Regionalism and Multilateralism in Africa: An empirical ... · that same summit African leaders made a decision to establish a Pan-Africa Continental Free Trade Area (CFTA) by 2017

Sabbatical Leave Programme 2016-2017 Report prepared by the staff member

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Sabbatical Leave Programme 2016-2017

Regionalism and Multilateralism in Africa:

An empirical perspective

(First draft)

Name of staff member:

Bineswaree Bolaky

Institution:

United Nations Conference on Trade and Development

/University of Geneva

Academic supervisor’s name and title:

Professor Marcelo Olarreaga

Dean, Geneva School of Economics and Management

University of Geneva

Date:

31 August 2017

© United Nations Sabbatical Leave Programme

The views and recommendations expressed in this report are solely those of the

original author and other contributors and do not necessarily reflect the official

views of the United Nations, its agencies or its Member States. Textual

material may be freely reproduced with proper citation as appropriate.


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Endorsement by academic supervisor

This is to certify that this report is based on the research undertaken by Bineswaree Bolaky during the period of March 1 and July 3rd 2017 at the University of Geneva under my supervision.

Signature:

Name: Professor Marcelo Olarreaga

Title: Dean, Geneva School of Economics and Management, University of Geneva

Date: 31 August 2017


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Contents

Table of Contents

Abstract ........................................................................................................................................... 4

Introduction .................................................................................................................................... 6

Body of the Report………………………………………………………………………………. 7

I. Regional integration and trade in Africa.

A. Brief history of regional integration in Africa and its current challenges

B. State of trade (exports and imports) within RECs

II. The interface between regionalism and multilateralism in Africa: An empirical

perspective.

A. Brief literature review: Building blocs v/s Stumbling blocs debate

B. Methodology of paper

C. Description of data used and State of MFN and Preferential tariffs in RECs

(i) Data

(ii) MFN rates in Africa

(iii) Minimum preferential rates in Africa

D. Estimation results

Conclusions and Recommendations……………………………………………………………35

Appendix A: Estimation Results……………………………………………………………….39

Appendix B: a. MFN Rates Profiles of African countries……………………………………50

b. Data Availability per African country: MFN rates

c. Data Availability per African country: Preferential rates

References


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Abstract

The focus of this report is to study the interface between regionalism and multilateralism in Africa from

an empirical perspective. The main idea is to investigate two key empirical questions:

▪ Whether Most Favored Nation (MFN) applied tariffs set by African countries exert an influence

on the preferential tariffs that they impose on members of their own regional economic

community (REC)? and;

▪ Whether preferential tariffs set by African countries on their REC members have an influence on

MFN applied tariffs set for members outside their regional economic community?

The purpose of the report is to shed light on whether external trade liberalization pressures affect the

setting of preferential rates by African countries for its African trading partners (within their regional

economic community), that is whether multilateralism is a building or stumbling bloc for regionalism in

Africa. Similarly it sheds light on whether preferential rates set by African countries for their African REC

partners influence the MFN rates granted by African countries to external trading partners, whether

regionalism is a building or stumbling bloc for multilateralism in Africa. Answers to questions of this

nature have policy implications for the regional integration process in Africa and can provide guidance to

policy makers on the "right" sequencing and timing of tariff cuts in their trade policies.

Based on a modeling approach borrowed in part from Estevadeordal, Freund and Ornelas (2008), and

using econometric methods of estimation, there is preliminary evidence to suggest that African countries

respond to reductions in the MFN rate (that is to increased external liberalization), to increased non-tariff

barriers to exports and to greater dependence on multilateral loans by increasing the preferential rate

(decreasing the preference margins) of their REC trading partners. Multilateralism in this sense hurts

regionalism. Greater dependence on multiltateral finance, that often comes with conditionalities also hurts

regionalism. Losses in export competitiveness does not help regionalism neither, this is perhaps tied to a

rationale to make up for lost export revenues by avoiding import tariff reductions and avoid lost fiscal

revenues. On the other hand, when REC trading partners face increased non-tariff barriers to imports, they

are "compensated" through reductions in the preferential rate charged to them in order to increase their

preference margins.

There is also statistical evidence that in the African context, regionalism neither hurts nor helps

multilateralism. However in setting their MFN rates, African countries take into account non-tariff barrier

constraints and their dependence on multilateral institutions for financial support. Losses in export

competitiveness tend to lead African countries to charge higher MFN rates while prohibitive barriers to

imports lead them to "compensate" importers with lower import tariffs.

Going back to the two empirical questions posed in the paper: i) whether Most Favored Nation (MFN)

applied tariffs set by African countries exert an influence on the preferential tariffs that they impose on

members of their own regional economic community? and (ii) whether preferential tariffs set by African

countries on their REC members have an influence on MFN applied tariffs set for members outside their

regional economic community? The answers, based on the available evidence is yes to the first question


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and no to the second. While this paper finds no evidence that regionalism helps or hurts multilateralism in

Africa, it finds evidence on the other hand that multilateralism hurts regionalism in Africa.

This report could be used by the organization, especially UNCTAD to make specific policy

recommendations to African policy makers on the interface between regionalism and multilateralism.

African countries should strategically set their MFN rates and the preferential rates of their different types

of trading partners with a view to deepening regional integration in Africa. Policies for removing non-

tariff barriers or lowering trade costs must be effectively implemented in order to boost intra-African

trade.


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Introduction

Focus and purpose of the report

The focus of this report is to study the interface between regionalism and multilateralism in Africa from an

empirical perspective. The main idea is to investigate two key empirical questions:

▪ Whether Most Favored Nation (MFN) applied tariffs set by African countries exert an influence

on the preferential tariffs that they impose on members of their own bloc? and;

▪ Whether preferential tariffs set by African countries on their bloc members have an influence on

MFN applied tariffs set for members outside their regional economic bloc?

