMART model also

analyzes net trade effects and revenue effects. The Net Trade effect is a simple addition of

trade creation effects and trade diversion effects.

TE= TC + TD

SMART also calculates the impact of the trade policy change on tariff revenue. The

custom revenue effect measures the change in revenue that is acquired from trade restrictions.

According to WITS/SMART, tariff revenue change on a given import flow is computed

simply as the final ad-valorem tariff multiplied by the final import value minus the initial ad-

valorem tariff multiplied by the initial import value. SMART uses the following formula to

calculate revenue effects:

ΔRijk / Rijk = (Δt

ijk / (1+ tijk )) * η * ((1 + β ) / (β – η)

Rijk

- Revenue effect of tariff change

η – Import elasticity of demand in the importing country tijk

- Tariff

β – Export supply elasticity

20 Within the Armington assumption, the representative agent maximizes its welfare through a two-stage

optimization process:

� First, given a general price index, she chooses the level of total spending/consumption on a “composite

good”, (say aggregate consumption of bananas). The relationship between changes in the price index

and the impact on total spending is determined by a given import demand elasticity.

� Then, within this composite good, she allocates the chosen level of spending among the different

“varieties” of the good, depending on the relative price of each variety (say, choose more bananas from

Ecuador, and less from Saint Lucia). The extent of the between-variety allocative response to change in

the relative price is determined by the Armington substitution elasticity.

58

Export supply elasticities, which are deemed in this case to be infinite (=99) mean that

an increase in demand for a given good will always be matched by the producers and

exporters of that good, without any impact on the price of the good. This is reasonably true for

specially the two EAC member states, Uganda and Tanzania, given their trade deficit with

Kenya (Khorana, Kimbugwe & Perdikis 2008).

Finally, the welfare effects are presented by the summation of consumer’s and

producer’s surplus and are calculated as:

Wijk = 0.5 (Δt

ijk * ΔMijk)

Mijk

– Imports of commodity i to country j from exporting country k

tijk

– Tariff

In the WITS/SMART, it should also be noted that the simulation model runs on

information contained in the UNCTAD managed TRAINS database. Also I want to reiterate

that intention of this investigation is not to predict what the trade will be in 2010 when the

custom union is completely implemented, rather its intention is to show the likely trade

creation and trade diversion effects of implementing internal tariff reduction and common

external tariff21 on the trade right before the formation of custom union.

4.2 Results of the simulation

4.2.1 Kenya

The table below shows the tariff reduction simulation for Kenya. The implementation of the

reduced intra-regional tariff on member states, which is to the rate of zero and the application

of the common external tariff on imports from the rest of the world on the trade data from

2004 will have the following effects:

21

The actually applied CET from was taken from 2010 UNCTAD data and was applied to the 2004 UNCTAD

data to simulate trade effects.

59

Table 4.1 Tariff reduction simulation results for Kenya

Kenya Complete Tariff reduction (2010)

In US$

Trade Creation 13,106,470

Trade Diversion 4,544,360

Net Trade Effect 17,642,280

Net Tariff Revenue -7,672,109

Net Welfare effect 1,934,799

Source: WITS/SMART simulation

The results indicate that there is a positive net trade creation effect for Kenya due to

the complete implementation of the custom union in the East African Community. There is

also a significant amount of trade diversion as efficient imports from the rest of the world are

in some cases replaced by less efficient products from the region. Furthermore, the results

indicate a negative revenue effect of about -7.7 million $ due to tariff liberalization with

Uganda and Tanzania. The tariff revenue loss corresponds to the transfer of capital from the

state to the consumers. This revenue loss is estimated in the Castro, Kraus & De la Rocha

(2004) study to be 16% of the total Kenya’s custom revenue income. As the custom revenue

is only 1% of the total tax collected the revenue losses are considered as moderate losses

(Castro, Kraus & De la Rocha 2004).

The net welfare effects indicate the net surplus for the consumers and producers within

the market. Unfortunately there is no separate numbers for consumers and produces in the

WITS/SMART simulation (Khorana, Kimbugwe & Perdikis 2008). It is also less likely that

the results will capture the real welfare effect on consumers and producers as it over assumes

about the preferences of consumers and producers. Notwithstanding the limitations the net

welfare results still show positive implications. But my main emphasis in this study will be

trade creation and trade diversion effects.

60

Table 4.2 Kenya Trade Creation and Trade Diversion Effects (Disaggregated) ($US)

Source: WITS/SMART Simulation

Table 4.2.2 shows the result of the WITS/SMART trade simulation for Kenya at a

more detailed aggregate product level. In this regard most of the trade effect was felt in the

wood and cork sector that is imported from Uganda. Kenya has historically depended on

Uganda for its wood and cork imports. The aim in this case is to prevent depletion of Kenyan

forests to supply its wood and cork demands (Export Processing Zones Authority 2005). The

regional tariff reduction on these products will lead to more trade between Kenya and Uganda

with a positive trade creation effects. In the case of Kenyan trade relations with Tanzania,

majority of the net trade effects are portrayed in the chemical related products and

Product Trade

Creation

Trade

Diversion

Trade

Effect

Revenue

Effect

Welfare

Effect


485,600 82,170 568,230 -184,392 48,469


999,800 923,000 1,922,300 -1,113,000 219,899


except fuels 5,385,000 1,446,000 6,831,000 -2,366,000 806,480


and related materials 538,600 626,100 1,165,300 -865,194 127,600


fats and waxes 229,500 69,900 299,300 -151,378 27,000


1,640,200 253,200 1,887,800 -1,307,000 182,800

Manufactured goods

1,430,600 319,500 1,747,100 -789,381 220,270


1,941,000 318,400 2,258,000 -369,564 226,700

Miscellaneous manufactured

articles

440,000 482,000 923,000 -500,000 71,828



16,170 24,090 40,250 -26,200 3,753

Total:

13,106,470

4,544,360

17,642,280

-7,672,109

1,934,799

61

manufactured goods22. Similarly the simulation output in this regard shows a net trade gains

with a positive trade creation effects.

In the level 1 aggregate product analysis23, the only case trade diversion significantly

exceeds trade creation is in the Mineral fuels, lubricants and related materials sector. Imports

tariff reduction on Petroleum and petroleum related products from Uganda will have a net

trade diverting effect as Uganda’s petroleum exports lack the efficiency to compete with other

well developed oil exporting countries from the rest of the world. With the recent discovery of

substantial petroleum deposits in Uganda, the country is home to about 2.5 billion barrels of

oil, with more to be discovered in the near future (Tumusiime 2011). For this sector to be

more competitive in the world market, Uganda wants to construct a $ 4.6 billion oil refinery

in Kabale-Buseruka. The planned construction will commence in 2012 and is expected to

commission in 2018. Uganda is also looking into effective ways of delivering oil to markets

in the region and beyond (Tumusiime 2011). Recently, Uganda is aiming to setup an oil

pipeline that will stretch to Kenya. The project, with an anticipated cost of $ 110 million is

expected to reduce delivery cost and hence propping efficiency in petroleum production. The

project is expected to get some support from Kenya as part of regional cooperation between

the two states (Reuters 2011). This cooperation is expected to encourage the oil sector in

Uganda to be more competitive and less costly to the consumers in neighbouring Kenya.

To summarize, the simulations based on the 2004 trade data for Kenya demonstrates

an exceeding amount of trade creation and a lesser amount of trade diversion. Accordingly,

application of regional trade liberalizing and regional tariff reduction policy is expected to

promote trade creation in the region, therefore enhancing welfare gains for Kenya.

22

For a more detailed demonstration of the WITS/SMART simulation results refer to Appendix IV. 23

The table 4.2.2 shows the analysis based on level 1 SITC revision 3 data from the UNCTAD’s TRAINS.

62

4.2.2 Uganda

The impact of the establishment of East African Community Custom Union on the

Ugandan trade patterns, direction and composition has already been discussed in the previous

chapter. As I mentioned Uganda remains to be the largest importer of manufactured goods

from the region. This is especially true in its trade relations with the neighbouring Kenya.

Uganda still remains to be Kenya’s major trading partner and with the reduction of trade

barriers between these two nations, it is likely that trade between them will boost as never

before. The question here is to what extent is this trade beneficial to Uganda.

Table 4.3 Tariff reduction simulation results for Uganda ($US)

Uganda Complete Tariff reduction (2010)

In US$

Trade Creation 45,671,250

Trade Diversion 3,500,460

Net Trade Effect 49,175,230

Net Tariff Revenue -11,251,449

Net Welfare effect 837,286


The intensity of Uganda’s trade within the region is reflected in the simulation results

as can be inferred from the above table. After the EAC these intra-regional imports with

reduced tariffs are likely to create more trade than they divert. This is true despite the

common external tariff that will increase the tariff rate on non-EAC imports. The lower

amount of trade diversion is attributed to Uganda’s high amount of imports from the region

even before the establishment of EAC. Kenya’s trade intensity with Uganda has always been

extremely high24. In some cases 1000 times higher than would be expected. The relationship

between trade intensity and welfare gains from a PTA has already been noted by Krugman

(1991) when he stated “if a disproportionate share of world trade would take place within

24

Refer to table 3.7

63

trading blocs even in the absence of any preferential trading arrangement, then the trade

creation within the blocs are likely to outweigh any possible losses from external trade

diversion” (Krugman 1991: 21). Pangariya (1997), however, argued on the other direction. If

countries are natural partners with an intense trade before RTA formation, trade liberalization

will only decrease tariff revenue as there will be no significant increase in imports. Therefore,

“the more natural are the trading partners, the less is the gain from their own preferential

liberalization” (Pangariya 1997: 476). The simulations results as shown in the table above

reveal otherwise. Even though the revenue loss is significantly higher when compared to the

simulations for Kenya, tariff reduction has led to more consumption hence more trade is

created.

Table 4.4 Uganda Trade Creation and Trade Diversion Effects (disaggregated) ($US)


Product Trade

Creation

Trade

Diversion

Trade

Effect

Revenue

Effect

Welfare

Effect


221,300 59,810 281,100 -127,031 12,018


706,000 251,200 957,200 -656,458 43,898


except fuels 39,882,000 468,700 40,351,000 -5,435,150 537,944


and related materials 770,900 463,990 1,234,800 -940,121 52,100


fats and waxes 747,300 438,700 1,185,800 -724,311 33.952


247,400 103,200 350,500 -170,214 12,953

Manufactured goods

840,800 376,000 1,221,000 -796,262 61,591


1,392,000 642,600 2,031,000 -1,489,930 52,517


684,580 549,700 1,236,300 -719,179 51,907



178,970 146,560 326,530 -192,793 12,324

Total:

45,671,250

3,500,460

49,175,230

-11,251,449

837,286

64

A more detail look at the trade creation and diversion results disclose the net trade

effects. And most of the trade effect took hold in the crude material section. Especially

imports of fertilizers and construction materials from Kenya will be affected by the tariff

reduction agreement. This is specially important with the growing demand for construction

materials due to the rapid growing construction sector that is growing 13% per annum

(Uganda Bureau of Statistics 2006).

In summary, a positive trade creation effects suggest that inter-regional trade will grow

under the EAC since imports from Kenya will be cheaper after imposition of common

external tariff on trade with the rest of the world. The total amount of trade diversion is less

than 25% of the total trade created; hence confirming the rationale in the EAC members’

initial optimism expressed by the EAC treaty negotiators and phased tariff reductions within

the Custom Union protocol. Even though, there were initial wide concerns regarding revenue

losses, there is an increase in revenue in the EAC (Mugisa et.al 2009). The net welfare gains

from regional integration also show positive signs for Uganda.

4.2.3 Tanzania

Compared to Kenya and Uganda, Tanzania trades less regionally. Import from Kenya

has been growing since the establishment of the East African Community. On the other hand,

the proportion of trade with Uganda has declined over time to less than 20% in 2008 from

over 35% in 2004 for exports. Similarly, Tanzania’s imports from Uganda as a proportion of

total EAC imports saw a consistent annual decline from 6.5% in 2004 to about 3% in 2008

(Mugisa et.al 2009). Tanzania’s imports from Uganda consisted of maize, tobacco, distilled

fuel, Portland cement, soya been flower, aviation kerosene and self propelled bulldozers and

angle dozers (Mugisa et.al 2009).

65

Tanzania trade with Kenya showed better sign of improvement since the formation of

the custom union. Tanzania’s exports to Kenya have significantly increased from US $ 90.1

million in 2004 to about 231.5 million in 2008. Imports also ascended by 50% from US$

131.5 million to US$ 197.9 million during the same period. Hence, Kenya remains to be

Tanzania’s main trade partner in the region, accounting for more than 80% of Tanzania’s

exports region, and 96% of her imports from the region in 2008. In the table below we can see

the likely effects of the custom union on static gains from regional trade (Mugisa et.al 2009).

Table 4.5 Tariff reduction simulation results for Tanzania ($US)

Tanzania Complete Tariff reduction (2010)

In US$

Trade Creation 3,366,760 Trade Diversion 1,660,124 Net Trade Effect 5,030,750 Net Tariff Revenue -2,508,593 Net Welfare effect 694,992


As shown in the Table 4.5, the net trade effect of tariff reduction is significantly lower

compared to Kenya and Uganda. This is as a result of the portion of intra-regional trade in the

total trade of Tanzania, which is significantly low. This phenomenon might be related to the

similar nature of Ugandan exports with that of Tanzania. Uganda’s exports lack

diversification and are usually primary goods. These products are not the type of products that

Tanzania mainly imports. Also In the simulation for Tanzania, there was concern that the

elimination of internal tariffs and adoption of a CET would lead to revenue losses of up to

1.2% of the total. These estimates were based on static simulations on the assumption that a

0% tariff structure for primary, intermediate and finished import commodities would be

adopted. In addition, a CET structure of 0%, 10% and 25% on primary, intermediate and

finished import commodities are taken into consideration. However, recent researches on the

66

matter reveal that revenue earnings are rising at a higher average rate (Mugisa et. al 2009).

This is attributed to improved efficiency in collecting government taxes.

Table 4.6 Tanzania Trade Creation and Trade Diversion effects (disaggregated) ($US)

Product Trade

Creation

Trade

Diversion

Trade

Effect

Revenue

Effect

Welfare

Effect


153,500 39,000 192,300 -92,477 10,907


290,900

139,100 430,000 -306,381 23,614


except fuels 1,260,500 263,300 1,523,900 -270,830 147,909


and related materials 495,560 440,470 936,000 -613,082 57,569


fats and waxes 235,300 183,300 418,600 -236,757 30,727


60,200 12,300 72,500 -20,946 5,286

Manufactured goods

166,400 76,904 247,300 -152,036 20,541


481,400 229,400 710,800 -518,577 40.289


152,100 203,300 354,400 -197,318 19,617



70,900 73,050 144,950 -100,189 378,782

Total:

3,366,760

1,660,124

5,030,750

-2,508,593

694,992


Tanzania mainly imports gas oil, residual fuels, illuminating kerosene, diesel oil,

motor spirits, medicaments, rolled iron/steel, flat/cold-rolled iron/steel an maize starch

(Mugisa 2009). This is also reflected in the disaggregated simulation results as presented

above. Most of the trade occurred in the crude material products (such as construction

materials) and mineral fuels, lubricants and related materials. From the simulation results for

mineral fuels and lubricants one can observe that the trade created in this product category is

almost the same as the trade diverted. Also the tariff revenue losses with regards to these

67

products are significantly high. This entails that there are more efficient producers outside of

the region that can supply these products more efficiently. Therefore, the internal tariff

reduction and the setting up of common external tariff on these products are likely to have

negative effect on welfare. Nevertheless, the overall effect of the custom union suggests

positive benefits for Tanzania.

4.3 Discussion

In every simulation that is conducted for the respective member states, the trade

creation results are momentously higher than the trade diverted. Although we should be

careful in interpreting these results as the study used a partial model to analyze them, the fact

that they confirm the descriptive analysis results from the previous chapter suggests they

deserve considerable attention. The tariff change analysis in the chapter three suggested that

Uganda will likely experience trade diversion as the common external tariff will increase the

tariff rate on imports from the rest of the world. But with the further trade creation and trade

diversion analysis in this chapter I was able to observe that the trade diversion is less than

expected as Uganda acquires significant portion of its imports from the region. This is true

even before the formation of the East African Community. For this reason, internal tariff

reduction creates more trade than what common external tariffs divert.

According to the detailed product level analysis, the likelihood of trade diversion is

higher in the mineral fuel and lubricant trade between the member states. This can be

explained by re-export practices by Kenya particularly petroleum products to the markets both

in Uganda and Tanzania (Mugisa et. al 2009). It was reported that before the Custom Union

Kenya’s re-exports reached as high as 60% and 45% of the total exports to Uganda and

Tanzania respectively. But it was stabilized at about 10% of the total exports in recent years.

This re-exports will eventually contribute to the diversion of trade from the original producers

68

of the re-exporter. The application of rules of origin due to custom union will assist in

determining the product’s true country of origin hence resolving the issue of re-exporting.

With regards to the research question, whether the regional integration in the Eastern

Africa is beneficial to member states, the partial equilibrium analysis in this chapter divulges

that there is at least a static welfare gains from trade as a result of regional tariff reductions.

Even though the gains are minimal as a result of low intra-regional trade, the EAC holds

future prospects for the development of the member states as it creates more trade than it

diverts.

69

Chapter V: Conclusion

The objective of the current thesis was to investigate the benefits of forming a regional

trade arrangement in the Eastern Africa. It had also reflected on the old debate regarding

multilateralism versus regionalism. This debate is far from over as proponents of both trading

systems look for way to explain the recent widespread move towards regionalism around the

world. Why do countries prefer regional or bilateral arrangements instead of going for global

free trade regime? This question has puzzled many economists, and they have proposed a

variety of explanantia.

In this respect, Africa, the continent with the largest number of regional organizations

lacks the deserved attention. While undergoing this exercise, I couldn’t help but to notice that

even with the powerful tide of regionalization in the African continent, the situation has

developed for decades without the benefit of theory. The current study aims to fill part of that

gap. My thesis does not specifically deal with the broad question “What drives regionalism in

Africa?” However, in the second chapter of this study, I have attempted to frame the

formation of RTA in East Africa in the context of the ongoing debate about regionalism.

Accordingly, the “natural trade partners” thesis was applied to explain how the East African

Community is formed. The natural trading partners thesis proposed the idea that geographical

closeness, cultural commonness and other similar features will draw countries to have tight

trade relations than normally expected. Therefore, there is a higher tendency that these

countries will integrate to strengthen their economic ties. The trade intensity analysis in the

third chapter revealed the high concentration of trade between the EAC countries, even before

the formation of RTA. And this is related to the member states’ past history, geographical

closeness and cultural similarity.

70

Drawing on this theoretical background, I have then taken on the challenge of

empirically investigating the benefits of trading regionally in that part of Africa. The

empirical investigation of the welfare condition in the East African Community employed the

theory of trade creation and trade diversion to evaluate regional trade liberalization. With two

types of analysis modeling, descriptive statistics and partial equilibrium equation, I have

calculated the implication of reducing tariff within the region together with the setting up of

common external tariff on extra-regional imports. The results from both analyses support the

conclusion that custom union formation in the EAC has a trade creating tendency, hence

welfare enhancing in this regard. Besides this main finding, I also noticed that the regional

arrangement contributes to industrialization in the region, consequently, aiding the

development endeavours. The results of the current study also confirm the validity of previous

complaints by Uganda and Tanzania, regarding Kenya’s disproportionate gains from the

regional trade arrangement. In this concluding section, I will highlight the implication of these

results to regionalization in the Eastern Africa. I will also attempt to connect the findings to

the broader picture of regionalism in the African continent.

From the simulation results we can deduct that the East Africa community doesn’t

have adverse effects on any of the member states. This implies the “new” East African

community will strengthen further as all of the major partner states have stake in preserving

the organization. According to my analysis and previous literatures, its weakness emanates

from relatively low amount of intra-regional trade and some distributional issues. After 6

years of the establishment of the East African Community custom union intra-regional trade is

yet to pick up. It is currently around 13% of total trade of the region and compared to

European Union (60%) and in NAFTA (40%). The EAC has lots of room for improvement in

this respect. The second EAC Development Strategy (2001-2005) puts non-tariff barriers as

major impediments to trade in the region. This non-tariff Barriers include administrative and

71

bureaucratic inefficiencies, poor infrastructure and communication and lack of sufficient

information about the custom union on the side of the ordinary citizens of EAC (Mugisa et.al

2009). Serious attention must be given to alleviate these hindrances if trade in the region is to

pick up. Other trade impediments rise from unilateral imposition of product standards and

technical requirements. These unilateral impositions can have serious consequences especially

if they are imposed to protect local industries (Mugisa et.al 2009). These non-tariff barriers in

some instance also encourage illicit cross-border trades.

Some authors also consider the unequal trade gains in the EAC as a threat to regional

arrangement (Stahl 2005, Katembo 2008). Also the descriptive statistic model and the trade

simulation in the current thesis show that Kenya exports large amount of manufactured goods

to the other two members, while importing mostly cheaper primary good. The tariff reduction

further promotes Kenya’s exports and makes them more competitive in the region. This adds

pressure on relatively weaker local manufacturing industries in Uganda and Tanzania. This in

turn might add to protectionist sentiments that threaten trade liberalization. On the other hand,

hegemonic stability theory emphasizes the role of the dominant power in stabilizing a regional

system. Even though, it will be hard to conclude that Kenya is playing a hegemonic role in the

region currently, it is likely that it will intensify its role as gains from the regional bloc

increase in the future.

The other noteworthy finding in this empirical study is the contribution of the EAC to

industrialization in the region. One of the main challenges among the list developed nations

has been attaining economic transformation and diversification that is necessary for their

development. Most developing countries in Africa highly depend on the agricultural sector

that usually fails to generate enough income and saving for their industrialization.

Agricultural markets usually fail due to variety of reasons and result in economic stagnations

and even decline in some of the Eastern African states. This has led to wide spread starvation

72

and hunger and in some cases caused political instability and conflict. If surplus is to be

redistributed to a less fortunate part of a country and extreme poverty is eradicated, these

states need an economic sector that can generate enough surplus to compensate drought hit

regions. Industrialization has made it possible for many of the currently developed nations to

get out of poverty. Hence, if the EAC is in anyway contributing to industrialization in the

region then it is most likely that it will be welcomed. In this sense it can contribute to poverty

reduction in the region and play a role in the effort to achieve the millennium development

goals.

I will be really careful to make some generalizations about regional arrangements in

Africa beyond the empirical analysis that was undertaken. What I want to emphasis is the

need to acknowledge diversities in regionalization processes and the effect of these processes

within Africa. With similar investigations on other regional blocs, one can have a better

picture of regionalism in Africa. One contribution of this thesis can be to add to the literature

on this respect. The thesis can also be further complemented by investigations regarding non-

trade welfare gains due to the formation of The East African Community.

73

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Appendix I

Table 3.2 Tariff Changes on imports from China into EAC

2001 2004 2005 2010

Kenya

Simple Average 21.77 17.17 13.91 12.85



2001 2004 2005 2010

Uganda

Simple Average 9.38 8.88 15.83 14.52



200125 2004 2005 2010

Tanzania

Simple Average 19.38 16.32 14.39 13.65



Source: UNCTAD

25

Here as well the tariff rates in 2001 and 2004 are replaced by 2000 and 2003 respectively due to lack of

available data.

80

Appendix II

Revealed Comparative Advantage Analysis of Kenya, Uganda and Tanzania

(2003-2009)

Kenya

2003 2005 2007 2009 Live animals except fish

0.3749 0.3982 0.2386 0.2386

Meat & preparations

0.1929 0.2583 0.3313 0.3313

Dairy products & eggs

0.1595 0.308 0.8967 0.8967

Fish/shellfish/etc.

3.1308 2.769 2.5859 2.5859

Cereals/cereal preparatn

0.8353 0.6304 0.8163 0.8163

Vegetables and fruit

8.9166 8.5401 9.4906 9.4906

Sugar/sugar prep/honey

7.3301 5.6015 7.5161 7.5161

Coffee/tea/cocoa/spices

52.0119 50.0556 51.1103 51.1103

Animal feed ex unml cer.

0.0629 0.0422 0.1471 0.1471

Misc food products

1.6141 2.4186 4.0931 4.0931

Beverages

0.2753 0.3064 1.4752 1.4752

Tobacco/manufactures

6.7497 8.3899 14.5676 14.5676

Hide/skin/fur, raw

3.4191 4.1227 0.7766 0.7766

Oil seeds/oil fruits

0.4798 0.571 0.8662 0.8662

Crude/synthet/rec rubber

0.027 0.0254 0.0044 0.0044

Cork and wood

0.0774 0.0459 0.0533 0.0533

Pulp and waste paper

0.0338 0.0006 0.0149 0.0149

Textile fibres

3.1723 2.7068 3.3656 3.3656

Crude fertilizer/mineral

10.0235 4.9947 6.3551 6.3551

Metal ores/metal scrap

0.2891 0.3336 0.4474 0.4474

Crude anim/veg mater

nes

30.7266 33.1243 43.8122 43.8122

Coal/coke/briquettes

0.0068 0.0091 0.0009 0.0009

Petroleum and products

2.7723 1.9864 0.4371 0.4371

Gas

natural/manufactured

0.0399 0.0434 0.0528 0.0528

Animal oil/fat

0.0452 0.0073 0.1775 0.1775

Fixed veg oils/fats

4.6241 3.0386 3.173 3.173

Animal/veg oils procesd

1.4005 2.8006 3.8313 3.8313

Organic chemicals

0.0992 0.0686 0.1439 0.1439

Inorganic chemicals

0.5246 5.1185 4.2691 4.2691

Dyeing/tanning/color mat

0.3654 0.5009 0.7548 0.7548

Pharmaceutical products

0.3911 0.3713 0.5709 0.5709

Perfume/cosmetic/cleansr

1.4118 2.7702 2.0215 2.0215

81

Manufactured fertilizers

4.3685 1.1801 1.8346 1.8346

Plastics in primary form

0.1281 0.1647 0.207 0.207

Plastics non-primry form

0.2664 0.465 0.7046 0.7046

Chem material/prods nes

0.3042 0.7836 0.5788 0.5788

Leather manufactures

1.7385 2.4586 4.8629 4.8629

Rubber manufactures nes

0.4893 0.5302 0.4939 0.4939

Cork/wood manufactures

0.6928 0.5918 0.7608 0.7608

Paper/paperboard/article

0.8539 0.819 1.0994 1.0994

Textile yarn/fabric/art.