The purpose of the report is to shed light on whether external trade liberalization pressures affect the

setting of preferential rates by African countries for its African trading partners (within their regional

economic community and outside their regional economic community), that is whether multilateralism is a

building or stumbling bloc for regionalism in Africa. Similarly it sheds light on whether preferential rates

set by African countries for their African trading partners influence the MFN rates granted by African

countries to external trading partners, whether regionalism is a building or stumbling bloc for

multilateralism in Africa. Answers to questions of this nature have policy implications for the regional

integration process in Africa and can provide guidance to policy makers on the "right" sequencing and

timing of tariff cuts in their trade policies.

Background, context and relevance

Regional integration and the boosting of intra-Africa trade are key priorities for African governments and

its development partners, as evidenced in several main strategic African Union (AU) documents and in

decisions that were made at a high political level by African Heads of State. The Africa Agenda 2063 set

out the vision of African leaders for the continent for the next 50 years and acknowledges "the critical role

of Regional Economic Communities as building blocks for continental unity" (Paragraph 3, Page 1, AU

2015). The AU Action Plan for Boosting Intra-African Trade (BIAT), endorsed at the Assembly of the

Heads of State and Government of the African Union, during its 18th Ordinary Session in January 2012,

reflected the commitment of African governments to accelerate market integration on the continent. At

that same summit African leaders made a decision to establish a Pan-Africa Continental Free Trade Area

(CFTA) by 2017. Against this backdrop, empirical research on the factors promoting or hindering regional

trade and regional integration in Africa is highly relevant. Yet so far, to the best of our knowledge, scant

or no empirical research exists on the interface between regionalism and multilateralism in Africa. While a

theoretical and empirical literature exists on whether regionalism and multilateralism are "friends" or

"foes", research on that issue specific to Africa is scarce. This report intends to fill an important gap in that

regard.

Scope and direction of the report

The report is divided into two sections: Section I highlights a few empirical facts on the state of intra-bloc

trade in Africa while Section II outlines the methodology, data and estimaton results for answering the two

main empirical questions of the report as cited above.


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Body of the Report

I. Regional integration and trade in Africa.

A. Brief history of regional integration in Africa and its current challenges.

Regional integration has a long standing history in Africa. In the aftermath of the creation of the

Organization of African Unity in 1963, several “regional economic communities” or RECs saw the day.

According to De Melo (2015), that first wave of regional integration efforts or regional integration

arrangements (RIAs), based on the idea that the RECs will form the building blocs for the emergence of a

unified continent, failed for several reasons, both economic and political. Non-economic reasons involved

a reluctance on the part of post-independence leaders to surrender national sovereignty and to create the

supra-national regional authorities that were needed to deepen regional integration and regional

coordination. A second wave of RIAs emerged after the signature of the Abuja Treaty in 1991 in which a

linear approach to regional integration was adopted (see Table 1) with a focus on trade in goods. Countries

committed to first form Free Trade Areas (FTA) to accelerate goods market integration, to be followed by

the formation of a Customs Union (CU) with a common external tariff (CET). The integration of goods

markets should have been followed by the integration of labor and capital markets, the creation of a

common market, fiscal and monetary integration to finally culminate in a full economic and political

union.

Table 2 depicts the current 8 main regional economic communities recognized by the African Union as

building blocs for advancing continental integration in Africa. These are the Arab Maghreb Union

(AMU), the Community of Sahel-Saharan States (CEN-SAD), the Common Market for Eastern and

Southern Africa (COMESA), the Economic Community of Central African States (ECCAS), the

Economic Community for Western African States (ECOWAS), the Eastern African Community (EAC),

the Inter-governmental Authority on Government (IGAD), and the Southern African Development

Community (SADC). Out of these 8 RECS, so far in 2017, only EAC, ECOWAS and COMESA have

established a Customs Union while ECCAS and SADC are FTAs. However their operationalization,

within a linear model to regional integration, is yet to become fully effective. De Melo notes that “along

this linear sequence, except for the Southern African Customs Union (SACU), none have really reached

full CU status because exceptions to the 4-5 CET tariff band structure are so numerous. For example, the

ECOWAS CET includes an “exceptions list” of about 300 products eligible for exemption from the new

tariffs that includes 200 products from the former Nigerian Import Ban list” (De Melo, 2016).

Amidst announced plans for SADC, EAC and COMESA to merge into a Tripartite Free Trade Area

(TFTA), and for the region to form a Continental Free Trade Area CFTA) by 2017, there have been calls

of late for the continent to abandon its linear approach to regional integration through large membership

and to focus instead on integration in small groups. The linear model of integration, with its focus on

goods, has not resulted in impressive levels of trade performance with the volume of intra-regional trade

in African RIAs estimated to be on average 40 percent less than potential trade. Trade costs among

partners have fallen less rapidly than trade costs with outside partners (DeMelo, 2016). African borders

remain thick owing not only to “the geography of African trade, low trade complementarity across

partners, poor logistics, border delays, but also the neglect of services in the African linear integration

model which is no longer adapted to 21st century trade” (DeMelo, 2016). The way forward should include


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a greater recognition of the growing importance of trade in tasks and trade in services. Intra-African

barriers to trade in services should be dismantled in parallel to the dismantling of tariff and non-tariff

barriers in trade in goods (UNCTAD, 2015); trade facilitation measures at the border should be

emphasized along with policy reforms to attract FDI in services activities. According to De Melo (2016),

negotiations in small groups are less likely to to be marred by tensions between small economies and

larger ones over the distribution of the costs and benefits to the integration process and over the delegation

of authority to supra-national bodies. Multilateral think tanks such as UNCTAD and the Economic