0.5054 0.7116 0.7749 0.7749

Non-metal mineral manuf.

0.8898 0.9468 1.4926 1.4926

Iron and steel

1.0131 1.1731 0.8982 0.8982

Non-ferrous metals

0.4081 0.3169 0.408 0.408

Metal manufactures nes

0.6054 0.5305 0.7335 0.7335

Power generating

equipmt

0.0615 0.0443 0.0768 0.0768

Industry special machine

0.2443 0.1236 0.1177 0.1177

Metalworking machinery

0.0489 0.055 0.0467 0.0467

Industrial equipment nes

0.1029 0.093 0.1189 0.1189

Office/dat proc machines

0.0157 0.021 0.0444 0.0444

Telecomms etc

equipment

0.0281 0.0233 0.1191 0.1191

Electrical equipment

0.0529 0.0713 0.1171 0.1171

Road vehicles

0.1059 0.1223 0.1435 0.1435

Railway/tramway

equipmnt

0.0537 0.0371 0.2292 0.2292

Building fixtures etc

0.3718 0.3914 0.5004 0.5004

Furniture/furnishings

0.2531 0.3485 0.3683 0.3683

Travel goods/handbag/etc

0.1782 0.1538 0.0942 0.0942

Apparel/clothing/access

0.0979 2.0418 2.344 2.344

Footwear

1.1071 1.213 1.89 1.89

Scientific/etc instrumnt

0.1051 0.0625 0.0914 0.0914

Photographic equ/clocks

0.129 0.1295 0.0788 0.0788

Misc manufactures nes

1.316 0.9064 1.0614 1.0614

Gold non-monetary ex ore

1.4236 0.661 2.7747 2.7747

Uganda

2003 2005 2007 2009 Live animals except fish

0.089 0.0856 1.1487 2.0404

Meat & preparations

0.0087 0.1489 0.0304 0.0511


0.29 0.1162 0.1016 0.8782

Fish/shellfish/etc.

22.2175 26.765 15.1922 10.8106

Cereals/cereal preparatn 4.141 5.5407 4.1344 3.911


1.5339 1.4656 1.4012 1.3121

Sugar/sugar prep/honey 0.4812 3.6584 11.8908 10.8346

82

Coffee/tea/cocoa/spices 67.4068 66.8857 59.9813 44.9629

Animal feed ex unml cer. 0.454 0.6977 0.7743 0.68

Misc food products

0.6774 0.8106 3.4065 0.639

Beverages

0.6542 1.3849 3.5445 3.8563


28.7799 16.3453 23.405 14.3528

Hide/skin/fur, raw

8.9277 9.8356 5.6837 0.5451


2.3116 3.2731 2.4344 2.8632

Cork and wood

0.0083 0.0203 0.0764 0.1475


0.0015 0.0143 0.0062 0.0485

Textile fibres

14.3121 19.5727 10.012 9.7112


0.6985 0.5523 0.2501 0.4195


0.2289 1.7189 1.0993 0.5768

Crude anim/veg mater nes 18.2145 18.1065 14.8208 11.9818


0.7612 0.4416 0.3144 0.6853

Gas natural/manufactured 0.0002 0 0.0006 0.0004

Electric current

12.6419 2.6671 3.2379 3.4367

Fixed veg oils/fats

1.1302 0.8585 3.757 2.0502


7.1292 17.7254 61.0478 38.6211

Organic chemicals

0.0134 0.0285 0.0514 0.0916

Inorganic chemicals

1.0746 0.1592 0.1444 1.3758

Dyeing/tanning/color mat 0.0961 0.2233 0.3996 0.5327

Pharmaceutical products 0.17 0.0568 0.0673 0.0651

Perfume/cosmetic/cleansr 1.455 1.8345 2.4078 1.8476

Manufactured fertilizers 0.2075 0.0238 0.0319 0.008


0.0296 0.0966 0.0624 0.0999

Plastics non-primry form 0.0533 0.0961 0.1645 0.3631

Chem material/prods nes 0.0744 0.0734 0.0783 0.0867


0.099 0.245 4.2724 1.7048

Rubber manufactures nes 0.082 0.051 0.0587 0.0868

Cork/wood manufactures 0.292 0.4542 0.4492 0.3264

Paper/paperboard/article 0.1706 0.2689 0.2928 0.3878


0.1461 0.3188 0.4324 0.4257

Non-metal mineral manuf. 0.1813 0.2282 1.1144 3.0701

Iron and steel

0.8674 1.1927 1.3788 2.1107

Non-ferrous metals

0.0272 0.0177 0.0304 0.4929


0.1414 0.3467 0.3127 0.3689

Power generating equipmt 0.0158 0.0606 0.086 0.0831

Industry special machine 0.1732 0.209 0.196 0.9702

Metalworking machinery 0.1918 0.3425 1.9952 1.4696

Industrial equipment nes 0.2131 0.0478 0.0632 0.0823

Office/dat proc machines 0.0421 0.0144 0.0329 0.0251

Telecomms etc equipment 0.0492 0.4137 1.5687 0.9706


0.0177 0.0223 0.044 0.0521

Road vehicles

0.1274 0.1836 0.3129 0.5004

Railway/tramway equipmnt 0.1202 0.0785 0.1878 0.42

83


0.0139 0.0733 0.2053 0.3514


0.0863 0.3516 0.4575 0.3089

Travel goods/handbag/etc 0.0083 0.0222 0.077 0.0545

Apparel/clothing/access 0.114 0.218 0.0879 0.038

Footwear

0.0245 0.1006 0.4932 1.7489


0.057 0.0463 0.1003 0.1274

Photographic equ/clocks 0.015 0.0618 0.1093 0.0363


0.7654 0.1345 0.2954 0.1881

Gold non-monetary ex ore 15.8915 27.0048 10.137 0.9271

Tanzania

2003 2005 2007 2009

Live animals except fish

0.8806 0.6149 0.5276 0.3823

Meat & preparations

0.0079 0.0196 0.1359 0.3823


0.0172 0.0803 0.0636 0.0442

Fish/shellfish/etc.

16.7921 14.0629 13.3525 6.6479

Cereals/cereal preparatn 2.7318 4.492 5.4464 0.804


5.9769 5.0032 4.2162 4.3982

Sugar/sugar prep/honey 3.8132 3.0794 5.4127 0.6361

Coffee/tea/cocoa/spices 18.9683 18.5287 20.2096 14.2905

Animal feed ex unml cer. 1.285 1.6993 1.4191 2.0927

Misc food products

0.04 0.0616 0.2567 0.0671

Beverages

0.2719 0.4023 0.361 0.4334


14.6331 33.6634 21.0312 11.8171

Hide/skin/fur, raw

6.3076 4.9718 5.8881 1.8232


6.0689 6.6044 6.8955 6.93

Crude/synthet/rec rubber 0.0101 0.0112 0.2962 0.0346

Cork and wood

1.0841 1.2171 1.6952 3.0599


0.1556 0.0342 0.0161 0.0088

Textile fibres

16.6297 29.3995 20.3098 21.3878


2.8104 1.081 7.0512 3.2784


7.365 5.414 6.5054 12.2192

Crude anim/veg mater nes 6.0524 4.9936 7.7206 6.0473

Coal/coke/briquettes

0.0005 0.0016 0.0006 0.0014


0.0084 0.2581 0.0674 0.0595

Gas natural/manufactured 0.0002 0.0069 0.0317 0.0918

Animal oil/fat

0.1292 0.2819

0

Fixed veg oils/fats

0.6202 1.2347 2.5222 0.928


2.2553 2.4977 1.488 3.1574

Organic chemicals

0.0023 0.0076 0.0363 0.0093

Inorganic chemicals

0.0225 0.0772 0.1076 0.0926

Dyeing/tanning/color mat 0.426 0.3889 0.3136 0.1955

Pharmaceutical products 0.0364 0.0289 0.0413 0.0696

84

Perfume/cosmetic/cleansr 0.6819 0.7304 0.8881 0.7506

Manufactured fertilizers 0.0239 0.7494 4.7458 3.8789


0.0134 0.1668 0.1566 0.1177

Plastics non-primry form 0.0193 0.0919 0.127 0.147

Chem material/prods nes 0.0104 0.0323 0.0324 0.0487


0.1689 0.3311 2.6978 1.6394

Rubber manufactures nes 0.0525 0.2801 0.5054 0.0751

Cork/wood manufactures 0.179 0.4094 1.1458 0.4077

Paper/paperboard/article 0.0171 0.1485 0.4774 0.6365


0.7155 0.8854 1.472 2.407

Non-metal mineral manuf. 2.292 1.2922 1.9592 1.204

Iron and steel

0.2099 0.304 0.1424 0.25

Non-ferrous metals

0.0307 0.4191 0.215 0.0992


0.0278 0.1842 0.388 0.1679

Power generating equipmt 0.0016 0.0173 0.2646 0.5222

Industry special machine 0.0142 0.1762 0.2557 0.3153

Metalworking machinery 0.0164 0.1014 0.1209 0.2668

Industrial equipment nes 0.0034 0.0313 0.0841 0.0723

Office/dat proc machines 0.0018 0.0207 0.0102 0.0178

Telecomms etc equipment 0.0018 0.0343 0.0432 0.0775


0.0182 0.0392 0.167 0.1854

Road vehicles

0.0005 0.063 0.101 0.0741

Railway/tramway equipmnt 0.0007 0.0167 0.0426 0.0604


0.0163 0.04 0.0244 0.0166


0.0255 0.041 0.1416 0.0938

Travel goods/handbag/etc 0.0006 0.0049 0.0328 0.014

Apparel/clothing/access 0.1444 0.1391 0.1925 0.1165

Footwear

0.1866 0.2767 0.3698 0.2397


0.0028 0.0263 0.0665 0.0822

Photographic equ/clocks 0.0013 0.0175 0.0956 0.0594


0.0975 0.1624 0.5809 0.2023

Gold non-monetary ex ore 98.1874 99.1153 53.9807 30.4529

Source: UN COMTRADE

85

Appendix III

WITS/SMART Simulation Results for Kenya (Level.6 SITC Rev-3

UNCTAD)

Reporte

rName

PartnerN

ame

Product

Code

TradeT

otalEff

ect in

1000

USD

TradeCreati

onEffect in

1000 USD

TradeDivers

ionEffect in

1000 USD

OldSimple

DutyRate

NewSimple

DutyRate

Kenya Uganda 10290 10.34 9.453 0.887 5 0

Kenya Uganda 40900 6.573 3.561 3.013 25 0

Kenya Uganda 60210 0.197 0.096 0.101 5 0

Kenya Uganda 71339 10.092 5.272 4.82 35 0

Kenya Uganda 90190 0.335 0.177 0.158 15 0

Kenya Uganda 100510 0.436 0.164 0.272 25 0

Kenya Uganda 100590 105.66

4

44.721 60.943 25 0

Kenya Uganda 100630 36.507 9.319 27.188 35 0

Kenya Uganda 100700 0.14 0.122 0.017 15 0

Kenya Uganda 100820 0.42 0.003 0.417 15 0

Kenya Uganda 110100 6.427 2.99 3.437 60 0

Kenya Uganda 110210 13.031 12.925 0.107 15 0


9

191.325 37.074 35 0

Kenya Uganda 110290 0.61 0.178 0.432 15 0

Kenya Uganda 110320 0.526 0.428 0.098 15 0

Kenya Uganda 110820 0.229 0.229 0 15 0

Kenya Uganda 120100 6.408 2.037 4.371 5 0

Kenya Uganda 120210 0.195 0.102 0.093 5 0

Kenya Uganda 120720 0 0 0 0 0

Kenya Uganda 120810 9.487 9.042 0.445 15 0

Kenya Uganda 121020 0 0 0 0 0

Kenya Uganda 150600 0.354 0.354 0 15 0

Kenya Uganda 151610 0.458 0.234 0.223 15 0

Kenya Uganda 151790 4.472 1.188 3.285 30 0

Kenya Uganda 151800 20.571 10.423 10.147 35 0

Kenya Uganda 200980 8.076 2.178 5.898 28.33 0

Kenya Uganda 200990 17.001 5.247 11.754 35 0

Kenya Uganda 230210 1.776 1.02 0.756 15 0

Kenya Uganda 230220 0.368 0.368 0 15 0

Kenya Uganda 230230 148.15 148.155 0 15 0

86

5

Kenya Uganda 230610 20 20 0 15 0

Kenya Uganda 230630 0.244 0.244 0 15 0


21

4410.508 1203.514 20 0

Kenya Uganda 271019 67.789 44.625 23.164 5.53 0

Kenya Uganda 282720 0 0 0 0 0

Kenya Uganda 290230 0 0 0 0 0

Kenya Uganda 291511 0 0 0 0 0

Kenya Uganda 300490 13.125 4.171 8.953 7.5 0

Kenya Uganda 320110 0 0 0 0 0

Kenya Uganda 320420 0 0 0 0 0

Kenya Uganda 320810 0.422 0.138 0.283 30 0

Kenya Uganda 321511 10.007 3.915 6.091 25 0

Kenya Uganda 321519 2.016 0.06 1.955 25 0

Kenya Uganda 321590 14.71 3.301 11.409 13.75 0

Kenya Uganda 330290 1.886 0.773 1.113 21.67 0


8

18.7 106.368 35 0

Kenya Uganda 330510 0.29 0.079 0.211 35 0

Kenya Uganda 330790 14.428 6.361 8.067 28 0

Kenya Uganda 340111 4.376 1.567 2.809 35 0

Kenya Uganda 340119 79.042 68.447 10.594 35 0

Kenya Uganda 340219 13.059 5.339 7.72 35 0

Kenya Uganda 340220 34.952 12.714 22.238 25 0

Kenya Uganda 370790 9.308 3.613 5.695 15 0

Kenya Uganda 381300 0 0 0 0 0

Kenya Uganda 390110 0 0 0 0 0

Kenya Uganda 390760 0 0 0 0 0

Kenya Uganda 391739 2.423 0.812 1.611 25 0

Kenya Uganda 392220 1.158 0.398 0.76 25 0

Kenya Uganda 392310 37.859 20.167 17.692 25 0

Kenya Uganda 392390 0.179 0.066 0.113 13.75 0

Kenya Uganda 401162 2.238 0.509 1.729 25 0

Kenya Uganda 410229 8.497 8.497 0 5 0

Kenya Uganda 410310 11.703 6.361 5.342 5 0

Kenya Uganda 410510 1.599 0.378 1.222 15 0

Kenya Uganda 410621 6.544 6.544 0 15 0

Kenya Uganda 410691 22.218 22.218 0 15 0

Kenya Uganda 410692 2.615 2.615 0 15 0

Kenya Uganda 410799 17.983 17.983 0 15 0

Kenya Uganda 420219 0.478 0.197 0.281 25 0

Kenya Uganda 440710 3.046 1.713 1.333 5 0

Kenya Uganda 440724 5.16 3.206 1.955 5 0

Kenya Uganda 440729 4.092 3.691 0.401 5 0

Kenya Uganda 441029 1.057 0.769 0.288 25 0

Kenya Uganda 441300 0.819 0.518 0.3 25 0

Kenya Uganda 441520 1.458 0.881 0.577 35 0

Kenya Uganda 442190 0.779 0.186 0.593 29 0

87

Kenya Uganda 470710 0.232 0.117 0.115 5 0

Kenya Uganda 470790 0.379 0.148 0.231 5 0

Kenya Uganda 481013 1.519 0.615 0.905 15 0

Kenya Uganda 482390 21.558 10.298 11.261 35 0

Kenya Uganda 490210 0 0 0 0 0

Kenya Uganda 490290 0 0 0 0 0

Kenya Uganda 491000 2.341 1.007 1.334 35 0

Kenya Uganda 520100 0 0 0 0 0

Kenya Uganda 520512 4.593 4.556 0.036 20 0

Kenya Uganda 520521 4.293 4.293 0 20 0

Kenya Uganda 520522 4.288 4.288 0 20 0

Kenya Uganda 520524 1.992 1.992 0 20 0

Kenya Uganda 560811 14.38 4.453 9.927 25 0

Kenya Uganda 560819 1.218 0.627 0.591 13.33 0

Kenya Uganda 611030 3.015 1.88 1.136 35 0

Kenya Uganda 630533 32.003 19.897 12.106 30 0

Kenya Uganda 630900 2.123 0.85 1.273 35 0

Kenya Uganda 640199 5.074 1.519 3.555 30 0

Kenya Uganda 681011 0.299 0.118 0.181 25 0

Kenya Uganda 681110 20.575 6.361 14.214 25 0

Kenya Uganda 701090 0.17 0.045 0.125 15 0

Kenya Uganda 721391 4.738 1.911 2.826 5 0


62

1232.489 70.674 15 0

Kenya Uganda 722211 0 0 0 0 0

Kenya Uganda 730110 3.774 2.454 1.32 15 0

Kenya Uganda 730449 0.13 0.044 0.086 5 0

Kenya Uganda 730799 0.583 0.276 0.307 15 0

Kenya Uganda 730890 10.354 4.49 5.864 35 0

Kenya Uganda 730900 1.037 0.678 0.358 35 0

Kenya Uganda 731010 1.457 1.021 0.436 35 0

Kenya Uganda 731029 0.588 0.234 0.354 35 0

Kenya Uganda 732690 0.52 0.18 0.34 35 0

Kenya Uganda 740400 5.377 3.393 1.984 5 0

Kenya Uganda 761699 5.116 1.384 3.733 15 0

Kenya Uganda 830140 0.27 0.106 0.164 20 0

Kenya Uganda 840820 0.844 0.548 0.296 15 0

Kenya Uganda 840991 0.614 0.362 0.251 15 0

Kenya Uganda 841319 2.376 1.297 1.08 15 0

Kenya Uganda 841381 0.115 0.042 0.073 10 0

Kenya Uganda 841391 0.174 0.059 0.115 15 0

Kenya Uganda 841960 0 0 0 0 0

Kenya Uganda 842230 0 0 0 0 0

Kenya Uganda 842240 0 0 0 0 0

Kenya Uganda 843810 0 0 0 0 0

Kenya Uganda 844319 0.725 0.258 0.467 7.5 0

Kenya Uganda 844330 0 0 0 0 0

Kenya Uganda 844351 5.239 2.215 3.024 7.5 0

Kenya Uganda 844390 0.98 0.445 0.535 5 0

88

Kenya Uganda 846190 0 0 0 0 0

Kenya Uganda 846594 0 0 0 0 0

Kenya Uganda 847110 0 0 0 0 0

Kenya Uganda 847130 0 0 0 0 0

Kenya Uganda 847149 0 0 0 0 0

Kenya Uganda 847150 0 0 0 0 0

Kenya Uganda 847160 0 0 0 0 0

Kenya Uganda 847170 0 0 0 0 0

Kenya Uganda 847180 0 0 0 0 0

Kenya Uganda 847330 0.336 0.1 0.236 15 0

Kenya Uganda 847420 0 0 0 0 0

Kenya Uganda 847759 0 0 0 0 0

Kenya Uganda 847981 0 0 0 0 0

Kenya Uganda 847982 0 0 0 0 0

Kenya Uganda 848079 0 0 0 0 0

Kenya Uganda 848299 0.149 0.035 0.114 15 0

Kenya Uganda 850433 1.38 0.597 0.783 5 0

Kenya Uganda 850440 0.536 0.218 0.318 5 0

Kenya Uganda 850680 0.917 0.278 0.639 35 0

Kenya Uganda 850780 0.334 0.09 0.244 25 0

Kenya Uganda 851719 5.713 2.334 3.38 15 0

Kenya Uganda 851721 0.833 0.323 0.509 15 0

Kenya Uganda 851730 2.016 0.872 1.144 15 0

Kenya Uganda 851750 3.195 1.233 1.961 15 0

Kenya Uganda 851780 21.021 9.543 11.479 15 0

Kenya Uganda 851790 6.158 0.828 5.33 15 0

Kenya Uganda 851850 1.529 0.671 0.859 25 0

Kenya Uganda 852110 0.421 0.198 0.223 25 0

Kenya Uganda 852190 0.38 0.162 0.218 25 0

Kenya Uganda 852491 0.795 0.233 0.561 10 0

Kenya Uganda 852499 2.103 0.607 1.496 7.5 0

Kenya Uganda 852719 2.852 1.231 1.622 15 0

Kenya Uganda 852812 9.838 4.26 5.578 22.5 0

Kenya Uganda 853400 5.477 1.812 3.665 15 0

Kenya Uganda 853630 0.486 0.193 0.293 5 0

Kenya Uganda 853810 19.778 7.466 12.312 15 0

Kenya Uganda 853890 3.288 1.148 2.14 15 0

Kenya Uganda 854381 3.897 3.606 0.291 15 0

Kenya Uganda 854411 0.431 0.149 0.282 22.5 0

Kenya Uganda 854441 0.882 0.231 0.651 15 0

Kenya Uganda 854449 2.682 0.801 1.881 31.67 0

Kenya Uganda 860791 9.765 5.141 4.624 5 0

Kenya Uganda 870190 0 0 0 0 0

Kenya Uganda 870210 118.53 59.152 59.378 28 0

Kenya Uganda 870321 0.488 0.124 0.364 17.5 0

Kenya Uganda 870322 8.136 2.884 5.252 17.5 0

Kenya Uganda 870323 10.985 4.306 6.679 17.5 0

Kenya Uganda 870332 6.868 4.92 1.948 17.5 0

Kenya Uganda 870333 1.149 0.483 0.666 17.5 0

89

Kenya Uganda 870421 10.249 3.926 6.323 23.33 0

Kenya Uganda 870422 24.636 10.482 14.154 17.5 0

Kenya Uganda 870423 5.176 1.982 3.194 12.5 0

Kenya Uganda 870790 0.962 0.281 0.681 25 0

Kenya Uganda 870810 0.485 0.182 0.304 15 0

Kenya Uganda 871120 0.122 0.042 0.08 7.5 0

Kenya Uganda 871493 0.425 0.164 0.261 15 0

Kenya Uganda 871640 0.315 0.119 0.196 12.5 0

Kenya Uganda 880330 0.341 0.133 0.208 5 0

Kenya Uganda 880390 3.355 0.897 2.458 5 0

Kenya Uganda 900911 0.759 0.349 0.409 15 0

Kenya Uganda 900930 1.147 0.47 0.677 15 0

Kenya Uganda 900999 0.807 0.298 0.509 15 0

Kenya Uganda 902810 0.416 0.217 0.198 5 0

Kenya Uganda 902920 0.556 0.288 0.268 10 0

Kenya Uganda 940330 2.086 0.615 1.471 35 0

Kenya Uganda 940340 1.849 1.332 0.517 35 0

Kenya Uganda 940390 1.487 0.696 0.791 35 0

Kenya Uganda 940540 0.252 0.101 0.151 15 0

Kenya Uganda Total 8570.8

95

6619.334 1951.562 15.72 0

Kenya Tanzania 10392 0.436 0.436 0 5 0

Kenya Tanzania 30410 0.905 0.905 0 15 0

Kenya Tanzania 30490 9.646 4.731 4.915 15 0

Kenya Tanzania 30510 1.452 1.452 0 15 0

Kenya Tanzania 30613 16.836 16.836 0 15 0

Kenya Tanzania 40900 4.218 2.232 1.985 25 0

Kenya Tanzania 51191 22.999 22.941 0.057 3.33 0

Kenya Tanzania 60390 2.15 1.331 0.818 15 0

Kenya Tanzania 70190 0.414 0.414 0 35 0

Kenya Tanzania 70200 1.473 0.382 1.091 35 0

Kenya Tanzania 70521 2.236 2.167 0.069 35 0

Kenya Tanzania 70810 2.186 1.01 1.176 35 0

Kenya Tanzania 70820 5.675 4.636 1.039 35 0

Kenya Tanzania 70890 0.267 0.13 0.137 35 0

Kenya Tanzania 71022 0.973 0.323 0.65 35 0

Kenya Tanzania 71310 30.314 12.506 17.808 35 0

Kenya Tanzania 71320 2.915 2.725 0.191 35 0

Kenya Tanzania 71333 7.952 3.067 4.885 35 0

Kenya Tanzania 71340 13.85 4.202 9.648 35 0

Kenya Tanzania 80131 354.33

4

354.334 0 15 0

Kenya Tanzania 80290 0.33 0.106 0.224 15 0

Kenya Tanzania 80510 48.577 22.38 26.197 35 0

Kenya Tanzania 90111 5.196 4.798 0.399 15 0

Kenya Tanzania 90122 1.966 1.492 0.475 15 0

Kenya Tanzania 90190 3.375 1.919 1.456 15 0

Kenya Tanzania 100510 0.473 0.178 0.296 25 0

Kenya Tanzania 100590 1315.7 563.927 751.84 25 0

90

67

Kenya Tanzania 100700 2.334 2.075 0.259 15 0

Kenya Tanzania 100810 37.391 37.391 0 15 0

Kenya Tanzania 100820 1.398 0.01 1.388 15 0

Kenya Tanzania 110319 25.061 24.276 0.784 15 0

Kenya Tanzania 110430 0.208 0.109 0.099 15 0

Kenya Tanzania 120210 2.379 1.275 1.104 5 0

Kenya Tanzania 120220 5.3 3.57 1.73 5 0

Kenya Tanzania 120710 23.342 22.876 0.466 15 0

Kenya Tanzania 120720 0 0 0 0 0

Kenya Tanzania 120991 6.851 2.757 4.094 15 0

Kenya Tanzania 121190 58.79 53.253 5.537 15 0

Kenya Tanzania 151229 0.303 0.303 0 30 0

Kenya Tanzania 170490 8.803 1.894 6.909 35 0

Kenya Tanzania 210111 60.155 14.766 45.389 15 0

Kenya Tanzania 210130 8.89 7.692 1.198 20 0

Kenya Tanzania 210210 5.519 2.219 3.3 20 0

Kenya Tanzania 210690 1.901 0.71 1.191 18.75 0


3

78.688 107.475 30 0

Kenya Tanzania 220410 0.352 0.101 0.251 30 0


8

194.221 3.567 27.5 0

Kenya Tanzania 220890 29.611 9.029 20.582 30 0



Kenya Tanzania 230210 3.687 2.173 1.514 15 0

Kenya Tanzania 230220 1.002 1.002 0 15 0

Kenya Tanzania 230230 14.646 14.646 0 15 0

Kenya Tanzania 230240 1.149 0.616 0.534 15 0

Kenya Tanzania 230400 6.225 2.093 4.132 15 0


9

383.269 0 15 0

Kenya Tanzania 230630 9.974 9.974 0 15 0

Kenya Tanzania 230650 1.117 1.117 0 15 0

Kenya Tanzania 240120 29.916 22.976 6.941 20 0



Kenya Tanzania 252230 3.85 3.85 0 15 0

Kenya Tanzania 271019 1.465 0.964 0.5 5.53 0

Kenya Tanzania 271210 4.466 1.841 2.624 30 0


Kenya Tanzania 283010 2.243 0.89 1.353 15 0

Kenya Tanzania 285100 0.767 0.337 0.429 15 0






91


Kenya Tanzania 320120 2.848 0.956 1.892 15 0

Kenya Tanzania 320290 1.312 0.529 0.783 15 0


Kenya Tanzania 320990 4.364 1.85 2.515 25 0


Kenya Tanzania 330190 1.519 0.533 0.986 7.5 0

Kenya Tanzania 330300 2.495 0.929 1.565 35 0

Kenya Tanzania 330420 0.785 0.326 0.46 35 0

Kenya Tanzania 330499 0.45 0.064 0.386 35 0

Kenya Tanzania 330520 1.265 0.494 0.77 35 0


9

60.331 68.557 25 0

Kenya Tanzania 330790 0.627 0.269 0.357 28 0


1

230.467 213.344 30 0

Kenya Tanzania 340220 26.201 9.424 16.777 25 0

Kenya Tanzania 340290 124.74 57.302 67.439 25 0


Kenya Tanzania 360410 2.096 0.826 1.271 25 0

Kenya Tanzania 370790 1.517 0.588 0.93 15 0



Kenya Tanzania 382490 1.691 0.669 1.023 7.5 0





Kenya Tanzania 391890 1.545 0.677 0.868 25 0

Kenya Tanzania 392190 1.052 0.419 0.633 15 0

Kenya Tanzania 392310 14.964 7.891 7.072 25 0

Kenya Tanzania 392321 27.73 11.258 16.472 25 0

Kenya Tanzania 392329 7.83 1.102 6.729 25 0

Kenya Tanzania 392330 1.188 0.534 0.654 25 0

Kenya Tanzania 392690 1.805 0.864 0.942 18.33 0





Kenya Tanzania 401110 8.319 2.191 6.128 35 0

Kenya Tanzania 401120 0.303 0.108 0.195 35 0

Kenya Tanzania 401212 0.28 0.035 0.245 35 0

Kenya Tanzania 410120 4.723 4.723 0 15 0

Kenya Tanzania 410221 0.044 0.044 0 5 0

Kenya Tanzania 420299 0.251 0.066 0.185 25 0





92

Kenya Tanzania 440710 13.178 7.475 5.703 5 0

Kenya Tanzania 440729 20.742 18.793 1.949 5 0

Kenya Tanzania 440799 40.052 39.569 0.484 5 0

Kenya Tanzania 440920 4.447 2.862 1.586 25 0

Kenya Tanzania 441520 59.885 40.737 19.148 35 0


Kenya Tanzania 480810 20.537 20.537 0 35 0

Kenya Tanzania 481690 8.99 3.418 5.572 35 0

Kenya Tanzania 481960 1.159 0.337 0.822 35 0




Kenya Tanzania 520210 2.878 1.256 1.622 20 0

Kenya Tanzania 520299 8.492 7.927 0.565 15 0

Kenya Tanzania 520511 10.045 5.223 4.822 20 0


6

523.106 0 20 0

Kenya Tanzania 520531 12.751 12.751 0 20 0

Kenya Tanzania 520811 2.958 1.43 1.529 25 0

Kenya Tanzania 520812 5.36 4.288 1.072 25 0

Kenya Tanzania 520842 13.856 10.683 3.173 25 0

Kenya Tanzania 520851 46.03 45.468 0.562 25 0

Kenya Tanzania 520912 1.199 0.57 0.629 25 0

Kenya Tanzania 521021 25.37 16.877 8.493 25 0


6

227.059 10.057 25 0

Kenya Tanzania 521051 12.853 12.668 0.185 25 0

Kenya Tanzania 521151 1.436 1.436 0 25 0



7

211.977 0.02 20 0

Kenya Tanzania 540410 1.815 0.817 0.998 20 0

Kenya Tanzania 540783 5.59 1.864 3.726 25 0

Kenya Tanzania 540792 85.623 85.397 0.226 25 0

Kenya Tanzania 540793 8.269 4.258 4.011 25 0

Kenya Tanzania 550922 38.376 35.481 2.895 20 0

Kenya Tanzania 551120 2.643 2.332 0.311 20 0

Kenya Tanzania 551339 45.471 44.432 1.039 25 0

Kenya Tanzania 551612 95.873 95.873 0 25 0

Kenya Tanzania 551621 15.835 15.835 0 25 0

Kenya Tanzania 560721 10.944 10.939 0.005 25 0

Kenya Tanzania 560811 17.596 5.503 12.094 25 0


5

228.656 184.199 13.33 0

Kenya Tanzania 580410 0.051 0.042 0.009 25 0

Kenya Tanzania 590700 1.461 1.146 0.315 25 0

Kenya Tanzania 600531 336.3 324.645 11.655 25 0


5

599.635 0 25 0

93

Kenya Tanzania 600622 78.179 66.396 11.783 25 0

Kenya Tanzania 600631 3.336 1.421 1.915 25 0

Kenya Tanzania 600632 8.633 8.633 0 25 0

Kenya Tanzania 600634 20.685 18.803 1.882 25 0

Kenya Tanzania 610510 6.369 2.026 4.342 35 0

Kenya Tanzania 610910 12.874 4.123 8.751 35 0

Kenya Tanzania 621320 0.557 0.216 0.341 35 0

Kenya Tanzania 630190 69.024 19.821 49.204 25 0


8

122.041 40.777 25 0

Kenya Tanzania 630319 0.464 0.16 0.304 25 0


1

131.734 61.538 30 0

Kenya Tanzania 630611 0.239 0.239 0 25 0

Kenya Tanzania 630612 18.188 7.262 10.926 25 0

Kenya Tanzania 630619 53.805 39.015 14.791 25 0

Kenya Tanzania 630621 4.641 2.172 2.469 25 0


3

40.558 60.515 35 0

Kenya Tanzania 660199 4.161 1.813 2.348 25 0

Kenya Tanzania 670420 2.817 2.432 0.385 25 0

Kenya Tanzania 691190 7.122 4.066 3.056 25 0

Kenya Tanzania 701010 1.463 0.44 1.023 7.5 0


2

38.29 99.731 15 0

Kenya Tanzania 701329 1.357 0.572 0.785 25 0

Kenya Tanzania 711790 1.087 0.663 0.425 25 0






Kenya Tanzania 721310 3.134 1.582 1.552 20 0

Kenya Tanzania 721320 43.132 42.902 0.23 20 0


8

465.983 27.376 15 0


8

88.939 37.578 15 0

Kenya Tanzania 721590 19.119 11.56 7.559 15 0


Kenya Tanzania 721669 2.155 1.611 0.544 35 0

Kenya Tanzania 722830 1.498 0.378 1.121 5 0

Kenya Tanzania 722860 1.124 0.451 0.673 15 0

Kenya Tanzania 732090 0.688 0.288 0.4 35 0

Kenya Tanzania 732399 3.941 1.574 2.367 35 0

Kenya Tanzania 740400 0.084 0.052 0.032 5 0

Kenya Tanzania 740811 23.065 9.956 13.109 5 0

Kenya Tanzania 740819 60.788 25.625 35.163 15 0


94


Kenya Tanzania 820130 1.81 0.712 1.098 15 0

Kenya Tanzania 820750 1.502 0.503 0.999 15 0

Kenya Tanzania 830110 0.3 0.121 0.179 20 0

Kenya Tanzania 830910 50.117 41.331 8.787 25 0

Kenya Tanzania 840890 1.076 0.402 0.674 15 0

Kenya Tanzania 840991 0.354 0.209 0.145 15 0

Kenya Tanzania 841381 0.539 0.198 0.341 10 0

Kenya Tanzania 841510 3.659 1.06 2.599 25 0

Kenya Tanzania 841582 4.89 2.008 2.882 25 0

Kenya Tanzania 841850 21.499 10.967 10.532 15 0

Kenya Tanzania 841911 4.2 1.907 2.293 10 0





Kenya Tanzania 842290 0.25 0.101 0.148 5 0


Kenya Tanzania 842489 1.492 0.623 0.869 15 0

Kenya Tanzania 842531 52.44 50.705 1.734 15 0


Kenya Tanzania 843210 34.705 19.371 15.334 7.5 0

















Kenya Tanzania 847030 1.619 1.229 0.39 15 0







Kenya Tanzania 847330 0.337 0.1 0.237 15 0



Kenya Tanzania 848310 0.741 0.343 0.399 15 0

95

Kenya Tanzania 848410 0.344 0.127 0.217 25 0

Kenya Tanzania 850110 0.094 0.045 0.049 5 0




Kenya Tanzania 850421 31.504 12.221 19.283 5 0

Kenya Tanzania 850422 4.673 2.415 2.258 5 0

Kenya Tanzania 850432 0.081 0.031 0.05 5 0

Kenya Tanzania 850433 33.198 14.409 18.789 5 0

Kenya Tanzania 850434 0.816 0.211 0.605 5 0

Kenya Tanzania 851150 0.328 0.132 0.195 15 0

Kenya Tanzania 851750 1.076 0.415 0.661 15 0

Kenya Tanzania 851790 1.102 0.148 0.954 15 0

Kenya Tanzania 852432 1.331 0.404 0.927 15 0

Kenya Tanzania 852812 6.883 2.979 3.904 22.5 0


Kenya Tanzania 853210 0.813 0.288 0.524 5 0

Kenya Tanzania 853229 4.937 1.672 3.265 15 0

Kenya Tanzania 853400 0.348 0.114 0.234 15 0

Kenya Tanzania 853630 1.294 0.514 0.78 5 0

Kenya Tanzania 853650 0.128 0.049 0.079 5 0

Kenya Tanzania 854420 56.938 18.145 38.793 30 0

Kenya Tanzania 854459 1.114 0.356 0.758 31.67 0

Kenya Tanzania 854720 0.188 0.054 0.134 5 0

Kenya Tanzania 870120 3.708 1.404 2.304 12.5 0


Kenya Tanzania 870210 2.927 1.459 1.468 28 0

Kenya Tanzania 870322 0.648 0.23 0.418 17.5 0

Kenya Tanzania 870332 1.924 1.378 0.546 17.5 0

Kenya Tanzania 870333 59.193 24.899 34.293 17.5 0


4

78.301 105.323 17.5 0

Kenya Tanzania 870423 3.448 1.32 2.128 12.5 0

Kenya Tanzania 870432 1.303 0.127 1.176 17.5 0

Kenya Tanzania 870710 6.097 1.926 4.171 35 0

Kenya Tanzania 870810 2.363 0.886 1.477 15 0

Kenya Tanzania 870831 16.329 0.597 15.732 15 0

Kenya Tanzania 870880 1.664 0.584 1.08 25 0


Kenya Tanzania 880310 0.079 0.033 0.046 5 0

Kenya Tanzania 900830 0.56 0.163 0.397 25 0

Kenya Tanzania 900911 0.324 0.149 0.175 15 0

Kenya Tanzania 900912 0.458 0.195 0.263 15 0

Kenya Tanzania 900930 1.435 0.589 0.846 15 0

Kenya Tanzania 900999 3.264 1.207 2.057 15 0

Kenya Tanzania 902780 0.107 0.045 0.061 5 0

Kenya Tanzania 940360 0.609 0.023 0.586 35 0

Kenya Tanzania 940600 0.705 0.184 0.521 12.5 0

Kenya Tanzania 960321 12.764 5.211 7.553 25 0

96

Kenya Tanzania 960810 2.615 0.795 1.82 35 0

Kenya Tanzania 961700 8.096 3.272 4.823 21.67 0

Kenya Tanzania Total 9072.4

07

6478.687 2593.72 15.26 0

97

Appendix IV

Simulation Results for Uganda (Level.6 SITC Rev-3 UNCTAD)