Commission for Africa (ECA) have also pointed out that intra-African trade has been hampered by a lack

of productive and trading capacities among African countries that remain overly dependent on primary

commodities and are poorly economically diversified. Overlapping memberships (see Table 3) of RECs

by some countries complicate further their tasks of meeting all their requirements as REC members when

it comes to streamlining trade procedures and removing tariff and non-tariff barriers. In other words,

overlapping memberships slows the implementation of regional trade agreements. The prevalence of large

informal economies and preponderance of informal cross-border trade weaken the scope for enforcing

policy reforms. Insufficient infrastructure such as the lack of efficient transit corridors connecting

landlocked countries to coastal states compound the challenges behind regional integration in Africa. That

is to say that the deepening of regional integration in Africa inevitably goes beyond a mere lowering of

tariff and non-tariff barriers. Sigificant manifold hurdles remain on the road towards a single African

Economic Community.

There are 4 main pillars where substantial progress is required in order to bring to fruition the African

Economic Community (AEC) and these are: (i) trade and market integration (ii) macroeconomic policy

convergence, financial and monetary integration (iii) peace, security and stability and (iv) harmonisation

of sectoral policies in infrastructure, natural resources, climate, food, gender and agriculture (sourc: ECA

Observatory on Regional Integration in Africa).

A 2009 review of African RECs (GTZ, 2009) made the following six recommendations to accelerate

regional integration in Africa:

• Design mechanisms to mainstream and measure informal trade within regional integration;

• Enhance policy convergence within RECs;

• Enhance the coordination between RECs and member countries;

• Design creative and innovative ways to secure political will and stakeholders’ support for regional

integration;

• Establish mechanisms to ensure that the process of continental integration led by the African Union are

complementary and supportive to regional integration efforts and vice versa;

• Redress the underlying structural constraints including deep seated distrust among member states, which

fundamentally limit the depth and progress in regional integration.

These recommendations remain valid today. UNCTAD in its Economic Development in Africa Report

2013 has recommended African countries to adopt a model based on “Developmental regionalism” over

the pursuit of a linear approach to integration. Developmental regionalism encompasses cooperation and

coordination among countries in a larger array of areas, ranging from the development of spatial economic


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corridors, implementation of common regional industrial policies, creation of special economic zones to

the spawning of regional value-chains. It calls for greater attention to the building of entrepreneurial

capabilities and productive capacities within countries and deeper involvement of the private sector in the

regional integration process. In its Report, UNCTAD advocates for African countries to “move away from

a linear and process-based approach to regional integration, which focuses mostly on the removal of

trade barriers, to a development-based approach, which pays as much attention to the building of

productive capacity and private sector development as to the elimination of trade barriers” ( Page 133,

UNCTAD 2013).

Table 1. Milestones in the history of African Regional Integration

Milestone

Date

Description

1963 Formation of the Organization of African Unity (OAU), the forerunner of the African Union.

1980 Lagos Plan of Action for the Economic Development of Africa, whose objective was to promote the

economic and social development and integration of African economies so that African economies achieve

an increasing measure of self-sufficiency and self-sustainment. The Lagos Plan of Action also committed

African States to promote the economic integration of the continent and to establish national, sub-regional

and regional institutions which will facilitate the attainment of objectives of self-reliance and self-

sustainment.

1981 African Charter on Human and People’s Rights drafted. A protocol to the charter was adopted in 1988 and

came into effect in 2005.

1985 Africa’s Priority Programme for Economic Recovery (APPER), later reconverted and subsumed into the

United Nations Programme of Action for African Economic Recovery and Development, 1986-1990 (UN-

PAAERD). In the APPER, African governments, afflicted by an economic crisis, reaffirmed their

responsibility for the development of their countries and undertook to mobilize and utilize domestic

resources to achieve their identified priorities.

1991 Treaty Establishing the African Economic Community (AEC) known as The Abuja Treaty, which came

into force in 1994. The objectives of the Community were set to be among others to : (i) promote

economic, social and cultural development and the integration of African economies in order to increase

economic self-reliance and promote an endogenous and self-sustained development; and (ii) to coordinate

and harmonize policies among existing and future economic communities in order to foster the gradual

establishment of the Community.

1999 Sirte Declaration

2000 Solemn Declaration on security, stability, development and cooperation of the African continent

2000 AU New Partnership for Africa’s Development (NEPAD)

2001 AU Constitutive Act

April 2007 Study on “Rationalization of the Regional Economic Communities (RECs): Review of the Abuja Treaty

and Adoption of the Minimum Integration Programme” was completed and presented at the Second

Conference of Ministers in Charge of Integration in Rwanda, in July 2007.

2009 Elaboration of Minimun Integration Programmes (MIP). AUC should coordinate REC activities and

harmonize their policies and programmes, as recommended in the AU decision taken in The Gambia; and

The free movement of persons, goods, capital and services among and across all RECs should be

encouraged and promoted to accelerate continental integration.