Reporte

rName

PartnerNa

me

Product

Code

TradeTo

talEffect

in 1000

USD

TradeCreatio

nEffect in

1000 USD

TradeDiver

sionEffect

in 1000

USD

OldSimp

leDutyR

ate

NewSimple

DutyRate

Uganda Kenya 10110 0.203 0.203 0 4 0

Uganda Kenya 10190 0.029 0.029 0 4 0

Uganda Kenya 10210 2.213 2.213 0 4 0

Uganda Kenya 10290 0.595 0.582 0.013 4 0

Uganda Kenya 10420 4.33 4.256 0.074 4 0

Uganda Kenya 10511 15.164 9.121 6.043 4 0

Uganda Kenya 10512 0.058 0.058 0 4 0

Uganda Kenya 10519 0.138 0.071 0.066 4 0

Uganda Kenya 30349 11.258 10.925 0.332 6 0

Uganda Kenya 40110 0.649 0.315 0.334 6 0

Uganda Kenya 40130 0.111 0.035 0.075 6 0

Uganda Kenya 40210 1.56 0.561 1 6 0

Uganda Kenya 40221 0.16 0.074 0.087 6 0

Uganda Kenya 40229 5.638 3.707 1.931 6 0

Uganda Kenya 40291 4.598 2.205 2.392 6 0

Uganda Kenya 40299 5.543 2.051 3.493 6 0

Uganda Kenya 40310 41.558 39.992 1.567 6 0

Uganda Kenya 40390 1.779 0.674 1.105 6 0

Uganda Kenya 40510 0.957 0.396 0.561 6 0

Uganda Kenya 40690 1.945 1.035 0.911 6 0

Uganda Kenya 51191 4.723 4.723 0 4 0

Uganda Kenya 60120 0 0 0 0 0

Uganda Kenya 60210 0 0 0 0 0

Uganda Kenya 60220 0 0 0 0 0

Uganda Kenya 60240 0 0 0 0 0

Uganda Kenya 60290 0 0 0 0 0

Uganda Kenya 60310 1.493 1.493 0 4 0

Uganda Kenya 70200 0.757 0.757 0 6 0

Uganda Kenya 70310 12.223 12.223 0 6 0

Uganda Kenya 70320 0.453 0.215 0.238 6 0

Uganda Kenya 70610 0.299 0.299 0 6 0

Uganda Kenya 70810 5.662 4.436 1.226 6 0

98

Uganda Kenya 70960 0.119 0.119 0 6 0

Uganda Kenya 70990 0.061 0.061 0 6 0

Uganda Kenya 71010 0.226 0.192 0.034 6 0

Uganda Kenya 71220 0.273 0.271 0.001 6 0

Uganda Kenya 71310 24.368 10.103 14.265 6 0

Uganda Kenya 71331 5.308 0.172 5.135 6 0

Uganda Kenya 71340 1.729 0.447 1.282 6 0

Uganda Kenya 71420 0.06 0.06 0 6 0

Uganda Kenya 71490 0.06 0.059 0.001 6 0

Uganda Kenya 80111 0.661 0.57 0.091 6 0

Uganda Kenya 80119 0.186 0.108 0.078 6 0

Uganda Kenya 80131 22.681 22.681 0 6 0

Uganda Kenya 80132 23.372 23.242 0.13 6 0

Uganda Kenya 80290 1.533 0.944 0.589 6 0

Uganda Kenya 80410 0.427 0.198 0.229 6 0

Uganda Kenya 80450 0.4 0.235 0.166 6 0

Uganda Kenya 80510 0.703 0.404 0.298 6 0

Uganda Kenya 80520 0.618 0.618 0 6 0

Uganda Kenya 80590 0.788 0.728 0.06 6 0

Uganda Kenya 80610 0.417 0.363 0.054 6 0

Uganda Kenya 80711 0.171 0.086 0.085 6 0

Uganda Kenya 80719 0.108 0.038 0.07 6 0

Uganda Kenya 80810 9.317 3.94 5.377 6 0

Uganda Kenya 80820 4.661 2.241 2.42 6 0

Uganda Kenya 81090 0.435 0.272 0.162 6 0

Uganda Kenya 81110 0.076 0.076 0 6 0

Uganda Kenya 81120 0.023 0.023 0 6 0

Uganda Kenya 81190 0.194 0.16 0.034 6 0

Uganda Kenya 81340 0.166 0.074 0.092 6 0

Uganda Kenya 90121 1.004 0.818 0.185 4 0

Uganda Kenya 90122 0.181 0.059 0.122 4 0

Uganda Kenya 90210 0.227 0.178 0.049 4 0

Uganda Kenya 90220 0.55 0.523 0.027 4 0

Uganda Kenya 90230 0.575 0.231 0.344 4 0

Uganda Kenya 90240 0.493 0.314 0.179 4 0

Uganda Kenya 90420 0.051 0.033 0.018 4 0

Uganda Kenya 90500 0.181 0.171 0.01 4 0

Uganda Kenya 91020 0.287 0.287 0 4 0

Uganda Kenya 91030 0.071 0.071 0 4 0

Uganda Kenya 91050 6.564 6.564 0 4 0

Uganda Kenya 91091 13.927 13.85 0.077 4 0

Uganda Kenya 91099 4.997 2.983 2.014 4 0

Uganda Kenya 100110 0 0 0 0 0

Uganda Kenya 100190 0 0 0 0 0

Uganda Kenya 100300 0 0 0 0 0

Uganda Kenya 100510 1.67 0.667 1.002 4 0

Uganda Kenya 100590 9.783 5.043 4.74 4 0

Uganda Kenya 100630 2.696 0.712 1.983 6 0

Uganda Kenya 100640 2.018 0.885 1.133 6 0

99

Uganda Kenya 100700 12.565 3.371 9.194 6 0

Uganda Kenya 100810 1.161 1.161 0 4 0

Uganda Kenya 100890 0.69 0.668 0.022 4 0

Uganda Kenya 110100 0.141 0.061 0.08 6 0

Uganda Kenya 110220 31.878 17.499 14.379 6 0

Uganda Kenya 110290 0.059 0.018 0.041 6 0

Uganda Kenya 110319 27.307 26.548 0.759 6 0

Uganda Kenya 110412 0.111 0.016 0.095 6 0

Uganda Kenya 110419 0.57 0.485 0.085 6 0

Uganda Kenya 110423 0.069 0.028 0.041 6 0

Uganda Kenya 110710 0 0 0 0 0

Uganda Kenya 110720 0 0 0 0 0

Uganda Kenya 110812 9.897 5.819 4.078 4 0

Uganda Kenya 110819 0.32 0.106 0.215 4 0

Uganda Kenya 120220 0.02 0.02 0 4 0

Uganda Kenya 120810 8.482 6.017 2.465 4 0

Uganda Kenya 120890 0.022 0.014 0.007 4 0

Uganda Kenya 120991 28.845 20.286 8.559 4 0

Uganda Kenya 121190 0.626 0.626 0 1 0

Uganda Kenya 121410 0.026 0.026 0 4 0

Uganda Kenya 130190 0 0 0 0 0

Uganda Kenya 150500 0 0 0 0 0

Uganda Kenya 150710 0.177 0.055 0.122 4 0

Uganda Kenya 151110 0 0 0 0 0

Uganda Kenya 151190 103.084 40.64 62.444 5.2 0

Uganda Kenya 151219 3.765 1.708 2.057 6 0

Uganda Kenya 151319 0.3 0.27 0.031 6 0

Uganda Kenya 151529 0.1 0.1 0 6 0

Uganda Kenya 151590 1.495 0.684 0.811 6 0

Uganda Kenya 151610 0.766 0.342 0.424 6 0

Uganda Kenya 151620 42.327 18.188 24.14 6 0

Uganda Kenya 151710 107.977 106.534 1.442 6 0

Uganda Kenya 151790 16.55 14.574 1.976 6 0

Uganda Kenya 151800 3.862 1.65 2.212 6 0

Uganda Kenya 152000 2.714 1.391 1.323 4 0

Uganda Kenya 160100 37.566 37.145 0.421 6 0

Uganda Kenya 160241 43.118 41.841 1.278 6 0

Uganda Kenya 160242 0.862 0.727 0.135 6 0

Uganda Kenya 160411 0.801 0.708 0.093 6 0

Uganda Kenya 160414 0.468 0.218 0.25 6 0

Uganda Kenya 170111 2.668 1.017 1.65 6 0

Uganda Kenya 170191 3.489 3.386 0.103 6 0

Uganda Kenya 170199 0.745 0.298 0.447 6 0

Uganda Kenya 170211 0.678 0.48 0.198 4 0

Uganda Kenya 170219 0.076 0.045 0.031 4 0

Uganda Kenya 170230 41.616 37.881 3.735 4 0

Uganda Kenya 170240 4.378 2.785 1.593 4 0

Uganda Kenya 170290 0.677 0.402 0.275 4 0

Uganda Kenya 170310 2.635 2.59 0.044 6 0

100

Uganda Kenya 170390 2.516 2.457 0.059 6 0

Uganda Kenya 170410 66.642 63.222 3.42 6 0

Uganda Kenya 170490 39.476 19.427 20.049 6 0

Uganda Kenya 180310 0.075 0.075 0 6 0

Uganda Kenya 180500 1.476 1.436 0.04 6 0

Uganda Kenya 180610 8.107 5.45 2.657 6 0

Uganda Kenya 180620 24.702 23.867 0.835 6 0

Uganda Kenya 180631 2.5 0.871 1.629 6 0

Uganda Kenya 180690 60.737 41.406 19.331 6 0

Uganda Kenya 190110 13.761 11.955 1.806 6 0

Uganda Kenya 190190 2.619 2.496 0.123 6 0

Uganda Kenya 190219 0.17 0.048 0.122 6 0

Uganda Kenya 190220 0.378 0.17 0.208 6 0

Uganda Kenya 190410 71.828 65.037 6.791 6 0

Uganda Kenya 190420 16.999 15.196 1.803 6 0

Uganda Kenya 190490 1.493 1.094 0.399 6 0

Uganda Kenya 190510 2.465 2.138 0.327 6 0

Uganda Kenya 190531 33.392 16.732 16.66 6 0

Uganda Kenya 190532 0.416 0.339 0.077 6 0

Uganda Kenya 190540 0.13 0.099 0.031 6 0

Uganda Kenya 190590 0.339 0.13 0.21 6 0

Uganda Kenya 200290 1.463 0.51 0.954 6 0

Uganda Kenya 200410 5.442 4.282 1.159 6 0

Uganda Kenya 200520 2.134 0.915 1.219 6 0

Uganda Kenya 200559 0.179 0.07 0.109 6 0

Uganda Kenya 200710 1.67 1.223 0.447 6 0

Uganda Kenya 200791 0.428 0.387 0.041 6 0

Uganda Kenya 200799 8.112 5.328 2.784 6 0

Uganda Kenya 200892 0.07 0.062 0.008 6 0

Uganda Kenya 200919 0.706 0.436 0.27 6 0

Uganda Kenya 200921 0.034 0.034 0 6 0

Uganda Kenya 200980 1.957 1.034 0.922 6 0

Uganda Kenya 200990 10.049 1.276 8.774 6 0

Uganda Kenya 210111 5.878 5.313 0.566 4 0

Uganda Kenya 210120 0.106 0.068 0.038 4 0

Uganda Kenya 210210 16.359 7.28 9.079 4 0

Uganda Kenya 210220 1.253 1.12 0.132 4 0

Uganda Kenya 210230 25.837 24.842 0.995 4 0

Uganda Kenya 210320 1.093 0.211 0.881 6 0

Uganda Kenya 210330 0.209 0.09 0.118 6 0

Uganda Kenya 210390 2.565 1.984 0.581 6 0

Uganda Kenya 210410 1.518 0.889 0.628 6 0

Uganda Kenya 210420 0.727 0.251 0.476 6 0

Uganda Kenya 210500 0.689 0.296 0.393 6 0

Uganda Kenya 210610 0 0 0 0 0

Uganda Kenya 210690 45.553 21.486 24.067 4 0

Uganda Kenya 220110 1.512 1.062 0.45 6 0

Uganda Kenya 220210 14.51 7.645 6.865 6 0

Uganda Kenya 220290 26.534 17.704 8.83 6 0

101

Uganda Kenya 220300 3.816 0.872 2.943 6 0

Uganda Kenya 220410 3.14 0.923 2.217 6 0

Uganda Kenya 220421 1.988 0.702 1.286 6 0

Uganda Kenya 220429 3.424 1.922 1.503 6 0

Uganda Kenya 220510 1.936 1.055 0.881 6 0

Uganda Kenya 220710 135.931 127.908 8.023 6 0

Uganda Kenya 220720 0.049 0.031 0.018 6 0

Uganda Kenya 220820 7.97 4.213 3.757 6 0

Uganda Kenya 220830 12.746 8.038 4.708 6 0

Uganda Kenya 220840 0.086 0.06 0.025 6 0

Uganda Kenya 220850 2.802 2.678 0.124 6 0

Uganda Kenya 220860 2.908 2.746 0.162 6 0

Uganda Kenya 220870 0.208 0.071 0.137 6 0

Uganda Kenya 220890 2.582 0.953 1.63 6 0

Uganda Kenya 220900 0.342 0.163 0.179 6 0

Uganda Kenya 230110 4.391 4.379 0.012 6 0

Uganda Kenya 230910 0.153 0.044 0.109 4 0

Uganda Kenya 230990 5.195 3.158 2.037 4 0

Uganda Kenya 240210 4.159 4.081 0.077 6 0

Uganda Kenya 240310 2.454 2.368 0.086 6 0

Uganda Kenya 250100 258.071 256.138 1.933 4 0

Uganda Kenya 250490 0.111 0.111 0 4 0

Uganda Kenya 250700 0.585 0.585 0 4 0

Uganda Kenya 250810 0 0 0 0 0

Uganda Kenya 250820 0.449 0.172 0.277 4 0

Uganda Kenya 250830 0.105 0.036 0.069 4 0

Uganda Kenya 250900 3.068 3.068 0 4 0

Uganda Kenya 251020 7.774 7.774 0 4 0

Uganda Kenya 251200 1.385 0.586 0.799 4 0

Uganda Kenya 251400 0.205 0.205 0 4 0

Uganda Kenya 251612 0.188 0.072 0.115 6 0

Uganda Kenya 251690 0.057 0.049 0.009 6 0

Uganda Kenya 251710 26.211 26.181 0.03 6 0

Uganda Kenya 251720 3.292 3.292 0 4 0

Uganda Kenya 251730 0.01 0.01 0 4 0

Uganda Kenya 251741 0.318 0.316 0.001 6 0

Uganda Kenya 251749 4.575 4 0.575 6 0

Uganda Kenya 252010 0 0 0 0 0

Uganda Kenya 252020 0 0 0 0 0

Uganda Kenya 252210 0.37 0.37 0 4 0

Uganda Kenya 252230 185.409 185.402 0.007 4 0

Uganda Kenya 252310 262.813 127.679 135.134 4 0

Uganda Kenya 252321 2.612 0.851 1.76 4 0

Uganda Kenya 252329 577.256 567.819 9.437 4 0

Uganda Kenya 252330 0.053 0.014 0.038 4 0

Uganda Kenya 252390 1.508 0.966 0.543 4 0

Uganda Kenya 252520 0.024 0.024 0 4 0

Uganda Kenya 252620 0 0 0 0 0

Uganda Kenya 252910 1.64 1.64 0 4 0

102

Uganda Kenya 252921 4.424 4.424 0 4 0

Uganda Kenya 253090 0.674 0.413 0.26 4 0

Uganda Kenya 270112 1.384 1.384 0 4 0

Uganda Kenya 270119 0 0 0 0 0

Uganda Kenya 270300 0.379 0.178 0.201 4 0

Uganda Kenya 270500 5.649 5.573 0.076 6 0

Uganda Kenya 270720 0 0 0 0 0

Uganda Kenya 270740 0 0 0 0 0

Uganda Kenya 270799 0 0 0 0 0

Uganda Kenya 270900 1.05 1.05 0 6 0

Uganda Kenya 271011 23515.2

29

23500.762 14.467 2 0

Uganda Kenya 271019 14706.2

53

14563.541 142.712 3 0

Uganda Kenya 271091 6.111 5.904 0.207 4 0

Uganda Kenya 271099 0.078 0.041 0.037 4 0

Uganda Kenya 271111 24.338 24.183 0.155 4 0

Uganda Kenya 271112 0.312 0.268 0.044 4 0

Uganda Kenya 271113 2.338 2.338 0 4 0

Uganda Kenya 271114 0.131 0.131 0 4 0

Uganda Kenya 271119 1.416 1.352 0.063 4 0

Uganda Kenya 271129 0 0 0 0 0

Uganda Kenya 271210 12.99 5.517 7.474 4 0

Uganda Kenya 271220 0 0 0 0 0

Uganda Kenya 271290 0 0 0 0 0

Uganda Kenya 271320 21.189 12.815 8.373 4 0

Uganda Kenya 271390 0 0 0 0 0

Uganda Kenya 271410 31.989 25.802 6.187 4 0

Uganda Kenya 271490 11.723 6.398 5.325 4 0

Uganda Kenya 271500 11.208 4.904 6.304 4 0

Uganda Kenya 280110 0 0 0 0 0

Uganda Kenya 280200 0 0 0 0 0

Uganda Kenya 280300 0 0 0 0 0

Uganda Kenya 280421 0 0 0 0 0

Uganda Kenya 280429 0 0 0 0 0

Uganda Kenya 280430 0 0 0 0 0

Uganda Kenya 280440 0 0 0 0 0

Uganda Kenya 280519 0 0 0 0 0

Uganda Kenya 280610 0 0 0 0 0

Uganda Kenya 280700 0 0 0 0 0

Uganda Kenya 280800 0 0 0 0 0

Uganda Kenya 280910 0 0 0 0 0

Uganda Kenya 280920 0 0 0 0 0

Uganda Kenya 281119 0 0 0 0 0

Uganda Kenya 281121 0 0 0 0 0

Uganda Kenya 281122 0 0 0 0 0

Uganda Kenya 281410 0 0 0 0 0

Uganda Kenya 281511 0 0 0 0 0

Uganda Kenya 281512 0 0 0 0 0

103

Uganda Kenya 281610 0 0 0 0 0

Uganda Kenya 282010 0 0 0 0 0

Uganda Kenya 282110 0 0 0 0 0

Uganda Kenya 282120 0 0 0 0 0

Uganda Kenya 282300 0 0 0 0 0

Uganda Kenya 282590 0 0 0 0 0

Uganda Kenya 282620 0 0 0 0 0

Uganda Kenya 282710 0 0 0 0 0

Uganda Kenya 282720 0 0 0 0 0

Uganda Kenya 282810 0 0 0 0 0

Uganda Kenya 282919 0 0 0 0 0

Uganda Kenya 282990 0 0 0 0 0

Uganda Kenya 283010 0 0 0 0 0

Uganda Kenya 283090 0 0 0 0 0

Uganda Kenya 283210 0 0 0 0 0

Uganda Kenya 283311 0 0 0 0 0

Uganda Kenya 283319 0 0 0 0 0

Uganda Kenya 283321 0 0 0 0 0

Uganda Kenya 283322 0 0 0 0 0

Uganda Kenya 283323 0 0 0 0 0

Uganda Kenya 283327 0 0 0 0 0

Uganda Kenya 283329 0 0 0 0 0

Uganda Kenya 283429 0 0 0 0 0

Uganda Kenya 283539 0 0 0 0 0

Uganda Kenya 283610 0 0 0 0 0

Uganda Kenya 283620 0 0 0 0 0

Uganda Kenya 283630 0 0 0 0 0

Uganda Kenya 283650 0 0 0 0 0

Uganda Kenya 283691 0 0 0 0 0

Uganda Kenya 283699 0 0 0 0 0

Uganda Kenya 283911 0 0 0 0 0

Uganda Kenya 283919 0 0 0 0 0

Uganda Kenya 284011 0 0 0 0 0

Uganda Kenya 284019 0 0 0 0 0

Uganda Kenya 284190 0 0 0 0 0

Uganda Kenya 284690 0 0 0 0 0

Uganda Kenya 284700 0 0 0 0 0

Uganda Kenya 284920 0 0 0 0 0

Uganda Kenya 285100 0 0 0 0 0

Uganda Kenya 290129 0 0 0 0 0

Uganda Kenya 290220 0 0 0 0 0

Uganda Kenya 290230 0 0 0 0 0

Uganda Kenya 290241 0 0 0 0 0

Uganda Kenya 290244 0 0 0 0 0

Uganda Kenya 290312 0 0 0 0 0

Uganda Kenya 290345 0 0 0 0 0

Uganda Kenya 290511 0 0 0 0 0

Uganda Kenya 290512 0 0 0 0 0

Uganda Kenya 290513 0 0 0 0 0

104

Uganda Kenya 290514 0 0 0 0 0

Uganda Kenya 290516 0 0 0 0 0

Uganda Kenya 290517 0 0 0 0 0

Uganda Kenya 290519 0 0 0 0 0

Uganda Kenya 290531 0 0 0 0 0

Uganda Kenya 290532 0 0 0 0 0

Uganda Kenya 290539 0 0 0 0 0

Uganda Kenya 290541 0 0 0 0 0

Uganda Kenya 290545 0 0 0 0 0

Uganda Kenya 290713 0 0 0 0 0

Uganda Kenya 290729 0 0 0 0 0

Uganda Kenya 290943 0 0 0 0 0

Uganda Kenya 290944 0 0 0 0 0

Uganda Kenya 290949 0 0 0 0 0

Uganda Kenya 291211 0 0 0 0 0

Uganda Kenya 291411 0 0 0 0 0

Uganda Kenya 291412 0 0 0 0 0

Uganda Kenya 291413 0 0 0 0 0

Uganda Kenya 291511 0 0 0 0 0

Uganda Kenya 291512 0 0 0 0 0

Uganda Kenya 291521 0 0 0 0 0

Uganda Kenya 291529 0 0 0 0 0

Uganda Kenya 291533 0 0 0 0 0

Uganda Kenya 291539 0 0 0 0 0

Uganda Kenya 291590 0 0 0 0 0

Uganda Kenya 291612 0 0 0 0 0

Uganda Kenya 291631 0 0 0 0 0

Uganda Kenya 291632 0 0 0 0 0

Uganda Kenya 291639 0 0 0 0 0

Uganda Kenya 291714 0 0 0 0 0

Uganda Kenya 291719 0 0 0 0 0

Uganda Kenya 291735 0 0 0 0 0

Uganda Kenya 291811 0 0 0 0 0

Uganda Kenya 291814 1.713 0.995 0.719 4 0

Uganda Kenya 291829 0 0 0 0 0

Uganda Kenya 291890 0 0 0 0 0

Uganda Kenya 292112 0 0 0 0 0

Uganda Kenya 292151 0 0 0 0 0

Uganda Kenya 292242 0 0 0 0 0

Uganda Kenya 292429 0 0 0 0 0

Uganda Kenya 292511 0 0 0 0 0

Uganda Kenya 292700 0 0 0 0 0

Uganda Kenya 292910 0 0 0 0 0

Uganda Kenya 293020 0 0 0 0 0

Uganda Kenya 293090 0 0 0 0 0

Uganda Kenya 293627 0 0 0 0 0

Uganda Kenya 293629 0 0 0 0 0

Uganda Kenya 293690 0 0 0 0 0

Uganda Kenya 293919 0 0 0 0 0

105

Uganda Kenya 294000 0 0 0 0 0

Uganda Kenya 294140 0 0 0 0 0

Uganda Kenya 294200 0 0 0 0 0

Uganda Kenya 300190 0 0 0 0 0

Uganda Kenya 300210 0 0 0 0 0

Uganda Kenya 300220 0 0 0 0 0

Uganda Kenya 300230 0 0 0 0 0

Uganda Kenya 300290 0 0 0 0 0

Uganda Kenya 300310 0 0 0 0 0

Uganda Kenya 300339 0 0 0 0 0

Uganda Kenya 300390 0 0 0 0 0

Uganda Kenya 300410 0 0 0 0 0

Uganda Kenya 300439 0 0 0 0 0

Uganda Kenya 300440 0 0 0 0 0

Uganda Kenya 300450 0 0 0 0 0

Uganda Kenya 300490 0 0 0 0 0

Uganda Kenya 300510 0 0 0 0 0

Uganda Kenya 300590 0 0 0 0 0

Uganda Kenya 300610 0 0 0 0 0

Uganda Kenya 300620 0 0 0 0 0

Uganda Kenya 300630 0 0 0 0 0

Uganda Kenya 300650 0 0 0 0 0

Uganda Kenya 300670 0 0 0 0 0

Uganda Kenya 310100 0 0 0 0 0

Uganda Kenya 310210 0 0 0 0 0

Uganda Kenya 310221 0 0 0 0 0

Uganda Kenya 310229 0 0 0 0 0

Uganda Kenya 310230 0 0 0 0 0

Uganda Kenya 310240 0 0 0 0 0

Uganda Kenya 310260 0 0 0 0 0

Uganda Kenya 310270 0 0 0 0 0

Uganda Kenya 310290 0 0 0 0 0

Uganda Kenya 310310 0 0 0 0 0

Uganda Kenya 310390 0 0 0 0 0

Uganda Kenya 310410 0 0 0 0 0

Uganda Kenya 310430 0 0 0 0 0

Uganda Kenya 310490 0 0 0 0 0

Uganda Kenya 310510 0 0 0 0 0

Uganda Kenya 310520 0 0 0 0 0

Uganda Kenya 310530 0 0 0 0 0

Uganda Kenya 310540 0 0 0 0 0

Uganda Kenya 310551 0 0 0 0 0

Uganda Kenya 310559 0 0 0 0 0

Uganda Kenya 310590 0 0 0 0 0

Uganda Kenya 320120 0 0 0 0 0

Uganda Kenya 320210 0 0 0 0 0

Uganda Kenya 320290 0 0 0 0 0

Uganda Kenya 320300 0 0 0 0 0

Uganda Kenya 320411 0 0 0 0 0

106

Uganda Kenya 320412 0 0 0 0 0

Uganda Kenya 320414 0 0 0 0 0

Uganda Kenya 320415 0 0 0 0 0

Uganda Kenya 320416 0 0 0 0 0

Uganda Kenya 320417 0 0 0 0 0

Uganda Kenya 320420 0 0 0 0 0

Uganda Kenya 320611 0 0 0 0 0

Uganda Kenya 320619 0 0 0 0 0

Uganda Kenya 320630 0.142 0.085 0.057 4 0

Uganda Kenya 320641 0.061 0.061 0 4 0

Uganda Kenya 320649 0 0 0 0 0

Uganda Kenya 320710 0 0 0 0 0

Uganda Kenya 320730 0 0 0 0 0

Uganda Kenya 320810 0.727 0.347 0.381 6 0

Uganda Kenya 320890 73.625 64.546 9.08 6 0

Uganda Kenya 320910 7.654 6.43 1.224 6 0

Uganda Kenya 320990 0.339 0.15 0.189 6 0

Uganda Kenya 321000 0.1 0.048 0.052 4 0

Uganda Kenya 321290 0 0 0 0 0

Uganda Kenya 321390 0.25 0.178 0.073 6 0

Uganda Kenya 321410 4.538 2.069 2.468 6 0

Uganda Kenya 321490 7.537 4.662 2.875 6 0

Uganda Kenya 321511 0 0 0 0 0

Uganda Kenya 321519 0 0 0 0 0

Uganda Kenya 321590 0 0 0 0 0

Uganda Kenya 330190 1.697 1.116 0.581 6 0

Uganda Kenya 330210 0 0 0 0 0

Uganda Kenya 330290 0.988 0.422 0.566 2.5 0

Uganda Kenya 330300 7.077 2.088 4.988 6 0

Uganda Kenya 330410 0.357 0.114 0.243 6 0

Uganda Kenya 330430 1.773 0.87 0.903 6 0

Uganda Kenya 330491 2.401 0.916 1.484 6 0

Uganda Kenya 330499 46.857 18.531 28.326 6 0

Uganda Kenya 330510 1.45 0.205 1.245 6 0

Uganda Kenya 330530 4.591 2.462 2.129 6 0

Uganda Kenya 330590 54.844 27.414 27.43 6 0

Uganda Kenya 330610 79.971 38.021 41.95 4 0

Uganda Kenya 330710 1.199 0.542 0.656 6 0

Uganda Kenya 330720 5.519 1.728 3.791 6 0

Uganda Kenya 330730 2.869 2.344 0.524 6 0

Uganda Kenya 330749 2.483 0.796 1.687 6 0

Uganda Kenya 330790 7.187 4.31 2.877 6 0

Uganda Kenya 340111 89.924 62.326 27.598 6 0

Uganda Kenya 340119 46.331 38.379 7.952 6 0

Uganda Kenya 340120 117.264 59.078 58.186 6 0

Uganda Kenya 340130 0.715 0.005 0.71 6 0

Uganda Kenya 340211 0 0 0 0 0

Uganda Kenya 340212 0.383 0.176 0.207 4 0

Uganda Kenya 340213 0.204 0.13 0.074 4 0

107

Uganda Kenya 340219 1.483 1.055 0.427 4 0

Uganda Kenya 340220 5.8 0.834 4.967 6 0

Uganda Kenya 340290 1.036 0.723 0.313 6 0

Uganda Kenya 340319 0.091 0.058 0.034 4 0

Uganda Kenya 340399 0.121 0.061 0.06 4 0

Uganda Kenya 340410 0 0 0 0 0

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110

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Uganda Kenya 610729 0.079 0.034 0.044 6 0

Uganda Kenya 610799 2.872 2.833 0.038 6 0

Uganda Kenya 610811 0.164 0.047 0.117 6 0

Uganda Kenya 610819 1.614 0.826 0.788 6 0

Uganda Kenya 610829 0.737 0.26 0.477 6 0

Uganda Kenya 610899 0.132 0.057 0.075 6 0

Uganda Kenya 610910 19.768 9.98 9.787 6 0

Uganda Kenya 610990 13.939 6.785 7.154 6 0

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Uganda Kenya 611019 0.984 0.886 0.098 6 0

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Uganda Kenya 611110 6.125 5.875 0.25 6 0

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Uganda Kenya 611190 14.667 7.044 7.622 6 0

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Uganda Kenya 611490 0.272 0.043 0.228 6 0

Uganda Kenya 611519 0.752 0.312 0.44 6 0

Uganda Kenya 611591 0.148 0.066 0.083 6 0

Uganda Kenya 611592 9.662 8.913 0.749 6 0

Uganda Kenya 611593 0.099 0.077 0.022 6 0

Uganda Kenya 611599 0.52 0.137 0.382 6 0

Uganda Kenya 611710 1.449 0.393 1.056 6 0

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Uganda Kenya 611780 0.768 0.318 0.45 6 0

Uganda Kenya 611790 3.531 3.442 0.089 6 0

Uganda Kenya 620113 0.273 0.127 0.146 6 0

Uganda Kenya 620119 0.358 0.15 0.209 6 0

Uganda Kenya 620191 0.09 0.09 0 6 0

Uganda Kenya 620192 0.105 0.094 0.011 6 0

Uganda Kenya 620199 0.288 0.136 0.152 6 0

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Uganda Kenya 620299 0.128 0.047 0.081 6 0

Uganda Kenya 620312 0.541 0.491 0.05 6 0

Uganda Kenya 620319 6.069 2.734 3.335 6 0

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Uganda Kenya 620339 0.494 0.112 0.383 6 0

Uganda Kenya 620342 1.058 0.633 0.426 6 0

117

Uganda Kenya 620349 4.375 1.84 2.534 6 0

Uganda Kenya 620419 1.819 0.663 1.156 6 0

Uganda Kenya 620429 0.118 0.03 0.088 6 0

Uganda Kenya 620439 0.171 0.066 0.105 6 0

Uganda Kenya 620441 0.535 0.429 0.106 6 0

Uganda Kenya 620442 0.151 0.05 0.101 6 0

Uganda Kenya 620443 0.155 0.076 0.079 6 0

Uganda Kenya 620444 4.082 1.674 2.408 6 0

Uganda Kenya 620449 16.074 7.251 8.823 6 0

Uganda Kenya 620452 0.107 0.072 0.035 6 0

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Uganda Kenya 620469 0.424 0.155 0.269 6 0

Uganda Kenya 620520 1.634 0.893 0.741 6 0

Uganda Kenya 620590 8.264 3.426 4.838 6 0

Uganda Kenya 620610 20.042 18.61 1.432 6 0

Uganda Kenya 620630 0.094 0.044 0.05 6 0

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Uganda Kenya 620690 1.243 0.343 0.9 6 0

Uganda Kenya 620711 0.275 0.028 0.247 6 0

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Uganda Kenya 620729 0.78 0.333 0.447 6 0

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Uganda Kenya 620819 13.835 8.212 5.624 6 0

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Uganda Kenya 620891 0.525 0.276 0.248 6 0

Uganda Kenya 620899 1.56 0.687 0.873 6 0

Uganda Kenya 620910 1.352 0.479 0.872 6 0

Uganda Kenya 620990 5.926 2.415 3.511 6 0

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Uganda Kenya 621290 0.684 0.229 0.455 6 0

Uganda Kenya 621390 0.588 0.24 0.348 6 0

Uganda Kenya 621410 3.059 1.973 1.086 6 0

Uganda Kenya 621420 0.137 0.137 0 6 0

Uganda Kenya 621430 2.848 2.139 0.709 6 0

Uganda Kenya 621440 0.44 0.38 0.06 6 0

Uganda Kenya 621490 6.324 3.14 3.183 6 0

Uganda Kenya 621710 0.123 0.02 0.103 6 0

Uganda Kenya 621790 0.708 0.244 0.464 6 0

Uganda Kenya 630120 4.196 1.851 2.345 6 0

118

Uganda Kenya 630130 0.399 0.157 0.242 6 0

Uganda Kenya 630140 233.821 208.083 25.738 6 0

Uganda Kenya 630190 3.432 1.376 2.056 6 0

Uganda Kenya 630210 0.283 0.115 0.168 6 0

Uganda Kenya 630229 0.106 0.056 0.05 6 0

Uganda Kenya 630239 0.219 0.075 0.144 6 0

Uganda Kenya 630240 0.414 0.267 0.147 6 0

Uganda Kenya 630251 1.63 1.397 0.233 6 0

Uganda Kenya 630260 0.837 0.218 0.619 6 0

Uganda Kenya 630299 0.848 0.374 0.475 6 0

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Uganda Kenya 630419 0.121 0.067 0.053 4 0

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Uganda Kenya 630499 0.607 0.282 0.326 4 0

Uganda Kenya 630510 6.251 2.622 3.629 6 0

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Uganda Kenya 630539 0.464 0.129 0.335 6 0

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Uganda Kenya 630629 13.03 7.026 6.005 6 0

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Uganda Kenya 640351 0.168 0.107 0.061 6 0

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Uganda Kenya 640399 15.297 6.472 8.826 6 0

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Uganda Kenya 640610 0.103 0.048 0.054 4 0

Uganda Kenya 640620 28.768 25.893 2.875 4 0

Uganda Kenya 640699 1.261 0.917 0.344 6 0

Uganda Kenya 650100 0.069 0.026 0.043 6 0

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Uganda Kenya 650510 0.117 0.073 0.044 6 0

Uganda Kenya 650590 6.676 2.888 3.788 6 0

Uganda Kenya 650610 0 0 0 0 0

Uganda Kenya 650699 3.982 2.133 1.849 6 0

119

Uganda Kenya 650700 0.2 0.141 0.059 6 0

Uganda Kenya 660110 2.785 1.373 1.412 6 0

Uganda Kenya 660191 0.306 0.25 0.056 6 0

Uganda Kenya 660199 1.784 1.076 0.709 6 0

Uganda Kenya 670300 7.356 6.398 0.958 6 0

Uganda Kenya 670411 0.189 0.089 0.101 6 0

Uganda Kenya 670419 18.848 18.581 0.268 6 0

Uganda Kenya 670420 19.837 19.693 0.144 6 0

Uganda Kenya 670490 2.047 1.325 0.721 6 0

Uganda Kenya 680221 1.069 0.745 0.324 6 0

Uganda Kenya 680223 2.975 1.551 1.424 6 0

Uganda Kenya 680229 4.348 1.694 2.655 6 0

Uganda Kenya 680293 59.485 58.386 1.099 6 0

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Uganda Kenya 680422 1.094 0.47 0.624 6 0