2012 The Heads of State of the African Union in January 2012 adopted a decision to establish a Continental

Free Trade Area (CFTA) by an indicative date of 2017. The Summit also endorsed the Action Plan on

Boosting Intra-Africa Trade (BIAT) which identifies seven priority action clusters: trade policy, trade

facilitation, productive capacity, trade related infrastructure, trade finance, trade information, and factor

market integration. The aim was that “the CFTA should be operationalized by the indicative date of 2017,

based on a framework, roadmap and architecture, with the following milestones: 1. Finalization of the East


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African Community (EAC)/the Common Market for Eastern and Southern Africa (COMESA)/Southern

African Development Community (SADC) Tripartite FTA initiative by 2014. 2. Completion of FTA(s) by

Non-Tripartite RECs, through parallel arrangement(s) similar to the EAC-COMESA-SADC Tripartite

Initiative or reflecting the preferences of their Member States, between 2012 and 2014. 3. Consolidation of

the Tripartite and other regional FTAs into a Continental Free Trade Area (CFTA) initiative between 2015

and 2016. 4. Establishment of the Continental Free Trade Area (CFTA) by 2017 with the option to review

the target date according to progress made.”

2015 The COMESA-EAC-SADC Tripartite Free Trade Area (TFTA) was officially launched by Heads of State

and Governments of COMESA, EAC and SADC on 10 June, 2015 in Sharm El Sheikh, Egypt at the Third

Tripartite Summit. The Tripartite Summit gave Member States 12 months from the launch of the TFTA to

conclude outstanding negotiations issues on rules of origin, trade remedies and tariff offers. Due to a

number of challenges, the deadline was not met, and the commencement of Phase II negotiations –

covering trade in services and other trade related matters – has been delayed pending the conclusion of

negotiations on Phase I issues. Twenty four Member States have signed the Declaration; only Libya and

Eritrea have yet to sign. The Agreement needs 14 ratifications to enter into force but so far only 8

countries have ratified it. The TFTA will consist of 26 member countries, half of Africa’s GDP, 56 per

cent of the continental population and 636 million customers.

Stages set out in the 1991 Abuja Treaty

The Community shall be established gradually in six (6) stages of variable duration over a transitional period not

exceeding thirty-four (34) years.

Stage 1

Strengthening of existing regional economic communities and, within a period not exceeding five (5) years

from the date of entry into force of this Treaty, establishing economic communities in regions where they

do not exist.

Stage 2 At the level of each regional economic community and within a period not exceeding eight years, Tariff

Barriers and Non-Tariff Barriers, Customs Duties and internal taxes existing at the date of entry into force

of the Treaty should be stabilised; and studies prepared and adopted to determine the time-table for the

gradual removal of Tariff Barriers and NonTariff Barriers to regional and intra-Community trade. There

should also be gradual harmonisation of Customs Duties in relation to third States. Sectoral integration

should be strengthened at regional and continental levels particularly in the fields of trade, agriculture,

money and finance, transport and communications, industry and energy; and there should be co-ordination

and harmonisation of activities among the existing and future economic communities.

Stage 3 At the level of each regional economic community and within a period not exceeding ten (10) years,

establishment of a Free Trade Area through the observance of the time-table for the gradual removal of

Tariff Barriers and Non-Tariff Barriers to intra-community trade and the establishment of a Customs

Union by means of adopting a common external tariff.

Stage 4 Within a period not exceeding two (2) years, co-ordination and harmonisation of tariff and non-tariff

systems among the various regional economic communities with a view to establishing a Customs Union

at the continental level by means of adopting a common external tariff.

Stage 5 Within a period not exceeding four (4) years, establishment of an African Common Market through: (i) the

adoption of a common policy in several areas such as agriculture, transport and communications, industry,

energy and scientific research; (ii) the harmonisation of monetary, financial and fiscal policies; (iii) the

application of the principle of free movement of persons as well as the provisions regarding the rights of

residence and establishment; and (iv) constituting the proper resources of the Community as provided for

in paragraph 2 of Article 82 of the Treaty.

Stage 6 Within a period not exceeding five (5) years: (i) Consolidation and strengthening of the structure of the

African Common Market, through including the free movement of people, goods, capital and services, as

well as, the provisions regarding the rights of residence and establishment; (ii) Integration of all the sectors

namely economic, political, social and cultural; establishment of a single domestic market and a Pan-

African Economic and Monetary Union; (iii) Implementation of the final stage for the setting up of an

African Monetary Union, the establishment of a single African Central Bank and the creation of a single

African Currency; (iv) Implementation of the final stage for the setting up of the structure of the Pan-

African Parliament and election of its members by continental universal suffrage; (v) Implementation of


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the final stage for the harmonisation and co-ordination process of the activities of regional economic

communities; (vi) Implementation of the final stage for the setting up of the structures of African multi-

national enterprises in all sectors; and (vii) Implementation of the final stage for the setting up of the

structures of the executive organs of the Community.

Sources: African Union website; ECA ARIA IV (2010); Text of Abuja Treaty (1991); TRALAC

(https://www.tralac.org/resources/by-region/comesa-eac-sadc-tripartite-fta.html).

Table 2 Regional Economic Communities (RECs) in Africa

Name of block Acronym, date of

creation and

corresponding

region in Abuja

Treaty*

Member states

(as at 31 Dec 2016)

Economic and

Governance Indicators

Current status

(as at 31 Dec 2016)

Economic

Community of

Western Africa States

ECOWAS, West

Africa, established in

1975, a revised treaty

signed in 1993

15: Benin, Burkina

Faso, Cabo Verde,

Côte d’Ivoire, The

Gambia, Ghana,

Guinea, Guinea

Bissau, Liberia, Mali,

Niger, Nigeria,

Senegal, Sierra Leone

and Togo.

GDP: 664 billion US

GDP per capita: 1,901 US

Population:349 million

Area: 5.1 million sq.km

Court of Justice:

Community Court of

Justice

Legislative Assembly: No

Regional Bank: The

ECOWAS Bank for

Investment and

Development (EBID);

Customs Union with an

ECOWAS Common External

Tariff since 2016. ECOWAS

Trade Liberalization Scheme

(ETLS) established in 1975 and

revised in 1991 to include

industrial products and establish

rules of origin.