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Uganda Kenya 681110 0.564 0.564 0 6 0

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Uganda Kenya 681290 0.219 0.079 0.14 6 0

Uganda Kenya 681310 1.166 0.462 0.704 4 0

Uganda Kenya 681390 0.147 0.044 0.103 4 0

Uganda Kenya 690100 4.256 3.724 0.532 6 0

Uganda Kenya 690310 0.054 0.017 0.037 6 0

Uganda Kenya 690410 2.543 2.543 0 6 0

Uganda Kenya 690490 17.331 12.398 4.932 6 0

Uganda Kenya 690510 1.687 1.198 0.488 6 0

Uganda Kenya 690590 0.297 0.137 0.16 6 0

Uganda Kenya 690710 3.067 1.705 1.362 6 0

Uganda Kenya 690790 2.299 1.456 0.842 6 0

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Uganda Kenya 690890 1.156 0.535 0.622 6 0

Uganda Kenya 690990 1.536 0.844 0.692 6 0

Uganda Kenya 691010 2.244 0.87 1.373 6 0

Uganda Kenya 691090 2.042 0.908 1.134 6 0

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Uganda Kenya 691190 1.283 0.681 0.602 6 0

Uganda Kenya 691200 11.3 5.299 6.001 6 0

Uganda Kenya 691310 0.566 0.294 0.272 6 0

Uganda Kenya 691390 0.182 0.071 0.112 6 0

Uganda Kenya 691410 0.11 0.05 0.06 6 0

Uganda Kenya 691490 0.149 0.074 0.075 6 0

Uganda Kenya 700490 0.546 0.265 0.281 6 0

Uganda Kenya 700510 1.033 0.481 0.551 6 0

Uganda Kenya 700521 3.497 2.571 0.926 6 0

120

Uganda Kenya 700529 35.387 18.188 17.199 6 0

Uganda Kenya 700530 0.285 0.284 0.001 6 0

Uganda Kenya 700600 0.135 0.08 0.055 6 0

Uganda Kenya 700711 0.623 0.06 0.563 6 0

Uganda Kenya 700719 0.24 0.141 0.099 6 0

Uganda Kenya 700721 7.438 4.35 3.088 6 0

Uganda Kenya 700729 6.018 3.316 2.702 6 0

Uganda Kenya 700910 0.83 0.121 0.709 6 0

Uganda Kenya 700991 1.415 0.793 0.622 6 0

Uganda Kenya 700992 2.27 0.867 1.403 6 0

Uganda Kenya 701010 3.266 1.637 1.628 4 0

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Uganda Kenya 701090 65.02 34.333 30.687 4 0

Uganda Kenya 701120 0.149 0.149 0 6 0

Uganda Kenya 701190 0.057 0.008 0.049 6 0

Uganda Kenya 701310 0.13 0.047 0.083 6 0

Uganda Kenya 701321 0.096 0.086 0.01 6 0

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Uganda Kenya 701339 0.562 0.237 0.325 6 0

Uganda Kenya 701399 1.85 0.665 1.185 6 0

Uganda Kenya 701690 0.727 0.436 0.29 6 0

Uganda Kenya 701710 0 0 0 0 0

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Uganda Kenya 701911 0.083 0.026 0.058 4 0

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Uganda Kenya 701990 0.204 0.066 0.138 4 0

Uganda Kenya 702000 1.404 0.662 0.742 4 0

Uganda Kenya 710110 0.091 0.085 0.007 6 0

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Uganda Kenya 711719 0.133 0.082 0.05 6 0

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Uganda Kenya 720854 0.125 0.125 0 4 0

Uganda Kenya 720890 0.549 0.549 0 4 0

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Uganda Kenya 720926 0.345 0.345 0 4 0

Uganda Kenya 720990 0.37 0.218 0.152 4 0

121

Uganda Kenya 721011 0.44 0.44 0 4 0

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Uganda Kenya 721113 7.591 7.591 0 4 0

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Uganda Kenya 721691 0.033 0.033 0 4 0

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Uganda Kenya 722699 0.49 0.48 0.01 4 0

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123

Uganda Kenya 731822 0.089 0.04 0.049 4 0

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124

Uganda Kenya 760900 0.076 0.027 0.049 4 0

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125

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127

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128

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130

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131

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133

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Uganda Kenya 902750 0 0 0 0 0

Uganda Kenya 902780 0 0 0 0 0

Uganda Kenya 902820 0 0 0 0 0

Uganda Kenya 902890 0 0 0 0 0

Uganda Kenya 902920 0 0 0 0 0

Uganda Kenya 902990 0 0 0 0 0

Uganda Kenya 903031 0 0 0 0 0

Uganda Kenya 903039 0 0 0 0 0

Uganda Kenya 903040 0 0 0 0 0

Uganda Kenya 903089 0 0 0 0 0

Uganda Kenya 903090 0 0 0 0 0

Uganda Kenya 903110 0 0 0 0 0

Uganda Kenya 903180 0 0 0 0 0

Uganda Kenya 903289 0 0 0 0 0

Uganda Kenya 903290 0 0 0 0 0

Uganda Kenya 910129 0.614 0.35 0.264 6 0

Uganda Kenya 910219 0.229 0.13 0.099 6 0

Uganda Kenya 910229 0.942 0.633 0.31 6 0

Uganda Kenya 910519 0.199 0.112 0.086 6 0

Uganda Kenya 910990 0.114 0.069 0.045 6 0

Uganda Kenya 920290 0.148 0.11 0.038 4 0

Uganda Kenya 920300 0.042 0.01 0.032 4 0

Uganda Kenya 930190 58.797 58.797 0 4 0

Uganda Kenya 940130 0.11 0.05 0.06 6 0

Uganda Kenya 940150 0.133 0.101 0.033 6 0

Uganda Kenya 940161 9.106 6.664 2.442 6 0

Uganda Kenya 940169 2.589 1.091 1.499 6 0

Uganda Kenya 940171 0.174 0.052 0.122 6 0

Uganda Kenya 940180 1.4 0.514 0.886 6 0

Uganda Kenya 940210 0.049 0.014 0.035 2 0

Uganda Kenya 940310 4.964 2.231 2.733 6 0

Uganda Kenya 940320 1.407 0.238 1.169 6 0

135

Uganda Kenya 940330 14.697 3.929 10.768 6 0

Uganda Kenya 940340 0.499 0.409 0.091 6 0

Uganda Kenya 940350 1 0.069 0.931 6 0

Uganda Kenya 940360 14.453 1.036 13.417 6 0

Uganda Kenya 940370 29.019 14.825 14.194 6 0

Uganda Kenya 940380 8.878 3.566 5.312 6 0

Uganda Kenya 940390 1.296 0.695 0.601 6 0

Uganda Kenya 940410 1.759 1.318 0.442 6 0

Uganda Kenya 940421 1.146 0.771 0.374 6 0

Uganda Kenya 940429 0.251 0.119 0.133 6 0

Uganda Kenya 940490 0.105 0.021 0.084 6 0

Uganda Kenya 940510 10.787 5.309 5.478 6 0

Uganda Kenya 940540 3.696 1.553 2.143 6 0

Uganda Kenya 940550 11.846 4.998 6.847 6 0

Uganda Kenya 940560 31.489 13.811 17.677 6 0

Uganda Kenya 940591 4.315 1.927 2.388 6 0

Uganda Kenya 940599 0.127 0.03 0.096 6 0

Uganda Kenya 940600 22.287 6.762 15.524 3 0

Uganda Kenya 950210 0.722 0.286 0.436 6 0

Uganda Kenya 950440 0.399 0.159 0.24 6 0

Uganda Kenya 950590 0.074 0.028 0.046 6 0

Uganda Kenya 950619 0.109 0.055 0.054 6 0

Uganda Kenya 950669 0.1 0.042 0.058 6 0

Uganda Kenya 950691 0.104 0.046 0.058 6 0

Uganda Kenya 950699 0.132 0.052 0.081 6 0

Uganda Kenya 950720 0.168 0.083 0.085 4 0

Uganda Kenya 950730 0.064 0.03 0.034 4 0

Uganda Kenya 950790 2.135 1.287 0.848 4 0

Uganda Kenya 960200 0.154 0.102 0.052 6 0

Uganda Kenya 960310 2.395 1.235 1.16 6 0

Uganda Kenya 960321 3.296 1.749 1.548 6 0

Uganda Kenya 960329 0.448 0.207 0.241 6 0

Uganda Kenya 960330 0.199 0.092 0.107 6 0

Uganda Kenya 960340 0.697 0.248 0.449 6 0

Uganda Kenya 960350 0.525 0.302 0.223 6 0

Uganda Kenya 960390 0.615 0.21 0.405 6 0

Uganda Kenya 960610 0.076 0.041 0.035 4 0

Uganda Kenya 960621 0.057 0.017 0.039 4 0

Uganda Kenya 960629 0.092 0.055 0.037 4 0

Uganda Kenya 960711 0.41 0.154 0.256 4 0

Uganda Kenya 960719 0.318 0.233 0.084 4 0

Uganda Kenya 960720 0.727 0.715 0.012 4 0

Uganda Kenya 960810 41.085 22.194 18.891 4 0

Uganda Kenya 960839 0.159 0.061 0.098 4 0

Uganda Kenya 960910 0.379 0.069 0.31 4 0

Uganda Kenya 960990 7.523 6.581 0.942 4 0

Uganda Kenya 961000 0.213 0.089 0.124 4 0

Uganda Kenya 961210 1.21 0.571 0.638 4 0

Uganda Kenya 961310 0.558 0.281 0.277 6 0

136

Uganda Kenya 961320 0.112 0.039 0.073 6 0

Uganda Kenya 961511 0.107 0.04 0.067 6 0

Uganda Kenya 961519 0.641 0.301 0.34 6 0

Uganda Kenya 961700 14.015 5.921 8.094 6 0

Uganda Kenya 961800 0.107 0.046 0.061 6 0

Uganda Kenya 970300 0.604 0.364 0.24 6 0

Uganda Tanzania 10420 10.461 10.283 0.178 4 0

Uganda Tanzania 30510 1.723 1.723 0 6 0

Uganda Tanzania 30549 0.27 0.139 0.132 6 0

Uganda Tanzania 30619 0.654 0.654 0 6 0

Uganda Tanzania 30629 1.459 1.459 0 6 0

Uganda Tanzania 51191 5.233 5.233 0 4 0

Uganda Tanzania 51199 1.937 1.934 0.003 4 0

Uganda Tanzania 60290 0 0 0 0 0

Uganda Tanzania 70810 0.133 0.101 0.033 6 0

Uganda Tanzania 71331 3.921 0.127 3.794 6 0

Uganda Tanzania 80132 1.659 1.649 0.011 6 0

Uganda Tanzania 90112 0.111 0.075 0.036 4 0

Uganda Tanzania 90920 0.085 0.049 0.036 4 0

Uganda Tanzania 91099 1.197 0.705 0.492 4 0


Uganda Tanzania 100590 23.476 12.109 11.367 4 0

Uganda Tanzania 100610 0.068 0.028 0.04 6 0

Uganda Tanzania 100620 0.081 0.028 0.053 6 0

Uganda Tanzania 100630 1.084 0.286 0.798 6 0

Uganda Tanzania 100640 2.631 1.154 1.477 6 0

Uganda Tanzania 120210 0.336 0.335 0 4 0

Uganda Tanzania 120220 1.038 1.038 0 4 0

Uganda Tanzania 120720 7.991 7.991 0 4 0


Uganda Tanzania 151620 8.219 3.524 4.695 6 0

Uganda Tanzania 170490 0.207 0.096 0.111 6 0

Uganda Tanzania 220300 24.563 5.665 18.898 6 0

Uganda Tanzania 220890 8.414 3.144 5.269 6 0

Uganda Tanzania 230610 114.235 114.235 0 6 0

Uganda Tanzania 230630 1.629 1.629 0 6 0

Uganda Tanzania 230690 0.087 0.087 0 6 0

Uganda Tanzania 240290 2.774 2.774 0 6 0

Uganda Tanzania 271011 82.087 82.035 0.052 2 0

Uganda Tanzania 271019 45.863 45.373 0.491 3 0





Uganda Tanzania 340220 0.007 0.001 0.007 6 0

Uganda Tanzania 340290 3.042 2.157 0.885 6 0

Uganda Tanzania 360200 0.921 0.234 0.686 6 0

137

Uganda Tanzania 392059 4.267 2.688 1.579 4 0

Uganda Tanzania 392190 0.122 0.058 0.064 4 0

Uganda Tanzania 392310 1.839 1.365 0.473 6 0

Uganda Tanzania 392520 0.491 0.363 0.128 6 0

Uganda Tanzania 392640 0.271 0.135 0.136 6 0

Uganda Tanzania 392690 0.829 0.495 0.334 6 0

Uganda Tanzania 401110 2.347 0.867 1.48 4 0

Uganda Tanzania 401150 2.472 1.013 1.459 4 0

Uganda Tanzania 440310 17.339 8.467 8.872 4 0

Uganda Tanzania 441520 4.447 4.29 0.157 6 0

Uganda Tanzania 442090 1.264 1.114 0.15 6 0

Uganda Tanzania 481149 0.123 0.102 0.021 4 0

Uganda Tanzania 481710 8.014 5.102 2.912 6 0

Uganda Tanzania 482010 0.463 0.187 0.276 6 0


Uganda Tanzania 490890 0.348 0.187 0.161 4 0

Uganda Tanzania 551341 22.766 10.629 12.137 4 0

Uganda Tanzania 560721 0.612 0.612 0 4 0

Uganda Tanzania 560811 0.805 0.065 0.74 6 0

Uganda Tanzania 560819 1.474 0.531 0.943 4 0

Uganda Tanzania 560890 7.144 3.41 3.734 4 0

Uganda Tanzania 580410 2.704 1.049 1.656 6 0

Uganda Tanzania 610910 1.212 0.58 0.632 6 0

Uganda Tanzania 610990 1.263 0.596 0.667 6 0

Uganda Tanzania 620444 0.185 0.07 0.115 6 0

Uganda Tanzania 630419 10.029 5.698 4.331 4 0

Uganda Tanzania 630533 7.844 3.272 4.572 6 0

Uganda Tanzania 630790 0.841 0.381 0.459 6 0

Uganda Tanzania 630900 87.908 36.737 51.171 6 0

Uganda Tanzania 640220 5.773 5.187 0.586 6 0

Uganda Tanzania 640299 3.168 1.37 1.798 6 0

Uganda Tanzania 640590 0.913 0.256 0.656 6 0

Uganda Tanzania 681310 1.622 0.643 0.978 4 0

Uganda Tanzania 701090 16.425 8.53 7.895 4 0

Uganda Tanzania 711790 0.139 0.087 0.052 6 0

Uganda Tanzania 720918 321.906 311.608 10.298 4 0

Uganda Tanzania 721190 1.389 1.381 0.008 4 0

Uganda Tanzania 721391 0.052 0.021 0.03 4 0

Uganda Tanzania 730640 0.185 0.114 0.071 4 0

Uganda Tanzania 730890 0.051 0.023 0.028 4 0

Uganda Tanzania 731823 0.301 0.172 0.129 4 0

Uganda Tanzania 732399 0.146 0.06 0.087 4 0

Uganda Tanzania 821192 0.087 0.033 0.053 4 0

Uganda Tanzania 830300 0.472 0.191 0.281 6 0

Uganda Tanzania 840820 0.985 0.804 0.18 4 0





138


Uganda Tanzania 841510 16.034 3.899 12.136 4 0


Uganda Tanzania 842123 0.113 0.052 0.06 4 0

Uganda Tanzania 842129 0.069 0.019 0.05 4 0







Uganda Tanzania 847090 1.188 0.342 0.846 4 0











Uganda Tanzania 851310 0.226 0.094 0.132 4 0

Uganda Tanzania 851711 0.223 0.059 0.165 4 0




Uganda Tanzania 852390 0.209 0.122 0.086 4 0


Uganda Tanzania 852812 0.371 0.167 0.204 6 0


Uganda Tanzania 853649 0.064 0.023 0.041 4 0

Uganda Tanzania 853650 0.513 0.182 0.331 4 0

Uganda Tanzania 853710 0.767 0.368 0.399 4 0

Uganda Tanzania 853910 0.126 0.056 0.07 4 0

Uganda Tanzania 854420 0.615 0.199 0.416 6 0

Uganda Tanzania 870210 1.733 0.887 0.846 5.6 0

Uganda Tanzania 870323 0.348 0.137 0.21 6 0

Uganda Tanzania 870421 1.015 0.407 0.609 4 0

Uganda Tanzania 870422 1.12 0.527 0.593 4 0

Uganda Tanzania 871639 0.037 0.012 0.025 4 0

Uganda Tanzania 900911 0.894 0.391 0.502 4 0

Uganda Tanzania 900991 0.626 0.246 0.38 4 0

Uganda Tanzania 900993 1.291 0.524 0.767 4 0

Uganda Tanzania 900999 0.674 0.263 0.411 4 0

Uganda Tanzania 910229 0.371 0.246 0.125 6 0

Uganda Tanzania 940180 0.203 0.074 0.129 6 0

Uganda Tanzania 960810 0.197 0.103 0.094 4 0

Uganda Tanzania 960891 0.169 0.067 0.102 4 0

139

Uganda Tanzania 970190 0.102 0.051 0.051 6 0

Uganda Tanzania Total 929.929 738.115 191.814 3.69 0

Appendix V

WITS/SMART Simulation Results for Tanzania (Level.6 SITC Rev-3

UNCTAD)