Within ECOWAS, the Western

African Economic and

Monetary Union (WAEMU)

operates among 8 countries

(Benin, Burkina Faso, Cote

d’Ivoire, Guinea Bissau, Mali,

Niger, Senegal and Togo). It is

a customs union and currency

union (CFA Franc as single

currency).

Economic

Community of

Central African

States

ECCAS, Central

Africa, established in

1983

10: Angola, Burundi,

Cameroon, Central

African Republic,

Chad, Congo,

Democratic Republic

of the Congo,

Equatorial Guinea,

Gabon, and Sao

Tome and Principe.

GDP:268 billion US




Court of Justice: The Court

of Justice (not yet

operational)


Regional Bank: No

FTA signed in 2004 and came

into force in 2006.

Within ECCAS, CEMAC (in

French, Communauté

Economique et Monétaire de

l’Afrique Centrale) operates as

an FTA with a Common

External Tariff on non-CEMAC

countries and a common

currency the CFA Franc.

Countries include Cameroon,

Central African Republic, Chad,

Congo, Equatorial Guinea and

Gabon. CEMAC is the

successor to the UDEAC (In

French, Union Douanière et

Economique de l’Afrique

Centrale), a customs union,

made effective in 1966.

Inter-governmental

Authority on

Development

IGAD, established in

1996, superseding the

Inter-governmental

Authority on Drought

8: Djibouti, Eritrea,

Ethiopia, Kenya,

Somalia, South

Sudan, Sudan and

GDP:251 billion US

GDP per capita: 988 US



Pre-FTA phase of market

integration

https://www.tralac.org/resources/by-region/comesa-eac-sadc-tripartite-fta.html)


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and Development

founded in 1986.

Uganda Court of Justice: No


Regional Bank: No

Arab Maghreb Union AMU, Northern

Africa, established

and treaty signed in

1989

5: Algeria, Libya,

Mauritania, Morocco,

Tunisia

GDP: 374 billion US

GDP per capita: US 3,914

Population: 95 million


Court of Justice: No


Regional Bank: Maghreb

Bank for Investment and

Foreign Trade

Community of Sahel-

Saharan States

CEN-SAD, North,

established in 1998

24: Benin, Burkina

Faso, Central African

Republic, Chad, the

Comoros, Côte

d’Ivoire, Djibouti,

Egypt, Eritrea, the

Gambia, Ghana,

Guinea-Bissau,

Libya, Mali,

Mauritania, Morocco,

Niger, Nigeria,

Senegal, Sierra

Leone, Somalia, the

Sudan, Togo and

Tunisia.

GDP: 1,320 billion


Population: 619 million


Court of Justice: No


Regional Bank: Sahel-

Saharan Bank for

Investment and Trade

East African

Community

EAC, East,

relaunched in 2001

after dissolution of

the previous

Cooperation Treaty in

1977. Originally

founded in 1967.

6: Burundi, Kenya,

Rwanda, South

Sudan, Uganda and

United Republic of

Tanzania.

GDP:144 billion US

GDP per capita: 890 US



Court of Justice: East

African Court of Justice

Legislative Assembly: Yes

Regional Bank: East

African Development Bank

Customs Union signed in 2004

and came into force from 2005

Southern African

Development

Community

SADC, South, SADC

treaty signed in 1992,

successor to Southern

African Development

Coordinating

Conference, SADCC.

15: Angola,

Botswana, the

Democratic Republic

of Congo, Lesotho,

Madagascar, Malawi,

Mauritius,

Mozambique,

Namibia, Seychelles,

South Africa,

Swaziland, Tanzania,

Zambia and

Zimbabwe

GDP:650 billion US



Area: 10 million sq.km

Court of Justice: SADC

Tribunal


Regional Bank: No

Free Trade Area in 2008.

Customs Union delayed but in

progress.

The Regional Indicative

Strategic Development

Plan (RISDP) and the Strategic

Indicative Plan for the

Organ (SIPO) remain the

guiding frameworks for SADC

Regional Integration.

Within SADC, SACU

(Southern African Customs

Union), comprising Botswana,

Lesotho, Namibia, South

Africa, Swaziland, operates as a

customs union and all except

Botswana use the South African

Rand as a common currency

within the Common Monetary

Area. It operates a FTA with the

European Free Trade


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Association (EFTA), consisting

of Iceland, Liechtenstein,

Norway and Switzerland and a

PTA with MERCOSUR

(Argentina, Brazil, Paraguay

and Uruguay).

Common Market for

Eastern and Southern

Africa

COMESA, East and

South, formed in

1994, as a successor

to the PTA for


Africa formed in

1981.

19: Burundi, the

Comoros, the

Democratic Republic

of Congo, Djibouti,

Egypt, Eritrea,

Ethiopia, Kenya,

Libya, Madagascar,

Malawi, Mauritius,

Rwanda, Sudan,

Swaziland,

Seychelles, Uganda,

Zambia and

Zimbabwe.

GDP:696 billion US



Area: 12 million sq.km.

Court of Justice: COMESA

Court of Justice


Regional Bank: The Trade

and Development Bank for


Africa (PTA- Bank)

Free Trade Area in 2000.

Customs Union launched in

2009 and not yet

operationalized.

Notes: * The Abuja Treaty recognizes five regions in Africa: North,West, East, South and Central. GDP and GDP

per capita based on US dollars in current prices at 2015. Sources: GTZ (2009);ECA Observatory on Regional

Integration in Africa website; UNCTADStat database (accessed March 2017).