Reporter

Name

Partner

Name

Product

Code

TradeTo

talEffect

in 1000

USD

TradeCr

eationEf

fect in

1000

USD

TradeDiv

ersionEff

ect in

1000

USD

OldSimp

leDutyR

ate

NewSi

mpleDu

tyRate

Tanzania Kenya 10119 0.103 0.085 0.018 5 0

Tanzania Kenya 10210 0 0 0 0 0


Tanzania Kenya 10511 15.542 10.146 5.396 2.5 0

Tanzania Kenya 10600 1.176 0.735 0.442 5 0

Tanzania Kenya 20120 0.237 0.136 0.101 5 0

Tanzania Kenya 20130 0.387 0.217 0.169 5 0

Tanzania Kenya 20210 0.167 0.167 0 5 0

Tanzania Kenya 20220 0.091 0.038 0.053 5 0

Tanzania Kenya 20230 2.184 1.507 0.677 5 0

Tanzania Kenya 20311 3.185 3.185 0 5 0

Tanzania Kenya 20312 3.773 3.773 0 5 0

Tanzania Kenya 20422 0.249 0.249 0 5 0

Tanzania Kenya 20711 0.267 0.247 0.02 5 0

Tanzania Kenya 20724 16.114 16.114 0 5 0

Tanzania Kenya 21011 1.669 1.653 0.016 5 0

Tanzania Kenya 21019 46.822 44.513 2.309 5 0

Tanzania Kenya 21090 0.347 0.193 0.155 5 0

Tanzania Kenya 30349 2.587 2.587 0 5 0

Tanzania Kenya 30410 1.896 1.663 0.234 5 0

Tanzania Kenya 40120 37.414 30.578 6.836 5 0

Tanzania Kenya 40210 1.206 0.365 0.841 5 0

Tanzania Kenya 40221 8.652 4.43 4.221 4 0

Tanzania Kenya 40229 0.97 0.737 0.233 4 0

Tanzania Kenya 40299 1.427 0.501 0.926 4 0

Tanzania Kenya 40390 0.79 0.293 0.497 5 0

Tanzania Kenya 40630 2.324 0.965 1.358 5 0

Tanzania Kenya 40690 0.17 0.098 0.072 5 0

140

Tanzania Kenya 40700 15.066 6.335 8.731 5 0




Tanzania Kenya 70700 0.288 0.266 0.022 5 0

Tanzania Kenya 70910 1.997 1.997 0 5 0

Tanzania Kenya 71010 1.562 1.124 0.438 5 0

Tanzania Kenya 71310 0.287 0.119 0.168 2.5 0

Tanzania Kenya 71333 0.29 0.124 0.166 2.5 0

Tanzania Kenya 80111 0.059 0.021 0.038 5 0

Tanzania Kenya 80410 0.073 0.03 0.042 5 0

Tanzania Kenya 80420 0.121 0.047 0.075 5 0

Tanzania Kenya 80510 0.594 0.355 0.239 5 0

Tanzania Kenya 90240 0.66 0.507 0.152 5 0

Tanzania Kenya 90411 0.182 0.074 0.108 5 0

Tanzania Kenya 91099 0.938 0.521 0.417 5 0

Tanzania Kenya 100190 0.158 0.081 0.077 1 0

Tanzania Kenya 100510 58.014 25.488 32.526 2.5 0

Tanzania Kenya 100590 0.248 0.13 0.118 5 0

Tanzania Kenya 110710 1.58 0.637 0.944 2 0

Tanzania Kenya 110720 0.352 0.349 0.003 2 0

Tanzania Kenya 110812 37.254 27.528 9.726 2 0

Tanzania Kenya 110814 0.026 0.026 0 5 0

Tanzania Kenya 120600 0.196 0.101 0.095 5 0




Tanzania Kenya 121490 1.222 1.174 0.049 5 0




Tanzania Kenya 150590 0.131 0.061 0.07 2 0

Tanzania Kenya 150600 0.016 0.016 0 2 0

Tanzania Kenya 150710 0.668 0.223 0.444 2 0

Tanzania Kenya 151190 34.209 14.145 20.064 3.5 0

Tanzania Kenya 151219 0.11 0.047 0.062 5 0

Tanzania Kenya 151229 0.023 0.023 0 5 0

Tanzania Kenya 151529 0.056 0.017 0.038 5 0

Tanzania Kenya 151590 0.693 0.297 0.396 5 0

Tanzania Kenya 151610 2.65 2.503 0.147 5 0

Tanzania Kenya 151620 30.518 17.421 13.097 5 0

Tanzania Kenya 151710 87.349 81.556 5.793 5 0

Tanzania Kenya 151790 2.43 0.743 1.686 5 0

Tanzania Kenya 152000 0.793 0.658 0.135 2 0


Tanzania Kenya 152200 0.16 0.067 0.093 2 0

Tanzania Kenya 160100 59.423 56.703 2.72 5 0

Tanzania Kenya 160300 0.086 0.027 0.059 5 0

Tanzania Kenya 170199 0.099 0.042 0.057 5 0

141

Tanzania Kenya 170230 0.695 0.343 0.352 2 0

Tanzania Kenya 170290 0.055 0.018 0.037 5 0

Tanzania Kenya 170410 36.986 25.08 11.906 5 0

Tanzania Kenya 170490 15.545 6.053 9.492 5 0

Tanzania Kenya 180500 0.092 0.025 0.067 5 0

Tanzania Kenya 180610 2.318 1.165 1.153 5 0

Tanzania Kenya 180631 4.898 2.038 2.86 5 0

Tanzania Kenya 180632 0.309 0.09 0.22 5 0

Tanzania Kenya 180690 1.445 0.829 0.616 5 0

Tanzania Kenya 190110 0.058 0.031 0.027 3 0

Tanzania Kenya 190190 0.239 0.065 0.174 5 0

Tanzania Kenya 190410 2.565 2.251 0.314 5 0

Tanzania Kenya 190420 1.703 1.515 0.188 5 0

Tanzania Kenya 190510 0.076 0.021 0.056 5 0

Tanzania Kenya 190530 4.675 1.701 2.974 5 0

Tanzania Kenya 190540 0.768 0.34 0.428 5 0

Tanzania Kenya 190590 0.849 0.365 0.485 1.67 0

Tanzania Kenya 200290 0.234 0.066 0.168 5 0

Tanzania Kenya 200490 0.142 0.068 0.074 5 0

Tanzania Kenya 200510 0.213 0.137 0.076 5 0

Tanzania Kenya 200520 0.293 0.095 0.198 5 0

Tanzania Kenya 200559 0.146 0.048 0.098 5 0

Tanzania Kenya 200919 1.421 0.876 0.544 5 0

Tanzania Kenya 200940 0.361 0.161 0.2 5 0

Tanzania Kenya 200980 1.225 0.353 0.872 5 0

Tanzania Kenya 200990 4.817 1.621 3.196 5 0

Tanzania Kenya 210130 0.023 0.015 0.008 3 0

Tanzania Kenya 210210 2.719 1.196 1.523 5 0

Tanzania Kenya 210220 0.549 0.281 0.268 5 0

Tanzania Kenya 210230 1.153 0.717 0.435 5 0

Tanzania Kenya 210310 0.18 0.057 0.123 5 0

Tanzania Kenya 210320 0.41 0.139 0.272 5 0

Tanzania Kenya 210390 2.16 1.663 0.497 5 0

Tanzania Kenya 210410 4.779 3.029 1.751 5 0

Tanzania Kenya 210420 0.26 0.088 0.172 5 0

Tanzania Kenya 210500 1.349 0.488 0.861 5 0

Tanzania Kenya 210610 0.497 0.164 0.332 3 0

Tanzania Kenya 210690 6.283 2.591 3.692 3.5 0

Tanzania Kenya 220110 4.078 2.182 1.896 5 0

Tanzania Kenya 220190 0.193 0.092 0.102 5 0

Tanzania Kenya 220210 0.497 0.155 0.342 5 0

Tanzania Kenya 220290 0.589 0.27 0.319 5 0

Tanzania Kenya 220300 13.15 0.694 12.456 20 0

Tanzania Kenya 220410 2.018 0.637 1.38 5 0

Tanzania Kenya 220421 1.183 0.414 0.769 5 0

Tanzania Kenya 220429 0.557 0.291 0.265 5 0

Tanzania Kenya 220510 0.435 0.184 0.251 5 0

Tanzania Kenya 220600 1.445 0.667 0.778 5 0

Tanzania Kenya 220710 14.532 7.879 6.654 2 0

142

Tanzania Kenya 220720 1.108 0.402 0.706 2 0

Tanzania Kenya 220900 0.141 0.056 0.085 5 0

Tanzania Kenya 230230 0.191 0.191 0 3 0

Tanzania Kenya 230310 0.048 0.013 0.035 3 0

Tanzania Kenya 230330 7.143 7.143 0 3 0

Tanzania Kenya 230500 0.592 0.592 0 3 0

Tanzania Kenya 230910 0.719 0.209 0.51 5 0

Tanzania Kenya 230990 13.421 6.743 6.677 2.33 0


Tanzania Kenya 240220 979.277 963.981 15.296 25 0

Tanzania Kenya 250100 23.077 19.928 3.149 5 0





















Tanzania Kenya 252310 0.264 0.194 0.07 2 0

Tanzania Kenya 252321 0.994 0.276 0.718 25 0

Tanzania Kenya 252329 16.999 6.89 10.109 25 0






Tanzania Kenya 271000 354.265 193.907 160.358 0.33 0










143


















































144


















































145




















Tanzania Kenya 300190 0.143 0.092 0.051 2 0

Tanzania Kenya 300210 0.191 0.131 0.06 2 0


Tanzania Kenya 300290 0.449 0.178 0.271 2 0

Tanzania Kenya 300310 1.054 0.888 0.167 2 0

Tanzania Kenya 300320 2.814 1.31 1.504 2 0

Tanzania Kenya 300339 0.38 0.152 0.228 2 0

Tanzania Kenya 300390 3.622 1.409 2.212 2 0

Tanzania Kenya 300410 1.654 0.707 0.948 2 0

Tanzania Kenya 300420 59.982 27.306 32.675 2 0

Tanzania Kenya 300432 0.081 0.03 0.051 2 0

Tanzania Kenya 300439 53.594 25.583 28.011 2 0

Tanzania Kenya 300440 0.2 0.096 0.104 2 0

Tanzania Kenya 300450 0.036 0.02 0.017 2 0

Tanzania Kenya 300490 124.902 42.982 81.92 2 0

Tanzania Kenya 300510 0.452 0.177 0.276 2 0

Tanzania Kenya 300590 5.257 2.289 2.968 2 0

Tanzania Kenya 300610 0.077 0.029 0.048 2 0

Tanzania Kenya 300620 0.496 0.198 0.298 2 0

Tanzania Kenya 300650 0.048 0.019 0.029 2 0

Tanzania Kenya 300660 0.308 0.127 0.181 2 0










146





























Tanzania Kenya 320810 0.173 0.061 0.112 5 0

Tanzania Kenya 320820 0.191 0.024 0.167 5 0

Tanzania Kenya 320890 4.555 2.783 1.772 3.5 0

Tanzania Kenya 320910 0.235 0.118 0.117 5 0

Tanzania Kenya 320990 9.834 4.882 4.952 5 0

Tanzania Kenya 321000 2.042 1.024 1.018 3.5 0

Tanzania Kenya 321290 0.317 0.102 0.215 5 0

Tanzania Kenya 321310 0.061 0.026 0.035 5 0

Tanzania Kenya 321410 1.007 0.503 0.503 5 0

Tanzania Kenya 321490 4.3 3.124 1.175 5 0

Tanzania Kenya 321511 1.222 0.503 0.718 2 0

Tanzania Kenya 321519 5.014 0.77 4.244 2 0

Tanzania Kenya 321590 0.691 0.169 0.523 5 0





Tanzania Kenya 330210 0.187 0.076 0.111 2 0

Tanzania Kenya 330290 0.524 0.234 0.29 2 0

Tanzania Kenya 330300 1.306 0.437 0.869 5 0

Tanzania Kenya 330410 0.056 0.017 0.039 5 0

147

Tanzania Kenya 330491 0.205 0.048 0.158 5 0

Tanzania Kenya 330499 4.846 0.716 4.13 5 0

Tanzania Kenya 330510 0.383 0.147 0.236 5 0

Tanzania Kenya 330520 1.617 0.76 0.858 5 0

Tanzania Kenya 330530 0.106 0.04 0.067 5 0

Tanzania Kenya 330590 23.988 7.429 16.559 5 0

Tanzania Kenya 330610 16.264 7.573 8.691 5 0

Tanzania Kenya 330620 0.063 0.028 0.035 5 0

Tanzania Kenya 330690 19.754 14.781 4.973 5 0

Tanzania Kenya 330730 0.409 0.299 0.111 5 0

Tanzania Kenya 330790 0.215 0.097 0.119 5 0

Tanzania Kenya 340111 6.173 2.457 3.716 5 0

Tanzania Kenya 340119 10.918 6.886 4.032 5 0

Tanzania Kenya 340120 42.871 33.175 9.696 5 0

Tanzania Kenya 340211 18.924 15.318 3.606 3 0

Tanzania Kenya 340212 1.097 0.505 0.592 3 0

Tanzania Kenya 340213 0.859 0.445 0.413 2 0

Tanzania Kenya 340219 1.525 0.7 0.825 3 0

Tanzania Kenya 340220 2.521 0.868 1.653 3 0

Tanzania Kenya 340290 5.254 1.985 3.269 3 0

Tanzania Kenya 340420 0.71 0.535 0.175 3 0

Tanzania Kenya 340510 1.658 0.749 0.909 5 0

Tanzania Kenya 340520 0.337 0.167 0.17 5 0

Tanzania Kenya 340540 2.208 1.801 0.407 5 0

Tanzania Kenya 340590 0.64 0.206 0.434 5 0

Tanzania Kenya 340700 1.593 0.749 0.843 5 0

Tanzania Kenya 350190 0.578 0.238 0.34 3 0

Tanzania Kenya 350300 0.343 0.161 0.181 3 0

Tanzania Kenya 350510 2.036 1.113 0.923 3 0

Tanzania Kenya 350520 8.374 5.699 2.674 3 0

Tanzania Kenya 350610 0.34 0.139 0.201 3 0

Tanzania Kenya 350691 4.386 4.286 0.1 3 0

Tanzania Kenya 350699 0.272 0.098 0.174 3 0

Tanzania Kenya 350790 0.476 0.02 0.456 3 0

Tanzania Kenya 360490 0.327 0.168 0.159 5 0

Tanzania Kenya 360690 0.477 0.296 0.182 5 0

Tanzania Kenya 370199 0.23 0.099 0.131 3 0

Tanzania Kenya 370244 0.033 0.009 0.024 3 0

Tanzania Kenya 370510 0.471 0.338 0.133 3 0

Tanzania Kenya 370710 0.872 0.347 0.525 3 0

Tanzania Kenya 370790 0.065 0.022 0.043 3 0









148

Tanzania Kenya 380810 17.61 7.404 10.206 1 0









Tanzania Kenya 381010 0.039 0.016 0.023 3 0

Tanzania Kenya 381090 0.121 0.05 0.071 3 0

Tanzania Kenya 381111 0.049 0.023 0.026 3 0

Tanzania Kenya 381121 0.262 0.117 0.146 2 0

Tanzania Kenya 381190 0.285 0.089 0.196 2 0

Tanzania Kenya 381300 0.199 0.088 0.111 3 0

Tanzania Kenya 381400 2.655 1.214 1.441 3 0

Tanzania Kenya 381600 0.214 0.107 0.107 3 0

Tanzania Kenya 381900 2.648 1.115 1.533 3 0

Tanzania Kenya 382000 3.325 1.93 1.395 3 0

Tanzania Kenya 382100 0.081 0.036 0.045 3 0

Tanzania Kenya 382200 2.229 0.921 1.308 3 0





Tanzania Kenya 382410 0.488 0.297 0.191 3 0

Tanzania Kenya 382479 0.078 0.078 0 3 0

Tanzania Kenya 382490 9.08 4.055 5.026 3 0






















149






Tanzania Kenya 391710 0.146 0.04 0.105 5 0

Tanzania Kenya 391723 7.053 3.724 3.329 5 0

Tanzania Kenya 391729 2.138 0.937 1.201 5 0

Tanzania Kenya 391731 1.445 0.626 0.819 5 0

Tanzania Kenya 391733 0.793 0.148 0.645 5 0

Tanzania Kenya 391739 0.938 0.357 0.581 5 0

Tanzania Kenya 391740 0.796 0.336 0.46 5 0

Tanzania Kenya 391810 0.136 0.067 0.069 5 0

Tanzania Kenya 391890 0.981 0.429 0.553 5 0

Tanzania Kenya 391910 9.079 3.419 5.659 5 0

Tanzania Kenya 391990 4.09 0.6 3.491 5 0

Tanzania Kenya 392010 6.624 3.275 3.349 2 0

Tanzania Kenya 392020 6.897 1.99 4.907 2 0

Tanzania Kenya 392042 1.19 0.318 0.872 5 0

Tanzania Kenya 392059 0.677 0.339 0.337 5 0

Tanzania Kenya 392062 7.186 5.512 1.674 5 0

Tanzania Kenya 392063 0.057 0.057 0 5 0

Tanzania Kenya 392069 2.503 1.577 0.926 5 0

Tanzania Kenya 392092 0.053 0.053 0 5 0

Tanzania Kenya 392099 5.045 2.07 2.975 5 0

Tanzania Kenya 392111 0.519 0.2 0.319 5 0

Tanzania Kenya 392112 1.344 0.772 0.572 5 0

Tanzania Kenya 392119 0.186 0.074 0.113 5 0

Tanzania Kenya 392190 2.35 0.993 1.357 5 0

Tanzania Kenya 392210 0.123 0.058 0.065 5 0

Tanzania Kenya 392290 1.008 0.387 0.621 5 0

Tanzania Kenya 392310 166.296 115.066 51.23 5 0

Tanzania Kenya 392321 15.849 7.599 8.249 5 0

Tanzania Kenya 392329 28.761 11.327 17.434 5 0

Tanzania Kenya 392330 38.086 26.927 11.159 5 0

Tanzania Kenya 392340 1.894 0.875 1.019 5 0

Tanzania Kenya 392350 0.659 0.238 0.421 5 0

Tanzania Kenya 392390 58.638 29.966 28.672 5 0

Tanzania Kenya 392410 15.872 7.438 8.434 5 0

Tanzania Kenya 392490 6.139 2.453 3.686 5 0

Tanzania Kenya 392510 3.404 1.957 1.448 2.5 0

Tanzania Kenya 392520 1.024 0.671 0.353 5 0

Tanzania Kenya 392530 0.253 0.116 0.137 5 0

Tanzania Kenya 392590 0.443 0.168 0.275 5 0

Tanzania Kenya 392610 0.782 0.312 0.47 5 0

Tanzania Kenya 392620 3.404 2.734 0.67 5 0

Tanzania Kenya 392640 0.075 0.037 0.037 5 0

Tanzania Kenya 392690 6.885 3.804 3.081 5 0


150





Tanzania Kenya 400819 0.16 0.069 0.091 3 0

Tanzania Kenya 400829 0.782 0.376 0.407 3 0

Tanzania Kenya 400910 0.09 0.039 0.05 3 0

Tanzania Kenya 400930 0.054 0.012 0.042 3 0

Tanzania Kenya 400950 0.127 0.058 0.069 3 0

Tanzania Kenya 401011 0.051 0.02 0.031 3 0

Tanzania Kenya 401019 0.602 0.237 0.365 3 0

Tanzania Kenya 401021 0.107 0.054 0.053 3 0

Tanzania Kenya 401110 34.613 2.1 32.512 5 0

Tanzania Kenya 401120 20.396 7.617 12.778 3 0

Tanzania Kenya 401150 2.831 1.208 1.623 5 0


Tanzania Kenya 401199 0.552 0.213 0.339 5 0

Tanzania Kenya 401210 0.06 0.022 0.038 5 0

Tanzania Kenya 401220 0.101 0.028 0.073 5 0

Tanzania Kenya 401290 0.298 0.132 0.166 5 0

Tanzania Kenya 401310 15.091 7.467 7.624 5 0

Tanzania Kenya 401390 2.597 1.185 1.411 5 0


Tanzania Kenya 401691 0.081 0.025 0.056 5 0

Tanzania Kenya 401693 0.547 0.138 0.409 5 0

Tanzania Kenya 401699 0.625 0.174 0.451 5 0

Tanzania Kenya 401700 0.099 0.038 0.061 3 0






Tanzania Kenya 420211 0.275 0.109 0.166 5 0

Tanzania Kenya 420212 0.872 0.347 0.525 5 0

Tanzania Kenya 420219 1.015 0.436 0.579 5 0

Tanzania Kenya 420221 1.193 0.984 0.209 5 0

Tanzania Kenya 420222 0.138 0.031 0.107 5 0

Tanzania Kenya 420229 0.76 0.212 0.548 5 0

Tanzania Kenya 420231 0.185 0.065 0.121 5 0

Tanzania Kenya 420239 0.243 0.129 0.113 5 0

Tanzania Kenya 420292 0.204 0.078 0.126 5 0

Tanzania Kenya 420299 0.148 0.043 0.105 5 0

Tanzania Kenya 420330 0.045 0.005 0.041 5 0

Tanzania Kenya 420340 0.552 0.283 0.269 5 0

Tanzania Kenya 430390 0.145 0.145 0 5 0

Tanzania Kenya 440410 0.25 0.244 0.006 3 0

Tanzania Kenya 440890 0.111 0.069 0.041 3 0

Tanzania Kenya 440910 1.337 1.162 0.175 5 0

Tanzania Kenya 441011 1.566 1.184 0.382 5 0

151

Tanzania Kenya 441019 9.426 5.296 4.13 5 0

Tanzania Kenya 441090 1.375 0.697 0.678 5 0

Tanzania Kenya 441119 3.034 1.545 1.489 5 0

Tanzania Kenya 441129 0.322 0.058 0.264 5 0

Tanzania Kenya 441199 0.98 0.433 0.546 5 0

Tanzania Kenya 441213 0.128 0.052 0.076 5 0

Tanzania Kenya 441219 15.166 6.955 8.211 5 0

Tanzania Kenya 441223 0.308 0.101 0.207 5 0

Tanzania Kenya 441229 0.994 0.616 0.378 5 0

Tanzania Kenya 441299 19.486 14.72 4.766 5 0

Tanzania Kenya 441300 0.613 0.456 0.157 5 0

Tanzania Kenya 441510 1.021 0.361 0.66 5 0

Tanzania Kenya 441520 0.134 0.048 0.085 5 0

Tanzania Kenya 441600 0.422 0.27 0.152 5 0

Tanzania Kenya 441810 2.692 2.566 0.127 5 0

Tanzania Kenya 441820 20.734 16.148 4.585 5 0

Tanzania Kenya 441890 1.985 1.354 0.631 5 0

Tanzania Kenya 442010 0.131 0.058 0.072 5 0

Tanzania Kenya 442190 0.145 0.036 0.109 2 0

Tanzania Kenya 460199 0.214 0.108 0.106 5 0

Tanzania Kenya 460290 0.693 0.558 0.136 5 0




Tanzania Kenya 480100 0.933 0.42 0.513 2 0

Tanzania Kenya 480300 5.902 2.344 3.558 5 0

Tanzania Kenya 480411 5.774 3.193 2.581 2 0

Tanzania Kenya 480419 1.475 0.556 0.919 2 0

Tanzania Kenya 480421 2.438 1.934 0.504 2 0

Tanzania Kenya 480429 1.266 0.584 0.682 2 0

Tanzania Kenya 480431 1.59 1.098 0.492 2 0

Tanzania Kenya 480439 3.72 1.707 2.013 2 0

Tanzania Kenya 480441 0.191 0.126 0.066 2 0

Tanzania Kenya 480449 0.217 0.074 0.143 2 0

Tanzania Kenya 480452 0.084 0.058 0.026 2 0

Tanzania Kenya 480459 0.224 0.156 0.068 2 0

Tanzania Kenya 480510 2.906 1.052 1.855 2 0

Tanzania Kenya 480529 0.207 0.106 0.101 2 0

Tanzania Kenya 480620 0.047 0.026 0.02 3 0

Tanzania Kenya 480810 0.383 0.27 0.112 3 0

Tanzania Kenya 480820 0.026 0.012 0.014 3 0

Tanzania Kenya 480830 0.075 0.067 0.008 3 0

Tanzania Kenya 480890 2.219 1.528 0.691 2 0

Tanzania Kenya 480910 2.079 1.091 0.987 5 0

Tanzania Kenya 480990 0.174 0.082 0.092 5 0

Tanzania Kenya 481011 1.365 0.625 0.739 2 0

Tanzania Kenya 481039 7.916 6.786 1.13 2 0

Tanzania Kenya 481099 0.575 0.197 0.378 2 0

Tanzania Kenya 481121 2.751 1.288 1.463 2 0

152

Tanzania Kenya 481139 0.645 0.165 0.48 2 0

Tanzania Kenya 481140 0.425 0.192 0.233 2 0

Tanzania Kenya 481190 0.728 0.321 0.407 2 0

Tanzania Kenya 481500 1.425 1.274 0.152 5 0

Tanzania Kenya 481610 0.457 0.189 0.268 5 0

Tanzania Kenya 481630 0.226 0.189 0.037 5 0

Tanzania Kenya 481710 0.946 0.476 0.47 5 0

Tanzania Kenya 481730 0.221 0.081 0.14 5 0

Tanzania Kenya 481810 0.916 0.412 0.504 5 0

Tanzania Kenya 481820 1.504 0.851 0.653 5 0

Tanzania Kenya 481840 0.432 0.272 0.161 5 0

Tanzania Kenya 481890 0.248 0.192 0.056 5 0

Tanzania Kenya 481910 122.528 84.862 37.666 3 0

Tanzania Kenya 481920 2.567 1.323 1.244 3 0

Tanzania Kenya 481930 12.289 8.523 3.766 3 0

Tanzania Kenya 481940 3.816 2.386 1.43 3 0

Tanzania Kenya 481950 1.395 0.716 0.679 3 0

Tanzania Kenya 481960 2.708 1.002 1.706 5 0

Tanzania Kenya 482010 2.671 1.087 1.584 5 0

Tanzania Kenya 482020 7.603 3.261 4.342 5 0

Tanzania Kenya 482030 0.654 0.317 0.337 5 0

Tanzania Kenya 482090 0.561 0.229 0.332 5 0

Tanzania Kenya 482110 2.036 0.818 1.218 2 0

Tanzania Kenya 482190 1.404 0.535 0.869 2 0

Tanzania Kenya 482210 0.536 0.241 0.295 5 0

Tanzania Kenya 482290 0.351 0.233 0.118 5 0

Tanzania Kenya 482311 10.284 6.064 4.22 5 0

Tanzania Kenya 482319 2.9 1.529 1.372 5 0

Tanzania Kenya 482340 0.085 0.032 0.053 5 0

Tanzania Kenya 482360 0.084 0.02 0.063 5 0

Tanzania Kenya 482370 0.219 0.024 0.195 5 0

Tanzania Kenya 482390 4.882 2.23 2.652 5 0









Tanzania Kenya 491000 1.363 0.65 0.712 5 0



Tanzania Kenya 500400 0.075 0.075 0 2 0

Tanzania Kenya 520790 0.361 0.24 0.12 2 0

Tanzania Kenya 520829 0.176 0.128 0.048 3 0

Tanzania Kenya 520949 0.202 0.146 0.055 5 0

Tanzania Kenya 521022 0.036 0.036 0 3 0


153


Tanzania Kenya 530919 0.083 0.064 0.019 3 0

Tanzania Kenya 540120 4.226 3.867 0.359 5 0

Tanzania Kenya 540349 0.24 0.091 0.149 2 0