Table 3 Overlapping memberships in African RECs recognized by the AU

Country REC

Member of only one REC

Algeria* AMU

Botswana SADC

Cameroon ECCAS

Cabo Verde* ECOWAS

Congo ECCAS

Equatorial Guinea ECCAS

Gabon ECCAS

Guinea ECOWAS

Lesotho SADC

Liberia ECOWAS

Madagascar COMESA

Mozambique* SADC

Namibia SADC

Sao Tome and Principe* ECCAS

South Africa SADC

Member of 2 RECs

Angola ECCAS, SADC

Benin CENSAD, ECOWAS

Burkina Faso CENSAD, ECOWAS

Central African Republic CENSAD, ECCAS

Chad CENSAD, ECCAS

Comoros CENSAD, COMESA

Cote d’Ivoire CENSAD, ECOWAS

Egypt** CENSAD, COMESA

Ethiopia** COMESA, IGAD

Gambia** CENSAD, ECOWAS

Ghana** CENSAD, ECOWAS

Guinea-Bissau CENSAD, ECOWAS

Malawi** COMESA, SADC

Mali CENSAD, ECOWAS

Mauritania** AMU, CENSAD


15

Mauritius COMESA, SADC

Morocco** AMU, CENSAD but has applied for membership of ECOWAS in

2017

Niger CENSAD, ECOWAS

Nigeria** CENSAD, ECOWAS

Rwanda COMESA, EAC

Senegal CENSAD, ECOWAS

Seychelles COMESA, SADC

Sierra Leone ECOWAS, CENSAD

Somalia** CENSAD, IGAD

South Sudan** IGAD, EAC

Swaziland COMESA, SADC

Togo CENSAD, ECOWAS

Tunisia** AMU, CENSAD

United Republic of Tanzania EAC, SADC

Zambia COMESA, SADC

Zimbabwe** COMESA, SADC**

Member of 3 RECs

Burundi COMESA, EAC, ECCAS

Dem. Republic of Congo COMESA, ECCAS, SADC

Djibouti*** CENSAD, COMESA, IGAD

Eritrea*** CENSAD, COMESA, IGAD

Kenya COMESA, EAC, IGAD

Libya*** AMU, CENSAD, COMESA

Sudan CENSAD, COMESA, IGAD

Uganda COMESA, EAC, IGAD

Note: *Member of only one regional community, including other regional communities not recognized by the AU as building

blocks for continental regional integration. **Member of only two regional communities, including other regional communities

not recognized by the AU as building blocks for continental regional integration. ***Member of only three regional communities,

including other regional communities not recognized by the AU as building blocks for continental regional integration. Above

table is based on information as at 31 March 2017.

B. State of trade (exports and imports) within RECs.

Disappointing results in terms of intra-bloc trade and intra-bloc Foreign Direct Investment have been

highlighted in several UNCTAD reports (UNTAD, 2009. UNCTAD, 2013). However while the shares of

intra-trade tend to be low within the bloc, a more substantial level of trade occurs outside the bloc within

the region. Significant heterogeneity also exists in intra-bloc trade performance among the 8 blocs. The

disappointing performance among some RECs is strongly linked to the region's lack of economic and

export diversification, rather than the mere presence of barriers to trade alone.

Based on Tables 4-5, the following inferences can be made on the state of intra-bloc trade by RECs in the

period 1995 to 2016, when comparing these two years:

▪ EAC, ECOWAS, IGAD and SADC had the largest shares of intra-bloc exports both in 1995 and

in 2016. In 2016 that figure ranged between 11 to 22 per cent, compared to 24 per cent in ASEAN

and 14 per cent in MERCOSUR;

▪ EAC, ECOWAS, and SADC were the 3 blocs with the largest shares of intra-bloc imports both in

1995 and 2016, and in 2016 that figure ranged between 7 to 21 per cent, compared to 23 per cent

in ASEAN and 15 per cent in MERCOSUR;

▪ The shares of intra-bloc imports are lower than the shares of intra-bloc exports for most blocs;

▪ All RECs over the period had increased their share of intra-bloc trade on the export side but on

the import side, the picture is more mixed; the share of intra-bloc imports fell in AMU, EAC, and

IGAD;

▪ There is substantial intra-African trade that occurs outside regional blocs;


16

▪ On the export side, COMESA, EAC, ECCAS and IGAD exported more than 60 per cent of their

products on the continent in 2016 while in 1995 only ECCAS and IGAD did so;

▪ On the import side, COMESA, ECCAS and IGAD imported more than 65 per cent of their goods

from within the continent, while in 1995 only COMESA and ECCAS did so;

▪ Comparing 2016 to 1995, ECOWAS increased its share of intra-African exports by 20 percentage

points, followed by AMU (+17 per cent), CENSAD (+15) and EAC (+12). The share fell only in

IGAD;

▪ Comparing 2016 to 1995, EAC increased its share of intra-African imports by 30 percentage

points, followed by IGAD (+21), CENSAD (+14) and ECOWAS (+11). The shares fell only in

COMESA and ECCAS;

▪ If figures are compared for 1995 and 2016, on the export side, all regional blocs, except IGAD

have raised their shares of intra-bloc exports and intra-african exports. On the import side, only

AMU, ECCAS and IGAD have seen a decrease in their share of intra-bloc imports while only

COMESA and ECCAS have had a decrease in their share of intra-African imports, though in both

blocs intra-African imports remain high at more than 65 per cent.