Tanzania Kenya 540500 0.029 0.005 0.024 2 0

Tanzania Kenya 540710 0.08 0.035 0.045 3 0

Tanzania Kenya 540744 0.207 0.088 0.12 5 0

Tanzania Kenya 540822 1.181 1.18 0.001 5 0




Tanzania Kenya 550810 0.096 0.045 0.051 5 0

Tanzania Kenya 550921 0.263 0.127 0.137 2 0

Tanzania Kenya 550922 0.117 0.086 0.031 2 0

Tanzania Kenya 550969 0.373 0.246 0.128 2 0

Tanzania Kenya 551011 0.121 0.076 0.045 2 0

Tanzania Kenya 551030 0.484 0.484 0 2 0

Tanzania Kenya 551110 1.515 1.506 0.009 2 0

Tanzania Kenya 551130 0.199 0.054 0.145 2 0

Tanzania Kenya 551299 0.04 0.018 0.021 3 0

Tanzania Kenya 551311 0.59 0.395 0.196 3 0

Tanzania Kenya 551339 19.189 18.606 0.583 5 0

Tanzania Kenya 551341 0.211 0.145 0.066 5 0

Tanzania Kenya 551413 0.173 0.064 0.109 3 0

Tanzania Kenya 551421 1.242 1.096 0.146 5 0

Tanzania Kenya 551511 5.945 3.671 2.274 5 0

Tanzania Kenya 551599 1.39 0.748 0.641 5 0

Tanzania Kenya 551614 0.686 0.491 0.195 5 0

Tanzania Kenya 551694 0.076 0.038 0.038 5 0

Tanzania Kenya 560110 1.755 0.766 0.989 3 0

Tanzania Kenya 560121 0.058 0.025 0.033 3 0

Tanzania Kenya 560129 0.215 0.084 0.131 3 0

Tanzania Kenya 560410 19.673 19.573 0.1 2 0

Tanzania Kenya 560749 1.979 1.071 0.909 3 0

Tanzania Kenya 560790 0.365 0.145 0.221 3 0

Tanzania Kenya 560819 0.103 0.024 0.08 3 0

Tanzania Kenya 560890 0.069 0.033 0.036 3 0

Tanzania Kenya 570110 0.371 0.188 0.183 5 0

Tanzania Kenya 570190 0.141 0.084 0.057 5 0

Tanzania Kenya 570500 2.677 1.603 1.075 5 0

Tanzania Kenya 580610 0.074 0.053 0.022 5 0

Tanzania Kenya 580631 0.335 0.222 0.113 5 0

Tanzania Kenya 580632 0.131 0.039 0.092 5 0

Tanzania Kenya 580639 0.061 0.022 0.039 5 0

Tanzania Kenya 580640 0.323 0.128 0.195 5 0

Tanzania Kenya 580710 0.482 0.342 0.14 5 0

Tanzania Kenya 580790 0.128 0.041 0.087 5 0

Tanzania Kenya 580810 0.066 0.037 0.029 5 0

Tanzania Kenya 580890 0.33 0.261 0.069 5 0

154

Tanzania Kenya 590110 0.126 0.04 0.086 2 0

Tanzania Kenya 590190 0.036 0.014 0.022 2 0

Tanzania Kenya 590210 1.601 0.657 0.945 2 0

Tanzania Kenya 590320 0.837 0.461 0.377 5 0

Tanzania Kenya 590610 0.33 0.135 0.196 3 0

Tanzania Kenya 590699 0.054 0.022 0.032 3 0

Tanzania Kenya 590700 0.139 0.072 0.067 3 0

Tanzania Kenya 590900 0.112 0.046 0.066 3 0

Tanzania Kenya 591000 0.236 0.098 0.138 5 0

Tanzania Kenya 591132 0.059 0.022 0.037 2 0

Tanzania Kenya 600199 0.061 0.032 0.03 3 0

Tanzania Kenya 610120 0.076 0.02 0.057 5 0

Tanzania Kenya 610290 0.253 0.112 0.141 5 0

Tanzania Kenya 610319 0.579 0.28 0.3 5 0

Tanzania Kenya 610322 0.154 0.014 0.14 5 0

Tanzania Kenya 610342 0.399 0.114 0.285 5 0

Tanzania Kenya 610349 8.176 7.156 1.02 5 0

Tanzania Kenya 610469 0.793 0.4 0.393 5 0

Tanzania Kenya 610510 0.337 0.104 0.233 5 0

Tanzania Kenya 610590 1.881 0.608 1.273 5 0

Tanzania Kenya 610719 0.246 0.194 0.052 5 0

Tanzania Kenya 610819 0.267 0.254 0.013 5 0

Tanzania Kenya 610910 3.016 1.026 1.99 5 0

Tanzania Kenya 610990 4.677 1.968 2.709 5 0

Tanzania Kenya 611090 0.271 0.209 0.062 5 0

Tanzania Kenya 611219 0.287 0.204 0.083 5 0

Tanzania Kenya 611490 0.08 0.014 0.066 5 0

Tanzania Kenya 611593 0.21 0.103 0.107 5 0

Tanzania Kenya 611599 0.157 0.042 0.115 5 0

Tanzania Kenya 611610 0.22 0.122 0.097 5 0

Tanzania Kenya 620192 0.09 0.062 0.028 5 0

Tanzania Kenya 620199 0.097 0.06 0.037 5 0

Tanzania Kenya 620312 0.613 0.498 0.115 5 0

Tanzania Kenya 620322 1.612 1.51 0.103 5 0

Tanzania Kenya 620413 0.54 0.344 0.196 5 0

Tanzania Kenya 620443 0.063 0.032 0.032 5 0

Tanzania Kenya 620520 0.321 0.252 0.07 5 0

Tanzania Kenya 620530 0.755 0.031 0.724 5 0

Tanzania Kenya 620590 1.347 0.566 0.781 5 0

Tanzania Kenya 620719 0.901 0.32 0.581 5 0

Tanzania Kenya 620729 0.092 0.031 0.061 5 0

Tanzania Kenya 620899 0.498 0.219 0.279 5 0

Tanzania Kenya 621010 0.814 0.29 0.524 5 0

Tanzania Kenya 621040 0.767 0.535 0.232 5 0

Tanzania Kenya 621142 0.106 0.045 0.061 5 0

Tanzania Kenya 621290 0.118 0.023 0.095 5 0

Tanzania Kenya 621430 0.357 0.2 0.157 5 0

Tanzania Kenya 621490 0.068 0.035 0.034 5 0

Tanzania Kenya 621790 0.2 0.069 0.131 5 0

155

Tanzania Kenya 630110 0.089 0.012 0.077 5 0

Tanzania Kenya 630120 16.354 14.239 2.115 5 0

Tanzania Kenya 630130 0.41 0.122 0.287 5 0

Tanzania Kenya 630140 21.479 19.401 2.078 5 0

Tanzania Kenya 630190 2.25 0.934 1.316 5 0

Tanzania Kenya 630221 0.187 0.064 0.123 5 0

Tanzania Kenya 630229 0.32 0.218 0.102 5 0

Tanzania Kenya 630231 0.113 0.056 0.057 5 0

Tanzania Kenya 630253 0.146 0.065 0.081 5 0

Tanzania Kenya 630260 0.094 0.006 0.088 5 0

Tanzania Kenya 630291 0.219 0.067 0.153 5 0

Tanzania Kenya 630311 0.759 0.125 0.633 5 0

Tanzania Kenya 630319 0.619 0.229 0.39 5 0

Tanzania Kenya 630391 0.257 0.111 0.146 5 0

Tanzania Kenya 630399 1.82 0.751 1.07 5 0

Tanzania Kenya 630419 0.634 0.35 0.284 5 0

Tanzania Kenya 630491 2.94 1.535 1.406 2.5 0

Tanzania Kenya 630510 0.279 0.116 0.163 3 0

Tanzania Kenya 630533 0.579 0.246 0.334 3 0

Tanzania Kenya 630539 0.759 0.235 0.524 3 0

Tanzania Kenya 630590 0.379 0.12 0.259 3 0

Tanzania Kenya 630619 1.53 0.85 0.68 5 0

Tanzania Kenya 630621 0.152 0.083 0.069 5 0

Tanzania Kenya 630622 0.137 0.063 0.074 5 0

Tanzania Kenya 630629 1.652 1.032 0.62 5 0

Tanzania Kenya 630699 0.408 0.195 0.213 5 0

Tanzania Kenya 630720 0.118 0.044 0.074 5 0

Tanzania Kenya 630790 0.089 0.036 0.054 5 0

Tanzania Kenya 630900 5.359 2.267 3.092 5 0

Tanzania Kenya 640110 0.598 0.19 0.409 5 0

Tanzania Kenya 640191 0.14 0.03 0.11 5 0

Tanzania Kenya 640192 3.439 2.222 1.217 5 0

Tanzania Kenya 640199 0.531 0.051 0.479 5 0

Tanzania Kenya 640212 0.064 0.027 0.037 5 0

Tanzania Kenya 640219 1.574 0.711 0.863 5 0

Tanzania Kenya 640220 18.532 12.804 5.728 5 0

Tanzania Kenya 640291 0.393 0.176 0.217 5 0

Tanzania Kenya 640299 11.477 4.914 6.563 5 0

Tanzania Kenya 640319 1.614 0.713 0.901 5 0

Tanzania Kenya 640320 0.145 0.095 0.05 5 0

Tanzania Kenya 640399 6.207 2.481 3.726 5 0

Tanzania Kenya 640411 1.088 0.325 0.763 5 0

Tanzania Kenya 640419 1.597 0.439 1.158 5 0

Tanzania Kenya 640420 0.628 0.335 0.293 5 0

Tanzania Kenya 640510 0.137 0.066 0.072 5 0

Tanzania Kenya 640520 1.399 0.741 0.658 5 0

Tanzania Kenya 640590 0.584 0.208 0.376 5 0

Tanzania Kenya 640610 2.432 1.882 0.55 2 0

Tanzania Kenya 640620 10.037 9.867 0.17 2 0

156

Tanzania Kenya 640691 2.128 2.107 0.02 2 0

Tanzania Kenya 640699 1.168 0.758 0.41 2 0

Tanzania Kenya 650300 0.434 0.31 0.124 5 0

Tanzania Kenya 650400 0.176 0.071 0.105 5 0

Tanzania Kenya 650590 1.146 0.429 0.717 5 0

Tanzania Kenya 650700 0.362 0.167 0.195 5 0

Tanzania Kenya 660110 0.134 0.059 0.075 5 0

Tanzania Kenya 660191 0.195 0.105 0.09 5 0

Tanzania Kenya 660199 0.26 0.133 0.127 5 0

Tanzania Kenya 670210 0.14 0.069 0.071 5 0

Tanzania Kenya 670419 8.067 7.903 0.165 5 0

Tanzania Kenya 670490 0.063 0.032 0.032 5 0

Tanzania Kenya 680210 0.851 0.31 0.541 5 0

Tanzania Kenya 680221 2.315 1.535 0.781 5 0

Tanzania Kenya 680223 0.289 0.154 0.136 5 0

Tanzania Kenya 680229 0.865 0.514 0.351 5 0

Tanzania Kenya 680293 8.92 8.647 0.273 5 0

Tanzania Kenya 680299 0.134 0.041 0.093 5 0

Tanzania Kenya 680410 0.459 0.253 0.205 5 0

Tanzania Kenya 680422 0.991 0.364 0.626 5 0

Tanzania Kenya 680430 0.066 0.03 0.035 5 0

Tanzania Kenya 680530 0.172 0.07 0.102 5 0

Tanzania Kenya 680610 0.272 0.127 0.145 5 0

Tanzania Kenya 680690 1.164 0.618 0.546 5 0

Tanzania Kenya 680710 0.179 0.056 0.123 5 0

Tanzania Kenya 680800 0.431 0.126 0.306 5 0

Tanzania Kenya 681011 0.615 0.392 0.223 5 0

Tanzania Kenya 681019 0.135 0.056 0.079 5 0

Tanzania Kenya 681099 0.64 0.181 0.459 5 0

Tanzania Kenya 681110 1.437 0.513 0.925 5 0

Tanzania Kenya 681190 0.318 0.094 0.225 5 0

Tanzania Kenya 681290 0.528 0.206 0.322 5 0

Tanzania Kenya 681310 0.306 0.122 0.184 5 0

Tanzania Kenya 690100 0.977 0.569 0.408 3 0

Tanzania Kenya 690210 0.322 0.063 0.259 3 0

Tanzania Kenya 690290 0.791 0.29 0.5 3 0

Tanzania Kenya 690490 33.543 28.3 5.243 5 0

Tanzania Kenya 690510 1.317 0.843 0.474 5 0

Tanzania Kenya 690590 2.236 1.148 1.088 5 0

Tanzania Kenya 690790 0.493 0.276 0.217 5 0

Tanzania Kenya 690810 0.831 0.459 0.372 5 0

Tanzania Kenya 690890 2.314 1.044 1.271 5 0

Tanzania Kenya 691010 2.236 0.927 1.31 5 0

Tanzania Kenya 691090 0.06 0.026 0.034 5 0

Tanzania Kenya 691110 1.514 0.744 0.77 5 0

Tanzania Kenya 691190 0.99 0.5 0.49 5 0

Tanzania Kenya 691200 2.041 0.933 1.108 5 0

Tanzania Kenya 691390 0.34 0.137 0.203 5 0

Tanzania Kenya 691410 0.095 0.047 0.048 5 0

157


Tanzania Kenya 700220 0.263 0.21 0.053 3 0

Tanzania Kenya 700319 0.096 0.09 0.006 3 0

Tanzania Kenya 700330 0.086 0.05 0.036 3 0

Tanzania Kenya 700420 0.118 0.102 0.016 3 0

Tanzania Kenya 700529 0.247 0.115 0.132 3 0

Tanzania Kenya 700711 2.36 0.346 2.014 5 0

Tanzania Kenya 700719 0.809 0.543 0.266 5 0

Tanzania Kenya 700721 11.013 6.567 4.446 5 0

Tanzania Kenya 700729 0.665 0.315 0.35 5 0

Tanzania Kenya 700991 0.297 0.146 0.151 5 0

Tanzania Kenya 700992 0.271 0.096 0.175 5 0

Tanzania Kenya 701010 0.321 0.117 0.204 3 0

Tanzania Kenya 701092 21.265 5.987 15.278 3 0

Tanzania Kenya 701110 0.163 0.076 0.088 5 0

Tanzania Kenya 701190 0.16 0.009 0.151 5 0

Tanzania Kenya 701200 0.146 0.057 0.088 5 0

Tanzania Kenya 701310 0.681 0.251 0.43 5 0

Tanzania Kenya 701329 1.054 0.469 0.585 5 0

Tanzania Kenya 701339 0.189 0.078 0.111 5 0

Tanzania Kenya 701391 2.534 2.203 0.331 5 0

Tanzania Kenya 701399 46.957 43.772 3.185 5 0

Tanzania Kenya 701610 0.534 0.253 0.28 3 0

Tanzania Kenya 701690 0.385 0.248 0.137 3 0




Tanzania Kenya 701919 0.227 0.084 0.143 3 0

Tanzania Kenya 701931 0.547 0.281 0.266 3 0

Tanzania Kenya 701932 0.68 0.68 0 3 0

Tanzania Kenya 701939 0.363 0.185 0.178 3 0

Tanzania Kenya 701990 0.092 0.003 0.089 3 0

Tanzania Kenya 702000 0.095 0.038 0.058 3 0








Tanzania Kenya 720916 31.418 30.828 0.59 2 0

Tanzania Kenya 720917 1.136 0.072 1.064 2 0

Tanzania Kenya 720918 29.23 18.291 10.939 2 0

Tanzania Kenya 720926 0.382 0.232 0.149 2 0

Tanzania Kenya 720927 0.214 0.115 0.099 2 0

Tanzania Kenya 720990 2.535 1.589 0.946 2 0

Tanzania Kenya 721012 10.905 5.171 5.734 2 0

Tanzania Kenya 721020 1.818 1.695 0.124 5 0

Tanzania Kenya 721030 0.798 0.786 0.012 5 0

158

Tanzania Kenya 721041 4.984 2.788 2.197 5 0

Tanzania Kenya 721049 0.833 0.351 0.482 5 0

Tanzania Kenya 721050 15.369 6.995 8.374 2 0

Tanzania Kenya 721061 70.667 66.886 3.781 5 0

Tanzania Kenya 721070 1.333 0.808 0.525 5 0

Tanzania Kenya 721090 3.918 3.117 0.801 5 0

Tanzania Kenya 721119 1.59 1.17 0.421 2 0

Tanzania Kenya 721129 0.7 0.414 0.286 3 0

Tanzania Kenya 721190 0.331 0.142 0.188 3 0

Tanzania Kenya 721210 0.085 0.024 0.061 3 0

Tanzania Kenya 721220 0.564 0.564 0 3 0

Tanzania Kenya 721260 0.049 0.012 0.037 3 0

Tanzania Kenya 721320 0.35 0.143 0.207 5 0

Tanzania Kenya 721391 0.115 0.048 0.067 3.5 0

Tanzania Kenya 721420 17.729 11.662 6.067 5 0

Tanzania Kenya 721491 0.06 0.024 0.036 5 0

Tanzania Kenya 721499 4.106 1.979 2.127 5 0

Tanzania Kenya 721590 3.687 1.681 2.006 3 0

Tanzania Kenya 721610 2.386 2.164 0.221 3 0

Tanzania Kenya 721621 0.202 0.028 0.174 3 0

Tanzania Kenya 721631 14.294 9.521 4.773 3 0

Tanzania Kenya 721632 0.642 0.189 0.453 3 0

Tanzania Kenya 721633 1.456 0.46 0.997 3 0

Tanzania Kenya 721640 0.244 0.118 0.127 3 0

Tanzania Kenya 721650 9.316 6.328 2.988 3 0

Tanzania Kenya 721669 0.665 0.396 0.269 3 0

Tanzania Kenya 721699 0.133 0.062 0.071 3 0

Tanzania Kenya 721710 0.298 0.108 0.19 3 0

Tanzania Kenya 721720 1.041 0.416 0.625 2 0

Tanzania Kenya 721730 0.048 0.021 0.027 3 0

Tanzania Kenya 721790 0.492 0.208 0.284 2 0

Tanzania Kenya 721911 0.073 0.045 0.028 3 0

Tanzania Kenya 721931 0.074 0.074 0 3 0

Tanzania Kenya 721932 0.046 0.046 0 3 0

Tanzania Kenya 721990 14.416 10.662 3.754 3 0

Tanzania Kenya 722020 1.857 1.828 0.029 3 0

Tanzania Kenya 722100 0.164 0.064 0.1 3 0

Tanzania Kenya 722211 0.095 0.042 0.054 3 0

Tanzania Kenya 722219 0.187 0.081 0.106 3 0

Tanzania Kenya 722230 0.043 0.02 0.022 3 0

Tanzania Kenya 722240 0.35 0.14 0.211 3 0

Tanzania Kenya 722790 0.096 0.063 0.033 3 0

Tanzania Kenya 722860 0.366 0.152 0.214 3 0

Tanzania Kenya 722870 0.71 0.509 0.201 3 0

Tanzania Kenya 722880 0.153 0.062 0.09 3 0

Tanzania Kenya 722910 0.11 0.051 0.059 3 0

Tanzania Kenya 722990 0.657 0.282 0.375 3 0

Tanzania Kenya 730110 0.263 0.119 0.144 5 0

Tanzania Kenya 730120 0.12 0.056 0.064 5 0

159


Tanzania Kenya 730300 10.973 7.354 3.619 5 0

Tanzania Kenya 730410 0.079 0.026 0.054 5 0

Tanzania Kenya 730429 1.072 0.494 0.578 5 0

Tanzania Kenya 730490 0.22 0.133 0.087 5 0

Tanzania Kenya 730519 1.835 1.208 0.628 5 0

Tanzania Kenya 730531 0.432 0.094 0.338 5 0

Tanzania Kenya 730590 1.734 0.482 1.252 5 0

Tanzania Kenya 730610 0.508 0.376 0.132 5 0

Tanzania Kenya 730630 6.649 3.081 3.568 5 0

Tanzania Kenya 730640 0.2 0.165 0.035 5 0

Tanzania Kenya 730650 1.264 1.099 0.165 5 0

Tanzania Kenya 730660 9.243 6.526 2.717 5 0

Tanzania Kenya 730690 5.385 1.897 3.488 5 0

Tanzania Kenya 730719 16.978 6.534 10.444 5 0

Tanzania Kenya 730722 0.092 0.025 0.067 5 0

Tanzania Kenya 730729 4.11 1.781 2.329 5 0

Tanzania Kenya 730791 0.137 0.053 0.083 5 0

Tanzania Kenya 730792 0.085 0.032 0.053 5 0

Tanzania Kenya 730799 19.145 10.452 8.693 5 0


Tanzania Kenya 730830 0.685 0.335 0.35 5 0



Tanzania Kenya 730900 29.377 15.014 14.364 2.5 0

Tanzania Kenya 731010 2.706 1.723 0.982 5 0

Tanzania Kenya 731021 0.056 0.055 0 5 0

Tanzania Kenya 731029 3.296 1.357 1.939 2.5 0

Tanzania Kenya 731100 1.575 0.77 0.805 5 0

Tanzania Kenya 731210 0.771 0.329 0.442 5 0

Tanzania Kenya 731290 1.098 0.439 0.659 5 0

Tanzania Kenya 731300 0.316 0.194 0.123 5 0

Tanzania Kenya 731420 1.189 0.783 0.406 5 0

Tanzania Kenya 731439 0.445 0.209 0.237 5 0

Tanzania Kenya 731441 0.176 0.081 0.095 5 0

Tanzania Kenya 731511 3.456 1.855 1.6 2 0

Tanzania Kenya 731512 0.909 0.36 0.549 2 0

Tanzania Kenya 731519 0.096 0.041 0.055 2 0

Tanzania Kenya 731589 0.205 0.051 0.154 2 0

Tanzania Kenya 731590 1.117 0.521 0.596 2 0

Tanzania Kenya 731700 0.997 0.433 0.564 5 0

Tanzania Kenya 731813 0.087 0.036 0.051 5 0

Tanzania Kenya 731815 3.487 1 2.487 5 0

Tanzania Kenya 731816 0.136 0.057 0.079 5 0

Tanzania Kenya 731819 0.125 0.049 0.076 5 0

Tanzania Kenya 731822 0.328 0.138 0.19 5 0

Tanzania Kenya 731930 13.95 10.902 3.048 5 0

Tanzania Kenya 732010 1.252 0.481 0.771 5 0

Tanzania Kenya 732090 0.69 0.337 0.353 5 0

160

Tanzania Kenya 732111 1.134 0.622 0.512 5 0

Tanzania Kenya 732112 3.51 1.435 2.075 5 0

Tanzania Kenya 732113 0.098 0.027 0.072 5 0

Tanzania Kenya 732190 0.283 0.139 0.145 5 0

Tanzania Kenya 732310 0.37 0.215 0.154 5 0

Tanzania Kenya 732392 0.72 0.477 0.243 5 0

Tanzania Kenya 732393 0.539 0.21 0.329 5 0

Tanzania Kenya 732394 0.086 0.036 0.051 5 0

Tanzania Kenya 732399 1.901 0.812 1.089 5 0

Tanzania Kenya 732410 0.447 0.183 0.265 5 0

Tanzania Kenya 732490 0.302 0.128 0.174 5 0

Tanzania Kenya 732599 6.407 3.252 3.155 5 0

Tanzania Kenya 732611 2.863 1.044 1.819 2 0

Tanzania Kenya 732620 1.015 0.441 0.575 5 0

Tanzania Kenya 732690 0.578 0.198 0.38 5 0

Tanzania Kenya 740319 0.035 0.034 0.001 3 0

Tanzania Kenya 740322 0.223 0.174 0.049 3 0

Tanzania Kenya 740729 0.216 0.098 0.118 2 0


Tanzania Kenya 740819 1.139 0.48 0.659 2 0

Tanzania Kenya 740829 0.029 0.007 0.022 3 0

Tanzania Kenya 740929 0.4 0.195 0.205 2 0

Tanzania Kenya 740939 0.074 0.025 0.049 2 0

Tanzania Kenya 741220 0.07 0.021 0.049 5 0

Tanzania Kenya 741300 1.17 0.606 0.564 5 0

Tanzania Kenya 741539 0.159 0.068 0.091 5 0

Tanzania Kenya 741819 30.558 27.855 2.703 5 0

Tanzania Kenya 741910 0.059 0.039 0.021 2 0

Tanzania Kenya 741999 0.061 0.027 0.034 3 0

Tanzania Kenya 750720 1.477 1.346 0.131 3 0



Tanzania Kenya 760410 10.824 4.816 6.008 2 0

Tanzania Kenya 760421 0.328 0.194 0.134 3 0

Tanzania Kenya 760429 0.676 0.182 0.494 3 0

Tanzania Kenya 760519 0.585 0.443 0.141 3 0

Tanzania Kenya 760529 0.329 0.177 0.151 3 0

Tanzania Kenya 760611 21.349 14.593 6.756 3 0

Tanzania Kenya 760612 0.242 0.11 0.132 3 0

Tanzania Kenya 760691 3.738 2.019 1.72 3 0

Tanzania Kenya 760692 50.083 41.513 8.57 2.5 0

Tanzania Kenya 760711 0.74 0.397 0.342 5 0

Tanzania Kenya 760719 0.432 0.183 0.249 3 0

Tanzania Kenya 760720 0.925 0.423 0.502 2 0

Tanzania Kenya 760900 6.7 2.917 3.783 5 0

Tanzania Kenya 761010 8.395 4.207 4.188 5 0


Tanzania Kenya 761100 5.438 2.602 2.836 2.5 0

Tanzania Kenya 761210 0.273 0.122 0.152 3 0

161

Tanzania Kenya 761290 0.94 0.366 0.574 5 0

Tanzania Kenya 761410 0.358 0.083 0.276 5 0

Tanzania Kenya 761490 0.114 0.053 0.061 5 0

Tanzania Kenya 761519 41.884 29.571 12.312 5 0

Tanzania Kenya 761610 0.664 0.293 0.371 5 0

Tanzania Kenya 761691 0.053 0.015 0.038 5 0

Tanzania Kenya 761699 0.101 0.029 0.073 5 0




Tanzania Kenya 820299 0.063 0.026 0.037 5 0

Tanzania Kenya 820310 0.222 0.057 0.165 5 0

Tanzania Kenya 820320 0.153 0.068 0.085 5 0

Tanzania Kenya 820420 0.115 0.041 0.074 5 0

Tanzania Kenya 820510 0.116 0.052 0.064 5 0

Tanzania Kenya 820520 0.141 0.06 0.081 5 0

Tanzania Kenya 820570 0.297 0.128 0.169 5 0

Tanzania Kenya 820580 0.197 0.069 0.129 5 0

Tanzania Kenya 820590 3.41 1.6 1.809 5 0

Tanzania Kenya 820600 1.17 0.29 0.88 5 0

Tanzania Kenya 820720 0.044 0.004 0.04 5 0

Tanzania Kenya 820770 0.125 0.085 0.04 5 0

Tanzania Kenya 820790 0.2 0.084 0.117 5 0


Tanzania Kenya 820900 1.564 0.9 0.664 5 0

Tanzania Kenya 821210 0.391 0.012 0.379 5 0

Tanzania Kenya 821300 0.111 0.048 0.063 5 0

Tanzania Kenya 821490 0.082 0.035 0.047 5 0

Tanzania Kenya 821510 0.134 0.071 0.063 5 0

Tanzania Kenya 821599 0.204 0.089 0.115 5 0

Tanzania Kenya 830110 0.063 0.027 0.036 5 0

Tanzania Kenya 830130 0.088 0.041 0.047 5 0

Tanzania Kenya 830140 0.509 0.211 0.298 5 0

Tanzania Kenya 830150 2.606 1.795 0.811 5 0

Tanzania Kenya 830210 0.162 0.077 0.085 5 0

Tanzania Kenya 830230 0.098 0.045 0.053 5 0

Tanzania Kenya 830241 0.452 0.317 0.134 5 0

Tanzania Kenya 830242 0.352 0.149 0.203 5 0

Tanzania Kenya 830249 0.104 0.011 0.093 5 0


Tanzania Kenya 830400 3.235 1.318 1.917 5 0

Tanzania Kenya 830590 0.128 0.055 0.074 5 0

Tanzania Kenya 830629 4.363 2.559 1.804 5 0

Tanzania Kenya 830990 4.056 1.679 2.377 5 0

Tanzania Kenya 831000 1.695 0.67 1.025 5 0

Tanzania Kenya 831110 5.564 2.653 2.912 3 0

Tanzania Kenya 831120 0.353 0.172 0.18 3 0

Tanzania Kenya 831130 2.552 1.332 1.22 3 0

Tanzania Kenya 831190 0.115 0.053 0.062 3 0

162





Tanzania Kenya 840290 0.268 0.081 0.187 2 0




Tanzania Kenya 840790 1.8 1.374 0.426 3 0

Tanzania Kenya 840890 0.456 0.173 0.283 3 0

Tanzania Kenya 840910 0.297 0.037 0.261 3 0

Tanzania Kenya 840991 0.667 0.547 0.12 3 0

Tanzania Kenya 840999 5.586 2.306 3.28 3 0


Tanzania Kenya 841090 0.042 0.009 0.033 2 0


Tanzania Kenya 841319 0.13 0.065 0.064 3 0

Tanzania Kenya 841320 1.924 0.839 1.085 1.5 0

Tanzania Kenya 841330 0.051 0.024 0.027 3 0

Tanzania Kenya 841350 0.137 0.051 0.086 1 0

Tanzania Kenya 841360 0.145 0.05 0.095 1 0

Tanzania Kenya 841370 5.971 3.046 2.925 1 0

Tanzania Kenya 841381 1.327 0.49 0.838 1 0

Tanzania Kenya 841382 0.197 0.05 0.147 1 0

Tanzania Kenya 841391 7.966 2.73 5.235 2 0

Tanzania Kenya 841410 4.698 1.79 2.909 3 0

Tanzania Kenya 841430 0.184 0.069 0.115 3 0

Tanzania Kenya 841440 2.227 0.437 1.791 3 0

Tanzania Kenya 841451 0.146 0.08 0.067 3 0

Tanzania Kenya 841459 0.437 0.177 0.26 3 0

Tanzania Kenya 841480 1.314 0.673 0.641 3 0

Tanzania Kenya 841490 0.523 0.277 0.247 3 0

Tanzania Kenya 841510 1.279 0.469 0.81 5 0

Tanzania Kenya 841582 0.091 0.039 0.052 5 0

Tanzania Kenya 841583 0.632 0.462 0.17 5 0

Tanzania Kenya 841590 0.027 0.012 0.014 2 0



Tanzania Kenya 841690 0.086 0.041 0.045 2 0

Tanzania Kenya 841810 0.512 0.307 0.205 5 0

Tanzania Kenya 841821 0.075 0.022 0.053 5 0

Tanzania Kenya 841829 3.206 1.197 2.009 5 0

Tanzania Kenya 841830 0.186 0.114 0.072 5 0

Tanzania Kenya 841850 0.146 0.075 0.071 1 0

Tanzania Kenya 841861 0.287 0.158 0.129 1 0

Tanzania Kenya 841869 0.14 0.056 0.084 0.75 0

Tanzania Kenya 841891 0.05 0.026 0.024 3 0

Tanzania Kenya 841899 0.417 0.182 0.235 3 0

Tanzania Kenya 841919 0.109 0.021 0.088 1.5 0

163

Tanzania Kenya 841939 0.164 0.086 0.079 3 0



Tanzania Kenya 841989 0.27 0.196 0.075 3 0

Tanzania Kenya 841990 1.115 0.52 0.595 3 0

Tanzania Kenya 842091 0.088 0.032 0.056 2 0

Tanzania Kenya 842119 0.069 0.017 0.053 3 0


Tanzania Kenya 842123 0.642 0.296 0.346 3 0

Tanzania Kenya 842129 0.16 0.039 0.12 3 0

Tanzania Kenya 842139 1.296 0.686 0.61 3 0

Tanzania Kenya 842191 0.042 0.02 0.022 3 0

Tanzania Kenya 842199 0.435 0.255 0.18 3 0

Tanzania Kenya 842211 0.043 0.023 0.02 3 0




Tanzania Kenya 842290 3.047 1.325 1.722 2 0


Tanzania Kenya 842381 0.133 0.052 0.081 3 0

Tanzania Kenya 842382 0.055 0.024 0.031 3 0

Tanzania Kenya 842390 0.095 0.038 0.057 3 0

Tanzania Kenya 842410 1.324 0.697 0.627 3 0

Tanzania Kenya 842420 0.346 0.174 0.173 3 0


Tanzania Kenya 842511 0.093 0.04 0.052 3 0

Tanzania Kenya 842520 0.229 0.143 0.086 3 0

Tanzania Kenya 842539 0.696 0.411 0.285 3 0

Tanzania Kenya 842542 0.035 0.014 0.021 3 0


















Tanzania Kenya 843110 1.001 0.467 0.534 2 0

Tanzania Kenya 843139 0.057 0.023 0.034 2 0

Tanzania Kenya 843143 0.172 0.039 0.133 2 0

164

Tanzania Kenya 843149 39.597 14.616 24.98 2 0




Tanzania Kenya 843290 0.173 0.074 0.099 2 0




Tanzania Kenya 843590 0.052 0.025 0.028 2 0




Tanzania Kenya 843699 0.199 0.072 0.127 2 0






Tanzania Kenya 843890 0.266 0.107 0.159 2 0



Tanzania Kenya 844250 0.136 0.044 0.091 3 0




Tanzania Kenya 844390 2.511 1.317 1.194 2 0




Tanzania Kenya 844849 0.282 0.143 0.139 2 0

Tanzania Kenya 844859 0.088 0.037 0.051 2 0



Tanzania Kenya 845190 0.029 0.012 0.016 2 0


Tanzania Kenya 845290 0.036 0.021 0.016 2 0














165


Tanzania Kenya 846693 0.246 0.097 0.149 2 0



Tanzania Kenya 847030 0.072 0.039 0.034 3 0









Tanzania Kenya 847290 0.718 0.291 0.427 3 0





Tanzania Kenya 847490 7.007 2.743 4.264 2 0


Tanzania Kenya 847790 0.049 0.02 0.029 2 0





Tanzania Kenya 847990 0.427 0.107 0.32 2 0

Tanzania Kenya 848110 0.881 0.439 0.442 3 0

Tanzania Kenya 848120 4.279 2.301 1.978 3 0

Tanzania Kenya 848140 0.057 0.023 0.034 3 0

Tanzania Kenya 848180 0.433 0.225 0.208 3 0

Tanzania Kenya 848190 0.446 0.174 0.272 3 0

Tanzania Kenya 848240 0.452 0.322 0.131 3 0

Tanzania Kenya 848280 1.354 0.555 0.798 3 0

Tanzania Kenya 848299 0.056 0.014 0.042 3 0

Tanzania Kenya 848330 0.423 0.207 0.215 3 0

Tanzania Kenya 848340 0.183 0.075 0.108 3 0

Tanzania Kenya 848350 0.203 0.082 0.12 3 0

Tanzania Kenya 848390 0.259 0.136 0.123 3 0

Tanzania Kenya 848490 1.039 0.316 0.723 3 0

Tanzania Kenya 850110 0.168 0.079 0.089 3 0

Tanzania Kenya 850132 0.115 0.052 0.063 3 0

Tanzania Kenya 850133 0.152 0.052 0.1 3 0

Tanzania Kenya 850140 0.696 0.508 0.187 3 0

Tanzania Kenya 850151 0.112 0.044 0.068 3 0

Tanzania Kenya 850152 0.349 0.147 0.201 3 0

Tanzania Kenya 850153 0.278 0.118 0.16 3 0

Tanzania Kenya 850161 0.31 0.074 0.236 3 0



166

Tanzania Kenya 850211 2.605 1.152 1.452 1.5 0



Tanzania Kenya 850239 8.935 5.275 3.66 3 0

Tanzania Kenya 850300 0.173 0.09 0.083 3 0





Tanzania Kenya 850610 1.887 0.799 1.087 5 0

Tanzania Kenya 850680 0.37 0.12 0.25 5 0

Tanzania Kenya 850710 6.236 2.557 3.679 3 0

Tanzania Kenya 850720 3.845 2.104 1.74 3 0

Tanzania Kenya 850780 3.067 0.019 3.047 3 0


Tanzania Kenya 850810 1.058 0.509 0.55 3 0

Tanzania Kenya 850980 0.281 0.134 0.147 5 0

Tanzania Kenya 851110 0.053 0.018 0.035 3 0

Tanzania Kenya 851220 0.078 0.026 0.051 3 0

Tanzania Kenya 851230 0.372 0.151 0.221 3 0

Tanzania Kenya 851310 2.124 0.872 1.253 3 0

Tanzania Kenya 851390 0.763 0.342 0.421 3 0





Tanzania Kenya 851590 0.064 0.043 0.022 2 0

Tanzania Kenya 851610 0.804 0.591 0.212 3 0

Tanzania Kenya 851629 0.418 0.112 0.305 5 0

Tanzania Kenya 851633 0.128 0.081 0.047 5 0

Tanzania Kenya 851660 0.906 0.384 0.521 5 0

Tanzania Kenya 851690 0.155 0.048 0.107 3 0

Tanzania Kenya 851719 0.35 0.149 0.201 3 0

Tanzania Kenya 851721 0.219 0.093 0.125 3 0


Tanzania Kenya 851780 0.347 0.18 0.167 3 0

Tanzania Kenya 851790 0.214 0.079 0.135 3 0

Tanzania Kenya 851810 0.047 0.014 0.033 5 0

Tanzania Kenya 851821 0.05 0.015 0.035 5 0

Tanzania Kenya 851829 2.669 1.775 0.893 5 0

Tanzania Kenya 851850 0.348 0.164 0.185 5 0

Tanzania Kenya 851890 0.15 0.05 0.101 3 0

Tanzania Kenya 852010 0.081 0.032 0.049 5 0

Tanzania Kenya 852190 1.988 0.869 1.119 5 0

Tanzania Kenya 852290 0.416 0.142 0.274 3 0

Tanzania Kenya 852311 0.386 0.166 0.22 5 0


Tanzania Kenya 852692 0.182 0.083 0.098 3 0

Tanzania Kenya 852712 5.881 1.292 4.589 5 0

167

Tanzania Kenya 852719 0.854 0.367 0.487 5 0

Tanzania Kenya 852812 0.154 0.074 0.08 5 0

Tanzania Kenya 852910 0.185 0.065 0.12 3 0

Tanzania Kenya 852990 9.552 2.943 6.609 3 0


Tanzania Kenya 853190 0.053 0.028 0.025 3 0

Tanzania Kenya 853510 1.736 0.938 0.798 3 0


Tanzania Kenya 853530 0.411 0.15 0.261 3 0

Tanzania Kenya 853590 2.009 0.929 1.08 3 0

Tanzania Kenya 853610 0.715 0.244 0.471 3 0

Tanzania Kenya 853620 0.429 0.181 0.248 3 0

Tanzania Kenya 853630 0.571 0.23 0.341 3 0

Tanzania Kenya 853649 0.254 0.081 0.173 3 0

Tanzania Kenya 853650 4.081 1.616 2.464 3 0

Tanzania Kenya 853669 0.953 0.236 0.717 3 0

Tanzania Kenya 853690 2.471 0.603 1.868 3 0

Tanzania Kenya 853710 20.318 9.197 11.121 3 0

Tanzania Kenya 853720 1.425 0.544 0.881 3 0

Tanzania Kenya 853810 1.079 0.438 0.641 3 0

Tanzania Kenya 853890 4.927 1.696 3.231 3 0

Tanzania Kenya 853910 0.353 0.168 0.185 5 0

Tanzania Kenya 853921 0.642 0.272 0.371 5 0

Tanzania Kenya 853929 3.132 1.41 1.721 5 0

Tanzania Kenya 853931 0.781 0.324 0.457 5 0

Tanzania Kenya 853939 0.891 0.318 0.572 5 0

Tanzania Kenya 853990 1.068 0.434 0.634 5 0


Tanzania Kenya 854212 0.058 0.017 0.041 3 0

Tanzania Kenya 854340 4.603 4.597 0.006 3 0

Tanzania Kenya 854411 8.702 3.558 5.144 5 0

Tanzania Kenya 854419 2.54 0.961 1.579 5 0

Tanzania Kenya 854420 2.261 0.748 1.512 5 0

Tanzania Kenya 854441 0.053 0.015 0.038 5 0

Tanzania Kenya 854449 5.021 1.333 3.688 5 0

Tanzania Kenya 854451 0.221 0.08 0.141 5 0

Tanzania Kenya 854460 0.984 0.547 0.437 5 0

Tanzania Kenya 854470 2.648 1.098 1.55 5 0

Tanzania Kenya 854520 0.19 0.069 0.121 3 0

Tanzania Kenya 854690 1.788 0.95 0.838 3 0





Tanzania Kenya 870120 0.29 0.113 0.177 1 0


Tanzania Kenya 870210 2.918 1.358 1.56 1.33 0

Tanzania Kenya 870290 0.625 0.25 0.375 1.33 0

Tanzania Kenya 870321 0.622 0.163 0.459 1.67 0

168

Tanzania Kenya 870322 0.502 0.125 0.377 1.67 0

Tanzania Kenya 870323 4.937 1.979 2.958 1.67 0

Tanzania Kenya 870324 3.582 1.724 1.858 1.67 0

Tanzania Kenya 870332 0.177 0.115 0.062 1.67 0

Tanzania Kenya 870333 1.687 0.701 0.987 1.67 0

Tanzania Kenya 870410 8.963 4.627 4.337 2 0

Tanzania Kenya 870421 10.045 4.028 6.017 1 0

Tanzania Kenya 870422 10.162 4.487 5.675 1 0

Tanzania Kenya 870423 0.216 0.081 0.135 1 0

Tanzania Kenya 870432 0.045 0.018 0.027 1 0

Tanzania Kenya 870490 0.753 0.256 0.497 1 0




Tanzania Kenya 870710 0.093 0.03 0.064 3 0

Tanzania Kenya 870790 3.376 0.513 2.863 3 0

Tanzania Kenya 870810 0.353 0.142 0.212 3 0

Tanzania Kenya 870829 0.084 0.052 0.032 3 0

Tanzania Kenya 870839 0.159 0.097 0.062 3 0

Tanzania Kenya 870860 0.231 0.21 0.022 3 0

Tanzania Kenya 870870 0.254 0.116 0.138 3 0

Tanzania Kenya 870891 1.258 0.457 0.801 3 0

Tanzania Kenya 870899 0.605 0.152 0.452 3 0

Tanzania Kenya 870990 1.016 0.406 0.61 3 0


Tanzania Kenya 871110 0.822 0.452 0.37 5 0

Tanzania Kenya 871120 0.192 0.078 0.114 5 0

Tanzania Kenya 871200 0.948 0.436 0.513 5 0

Tanzania Kenya 871419 0.494 0.199 0.294 3 0






Tanzania Kenya 871680 0.371 0.16 0.211 3 0

Tanzania Kenya 871690 0.86 0.374 0.485 3 0




Tanzania Kenya 890399 0.221 0.114 0.107 5 0



Tanzania Kenya 900219 0.626 0.279 0.347 3 0

Tanzania Kenya 900319 0.096 0.035 0.061 3 0

Tanzania Kenya 900490 0.121 0.045 0.076 3 0

Tanzania Kenya 900659 2.112 1.266 0.846 3 0

Tanzania Kenya 900719 11.949 7.298 4.651 3 0

Tanzania Kenya 900720 0.077 0.029 0.048 3 0

Tanzania Kenya 900911 0.394 0.189 0.204 3 0

169

Tanzania Kenya 900912 0.147 0.074 0.073 3 0

Tanzania Kenya 900990 1.464 0.565 0.899 3 0

Tanzania Kenya 901010 0.036 0.013 0.023 3 0

Tanzania Kenya 901090 0.055 0.014 0.041 3 0


Tanzania Kenya 901780 2.261 1.039 1.222 3 0

Tanzania Kenya 901790 0.052 0.023 0.029 3 0













Tanzania Kenya 902511 0.061 0.026 0.035 3 0

Tanzania Kenya 902580 0.837 0.35 0.486 3 0

Tanzania Kenya 902590 0.053 0.017 0.036 3 0

Tanzania Kenya 902610 0.136 0.062 0.074 3 0

Tanzania Kenya 902620 0.218 0.085 0.133 3 0

Tanzania Kenya 902680 0.085 0.032 0.053 3 0

Tanzania Kenya 902690 0.072 0.031 0.041 3 0

Tanzania Kenya 902780 0.753 0.358 0.395 3 0

Tanzania Kenya 902790 0.289 0.084 0.205 3 0

Tanzania Kenya 902820 0.411 0.18 0.231 3 0

Tanzania Kenya 902890 0.083 0.033 0.05 3 0

Tanzania Kenya 903141 0.042 0.027 0.016 3 0

Tanzania Kenya 903289 0.032 0.011 0.022 3 0

Tanzania Kenya 903290 0.261 0.111 0.15 3 0

Tanzania Kenya 903300 0.022 0.002 0.021 3 0

Tanzania Kenya 910529 0.287 0.165 0.122 5 0

Tanzania Kenya 911280 0.068 0.049 0.02 5 0

Tanzania Kenya 911490 0.097 0.065 0.032 5 0

Tanzania Kenya 920290 0.578 0.432 0.146 5 0

Tanzania Kenya 920300 0.148 0.036 0.112 5 0

Tanzania Kenya 920590 0.066 0.024 0.042 5 0

Tanzania Kenya 920790 0.696 0.31 0.386 5 0

Tanzania Kenya 920810 0.087 0.057 0.03 5 0

Tanzania Kenya 940120 1.146 0.438 0.707 5 0

Tanzania Kenya 940140 1.207 0.834 0.373 5 0

Tanzania Kenya 940169 0.158 0.065 0.093 5 0

Tanzania Kenya 940171 0.101 0.03 0.071 5 0

Tanzania Kenya 940179 0.091 0.022 0.069 5 0

Tanzania Kenya 940180 0.683 0.268 0.415 5 0

Tanzania Kenya 940190 1.167 0.649 0.518 5 0

170


Tanzania Kenya 940310 0.191 0.084 0.107 5 0

Tanzania Kenya 940320 0.502 0.131 0.371 5 0

Tanzania Kenya 940330 2.196 0.714 1.482 5 0

Tanzania Kenya 940340 2.138 1.521 0.617 5 0

Tanzania Kenya 940350 1.843 0.409 1.434 5 0

Tanzania Kenya 940360 5.53 1.136 4.394 5 0

Tanzania Kenya 940370 4.734 2.068 2.666 5 0

Tanzania Kenya 940380 1.832 0.751 1.081 5 0

Tanzania Kenya 940390 0.273 0.131 0.142 5 0

Tanzania Kenya 940410 0.874 0.289 0.585 5 0

Tanzania Kenya 940421 1.922 1.059 0.863 5 0

Tanzania Kenya 940429 1.959 0.984 0.975 5 0

Tanzania Kenya 940490 1.538 0.472 1.066 5 0

Tanzania Kenya 940510 11.265 5.555 5.71 5 0

Tanzania Kenya 940520 0.176 0.067 0.109 5 0

Tanzania Kenya 940540 9.004 3.982 5.021 5 0

Tanzania Kenya 940550 9.778 4.4 5.378 5 0

Tanzania Kenya 940560 1.472 0.283 1.189 5 0

Tanzania Kenya 940591 0.441 0.171 0.27 5 0

Tanzania Kenya 940599 0.867 0.296 0.571 5 0


Tanzania Kenya 950349 0.121 0.043 0.078 5 0

Tanzania Kenya 950390 0.137 0.071 0.066 5 0

Tanzania Kenya 950430 0.064 0.025 0.039 5 0

Tanzania Kenya 950440 0.178 0.063 0.115 5 0

Tanzania Kenya 950691 0.079 0.037 0.042 3 0

Tanzania Kenya 950699 0.08 0.032 0.048 3 0


Tanzania Kenya 950800 0.247 0.146 0.101 3 0

Tanzania Kenya 960200 2.077 1.558 0.519 5 0

Tanzania Kenya 960310 0.364 0.171 0.193 5 0

Tanzania Kenya 960321 1.279 0.533 0.746 5 0

Tanzania Kenya 960329 0.097 0.044 0.053 5 0

Tanzania Kenya 960340 0.102 0.032 0.07 5 0

Tanzania Kenya 960390 0.136 0.017 0.119 5 0

Tanzania Kenya 960400 2.461 1.39 1.071 5 0

Tanzania Kenya 960621 0.074 0.024 0.05 5 0

Tanzania Kenya 960720 0.655 0.524 0.132 5 0

Tanzania Kenya 960810 33.085 18.701 14.384 5 0

Tanzania Kenya 960820 0.052 0.012 0.04 5 0

Tanzania Kenya 960910 1.007 0.302 0.706 5 0

Tanzania Kenya 960990 0.808 0.425 0.383 5 0

Tanzania Kenya 961000 0.25 0.115 0.135 5 0

Tanzania Kenya 961210 0.173 0.11 0.063 5 0

Tanzania Kenya 961700 5.674 2.424 3.249 5 0

Tanzania Kenya Total 4860.21

2

3268.32

8

1591.88

4

2.84 0

Tanzania Uganda 10420 0.513 0.438 0.075 5 0

171

Tanzania Uganda 40120 18.524 15.011 3.513 5 0

Tanzania Uganda 70320 0.092 0.041 0.05 5 0

Tanzania Uganda 70820 0.977 0.894 0.083 5 0

Tanzania Uganda 71331 0.056 0.021 0.035 2.5 0

Tanzania Uganda 71390 0.168 0.082 0.086 2.5 0

Tanzania Uganda 100510 12.857 5.605 7.252 2.5 0

Tanzania Uganda 100590 24.819 13.109 11.709 5 0

Tanzania Uganda 100830 0.054 0.054 0 2.5 0

Tanzania Uganda 120991 0 0 0 0 0

Tanzania Uganda 180631 0.222 0.089 0.133 5 0

Tanzania Uganda 200590 0.081 0.03 0.051 5 0

Tanzania Uganda 220110 0.343 0.174 0.169 5 0



Tanzania Uganda 271000 55.441 30.322 25.118 0.33 0


Tanzania Uganda 300390 0.105 0.041 0.064 2 0

Tanzania Uganda 300490 0.116 0.039 0.077 2 0

Tanzania Uganda 320990 0.056 0.027 0.029 5 0

Tanzania Uganda 340111 0.645 0.254 0.391 5 0

Tanzania Uganda 340119 0.283 0.173 0.11 5 0

Tanzania Uganda 340120 0.61 0.448 0.162 5 0

Tanzania Uganda 340290 1.534 0.571 0.963 3 0

Tanzania Uganda 350300 0.092 0.043 0.049 3 0

Tanzania Uganda 370790 0.121 0.04 0.08 3 0



Tanzania Uganda 392310 7.59 5.016 2.574 5 0

Tanzania Uganda 392321 1.102 0.513 0.589 5 0

Tanzania Uganda 392329 0.154 0.057 0.097 5 0

Tanzania Uganda 392390 0.096 0.046 0.05 5 0

Tanzania Uganda 392690 0.53 0.292 0.238 5 0

Tanzania Uganda 401110 0.043 0.003 0.041 5 0

Tanzania Uganda 420299 0.234 0.068 0.167 5 0

Tanzania Uganda 440724 0.322 0.301 0.021 3 0

Tanzania Uganda 440810 0.041 0.041 0 3 0

Tanzania Uganda 441900 1.492 0.235 1.258 5 0

Tanzania Uganda 442010 2.598 1.229 1.369 5 0

Tanzania Uganda 480810 0.834 0.595 0.239 3 0

Tanzania Uganda 481890 3.495 2.738 0.758 5 0

Tanzania Uganda 481910 7.497 5.091 2.407 3 0

Tanzania Uganda 482190 0.066 0.025 0.041 2 0



Tanzania Uganda 611490 0.065 0.011 0.054 5 0

Tanzania Uganda 620829 0.542 0.48 0.063 5 0

Tanzania Uganda 621020 0.983 0.479 0.503 5 0

Tanzania Uganda 630299 0.414 0.181 0.234 5 0

Tanzania Uganda 630533 1.084 0.462 0.622 3 0

172

Tanzania Uganda 630900 4.187 1.771 2.416 5 0

Tanzania Uganda 690410 0.08 0.028 0.051 5 0


Tanzania Uganda 701092 0.247 0.068 0.179 3 0

Tanzania Uganda 702000 0.134 0.053 0.081 3 0

Tanzania Uganda 721049 0.228 0.096 0.133 5 0

Tanzania Uganda 721070 0.015 0.009 0.006 5 0

Tanzania Uganda 721590 0.094 0.042 0.051 3 0

Tanzania Uganda 721621 0.136 0.019 0.118 3 0

Tanzania Uganda 721633 0.076 0.023 0.053 3 0

Tanzania Uganda 721650 0.066 0.044 0.022 3 0

Tanzania Uganda 721699 0.049 0.023 0.026 3 0

Tanzania Uganda 721790 0.142 0.06 0.082 2 0

Tanzania Uganda 721990 0.034 0.024 0.01 3 0

Tanzania Uganda 722219 0.151 0.065 0.085 3 0

Tanzania Uganda 730429 0.396 0.181 0.215 5 0

Tanzania Uganda 730660 0.779 0.543 0.235 5 0


Tanzania Uganda 731419 0.178 0.123 0.055 5 0

Tanzania Uganda 731822 0.056 0.023 0.032 5 0


Tanzania Uganda 820520 0.107 0.046 0.062 5 0


Tanzania Uganda 841440 0.084 0.016 0.067 3 0

Tanzania Uganda 841829 0.397 0.148 0.25 5 0


Tanzania Uganda 842542 0.095 0.037 0.057 3 0

Tanzania Uganda 843149 0.191 0.07 0.121 2 0









Tanzania Uganda 851719 0.654 0.278 0.376 3 0

Tanzania Uganda 851721 0.098 0.042 0.056 3 0



Tanzania Uganda 851780 0.975 0.505 0.47 3 0

Tanzania Uganda 851790 0.567 0.209 0.358 3 0


Tanzania Uganda 852990 0.493 0.15 0.343 3 0


Tanzania Uganda 870210 0.766 0.356 0.41 1.33 0

Tanzania Uganda 870321 0.082 0.021 0.06 1.67 0

Tanzania Uganda 870323 0.565 0.226 0.338 1.67 0

Tanzania Uganda 870410 0.101 0.052 0.049 2 0

173

Tanzania Uganda 870421 0.326 0.131 0.196 1 0

Tanzania Uganda 870431 0.08 0.028 0.051 1 0

Tanzania Uganda 871110 0.138 0.076 0.062 5 0

Tanzania Uganda 871120 1.017 0.415 0.602 5 0

Tanzania Uganda 871130 0.069 0.016 0.053 5 0

Tanzania Uganda 871200 0.536 0.246 0.29 5 0

Tanzania Uganda 900110 0.04 0.018 0.022 3 0

Tanzania Uganda 900659 0.06 0.035 0.025 3 0

Tanzania Uganda 900830 0.094 0.02 0.074 3 0

Tanzania Uganda 900911 0.677 0.325 0.351 3 0

Tanzania Uganda 900912 1.905 0.956 0.949 3 0

Tanzania Uganda 900990 2.19 0.847 1.343 3 0

Tanzania Uganda 930330 1.766 1.631 0.135 5 0

Tanzania Uganda 940330 0.092 0.03 0.062 5 0

Tanzania Uganda 961100 0.16 0.066 0.093 5 0

Tanzania Uganda Total 168.265 95.562 72.703 2.93 0

Documents

Winners or Losers? The “new” East African Community: Welfare implication of Regional Trade Agreement in East Africa