A priori it seems that the formation of regional blocs is not a pre-requisite for boosting intra-African trade

and the culprit could lie in the lack of effective implementation in regional trade agreements. However

more rigorous empirical research is needed to investigate whether the formation of regional blocs have

diverted trade to the blocs or not.

It has been stated that that regional integration in Africa could serve as a launching pad for the

development of an indigenous manufacturing sector in Africa, given that intra-African trade is more

manufacturing-intensive than the trade of Africa with the rest of the world (UNCTAD, 2009; UNCTAD,

2013).

Table 6 shows the product composition of exports and imports in 1995 and 2016 for each regional bloc by

type of trading partner: (i) intra-bloc, that is trade with members within the given bloc (ii) intra-African

trade, that is trade with African countries outside of the bloc and (iii) trade with the rest of the world

(excluding Africa), that is trade with all non-African members.

In ALL regional economic blocs, intra-bloc exports are far more intensive in manufactures than exports

with the rest of the world and this holds both in 1995 and 2016. However, comparing 2016 to 1995, intra-

bloc exports have become less intensive in manufactures over time in AMU, COMESA, EAC, IGAD and

SADC, but exports with the rest of the world have become more intensive in manufactures in all blocs,

except for ECCAS, ECOWAS and SADC.

Intra-bloc imports on the other hand are less intensive in manufactures than imports with the rest of the

world, and this reflects the region’s poor and undiversified manufacturing base. The share of manufactures

in imports is always lower in the case of intra-bloc trade than trade with the rest of the world and this for

all blocs. When comparing 2016 to 1995, intra-bloc imports have become more manufacturing intensive

only in CENSAD and ECCAS. Increasing economic diversification through manufacturing development

can contribute towards the deepening of regional trade in Africa.


17

Table 4: Export Patterns across Regional Economic Communities

Source : UNCTADStat (downloaded July 2017) . Note : Rest of the world includes African countries outside the bloc.

Regional Economic Community 1995 2000 2005 2016

Intra-group Rest of region Rest of world Intra-group Rest of region Rest of world Intra-group Rest of region Rest of world Intra-group Rest of region Rest of world

AMU (Arab Maghreb Union) 3,90 28,46 96,10 2,15 28,71 97,85 1,94 39,20 98,06 4,36 45,07 95,64

CEN-SAD (Community of Sahel-Saharan States) 7,48 24,84 92,52 6,67 24,90 93,33 6,46 31,80 93,54 9,62 38,16 90,38

COMESA (Common Market for Eastern and Southern Africa) 5,70 52,51 94,30 4,80 56,95 95,20 5,24 49,16 94,76 9,87 52,35 90,13

EAC (East African Community) 17,50 37,14 82,50 17,28 40,73 82,72 18,95 47,15 81,05 21,75 44,96 78,25

ECCAS (Economic Community of Central African States) 1,39 65,51 98,61 0,91 53,53 99,09 0,86 72,98 99,14 2,08 66,38 97,92

ECOWAS (Economic Community of West African States) 9,43 20,49 90,57 9,15 25,36 90,85 9,54 30,82 90,46 11,67 38,34 88,33

IGAD (Intergovernmental Authority on Development) 11,81 51,06 88,19 13,07 40,98 86,93 11,22 45,60 88,78 17,11 43,73 82,89

SADC (Southern African Development Community) 14,66 15,08 85,34 11,98 15,97 88,02 10,83 20,96 89,17 21,07 11,65 78,93

ASEAN (Association of Southeast Asian Nations) 24,92 58,09 75,08 23,00 60,95 77,00 25,25 60,59 74,75 24,01 64,11 75,99

EU28 (European Union) 61,77 9,23 38,23 67,73 7,50 32,27 67,83 8,83 32,17 63,74 9,45 36,26

MERCOSUR (Southern Common Market) 19,07 66,12 80,93 18,06 72,05 81,94 11,61 79,90 88,39 14,03 63,88 85,97


18

Table 5: Import Patterns across Regional Economic Communities

Source : UNCTADStat (downloaded August 2017) .Note : Rest of the world includes African countries outside the bloc.

1995 2000 2005 2016

Regional Economic Community Intra-group Rest of the region Rest of the world Intra-group Rest of the region Rest of the world Intra-group Rest of the region Rest of the world Intra-group Rest of the region Rest of the world

AMU (Arab Maghreb Union) 3,62 31,52 96,38 3,13 36,48 96,87 2,97 40,78 97,03 2,73 41,08 97,27

CEN-SAD (Community of Sahel-Saharan States) 5,70 19,53 94,30 6,50 26,57 93,50 6,98 32,71 93,02 6,15 32,96 93,85

COMESA (Common Market for Eastern and Southern Africa) 4,16 70,60 95,84 4,99 71,39 95,01 6,19 66,40 93,81 5,63 60,31 94,37

EAC (East African Community) 10,54 15,37 89,46 12,58 46,44 87,42 10,56 53,44 89,44 7,11 49,27 92,89

ECCAS (Economic Community of Central African States) 2,61 82,80 97,39 2,48 88,40 97,52 2,53 88,47 97,47 3,58 80,96 96,42

ECOWAS (Economic Community of West African States) 8,40 20,29 91,60 12,53 21,06 87,47 12,47 25,57 87,53 9,95 29,76 90,05

IGAD (Intergovernmental Authority on Development) 7,02 36,48 92,98 9,56 42,73 90,44 5,87 55,99 94,13 3,98 60,86 96,02

SADC (Southern African Development Community) 14,99 9,87 85,01 20,25 6,65 79,75 17,61 10,94 82,39 21,03 11,41 78,97

ASEAN (Association of Southeast Asian Nations) 18,04 71,41 81,96 22,19 67,44 77,81 25,64 64,53 74,36 22,62 69,72 77,38

EU28 (European Union) 59,77 10,10 40,23 61,25 9,97 38,75 61,45 11,80 38,55 59,66 11,21 40,34

MERCOSUR (Southern Common Market) 17,68 66,03 82,32 20,06 61,73 79,94 19,19 60,36 80,81 15,19 62,84 84,81


19

Table 6: Product composition of trade by regional bloc

a. AMU

b. CENSAD

c. COMESA

d. EAC

Source : UNCTADStat (downloaded August 2017) .

Exports

Intra-Group Intra-African (outside bloc) Rest of World (excl. Africa)

1995 2016 1995 2016 1995 2016

Primary commodities 48,61 58,16 30,35 49,54 71,95 63,03

Manufactured goods 51,39 41,84 69,42 49,92 27,94 36,52

Other 0,01 0,00 0,23 0,54 0,11 0,45

Imports


1995 2016 1995 2016 1995 2016



Other 0,00 0,00 0,01 0,42 4,82 0,14

Exports


1995 2016 1995 2016 1995 2016



Other 0,61 0,78 0,23 0,23 0,25 0,56

Imports


1995 2016 1995 2016 1995 2016



Other 0,27 0,31 0,23 0,23 5,05 0,50

Exports


1995 2016 1995 2016 1995 2016



Other 0,08 2,13 0,31 4,51 0,25 2,06

Imports


1995 2016 1995 2016 1995 2016



Other 0,09 0,49 0,07 0,13 1,44 1,17

Exports

Intra-Group Intra-African (outside bloc)Rest of World (excl. Africa)

1995 2016 1995 2016 1995 2016



Other 0,17 1,51 0,55 0,27 0,56 0,46

Imports

Intra-Group Intra-African (outside bloc)Rest of World (excl. Africa)

1995 2016 1995 2016 1995 2016



Other 0,03 0,04 0,88 0,05 1,28 0,54


20

e. ECCAS

f. ECOWAS

g. IGAD

h. SADC

Source : UNCTADStat (downloaded August 2017) .

Exports


1995 2016 1995 2016 1995 2016



Other 0,03 0,06 5,97 0,39 -0,13 1,55

Imports


1995 2016 1995 2016 1995 2016



Other 0,12 0,13 0,17 0,21 1,11 1,71

Exports


1995 2016 1995 2016 1995 2016



Other 0,44 0,02 0,42 0,33 0,17 0,36

Imports


1995 2016 1995 2016 1995 2016



Other 0,29 0,02 2,42 0,48 5,99 0,18

Exports


1995 2016 1995 2016 1995 2016



Other 0,00 12,55 0,06 0,08 0,62 0,68

Imports


1995 2016 1995 2016 1995 2016



Other 0,00 9,33 0,17 0,36 1,34 0,89

Exports


1995 2016 1995 2016 1995 2016



Other 1,26 0,18 0,56 0,22 2,28 1,26

Imports


1995 2016 1995 2016 1995 2016



Other 1,41 0,19 0,22 0,10 7,22 5,88


21

However more research is needed to investigate how the setting of tariff barriers, both MFN and

preferential rates, and non-tariff barriers impact quantitatively on intra-bloc trade and intra-trade in the

African region. The Economic Commission for Africa found in 2010 that the costs of non-tariff barriers

exceeded the costs of tariff barriers in Africa. With the advent of the Trade Facilitation Agreement (TFA)

at the World Trade Organization, in international development circles, trade facilitation has been rising in

preeminence on the trade agenda as a driver for increasing the integration of developing economies into

regional and global markets.

II. The interface between regionalism and multilateralism in Africa: An empirical

perspective

The major focus of this research paper is to explore the interface between regionalism1 and multilateralism

in Africa empirically by addressing two empirical questions: (i) whether Most Favored Nation (MFN)

applied tariffs set by African countries exert an influence on the preferential tariffs2 that they impose on

members of their own bloc? and (ii) whether preferential tariffs set by African countries on their bloc

members have an influence on MFN applied tariffs set for members outside their regional economic bloc?

The remainder of this paper is organized as follows: first a brief review of the literature on the interface

between regionalism and multilateralism is provided; second the methodology used in the paper is laid

out; third the data used for the empirical analysis is described and fourth the estimation results are

described and discussed.

A. Brief literature review: Building blocs v/s Stumbling blocs3 debate

The issue of whether increased regionalism by countries may affect how they liberalize their trade

externally, that is to the rest of the world, though an old one, became prominent again in the early 2000s

as more and more countries were signing up to Regional Trade Agreements. As of October 2015 for

instance, there were 265 RTAs notified to the WTO (Acharya, 2016). At the time of writing the WTO

website reports that in the period 1948-1994, GATT had received 124 notifications of RTAs (relating to

trade in goods), and since the creation of the WTO in 1995, over 400 additional arrangements covering

trade in goods or services have been notified to the organization. While some economists like Larry

Summers viewed regionalism as a building bloc for multilateralism, others such as Jagdish Bhagwati

expressed scepticism, purporting to the argument that on the contrary regionalism could be a stumbling

bloc to multilateralism since regionalism could blunt the incentives of member countries to liberalize vis-

à-vis non-members. Both the theoretical and empirical economic literature yields ambiguous results on

1 Regionalism refers to PTAs defined by a geographic region (Bhagwati and Panagariya, 1996). 2 Due to data constraints, non-tariff barriers are not explicitly included in the analysis. Due to limited data

availability and issues over the quality of the data, the methodology outlined in the original proposal was

subsequently modified. 3 “The phraseology and conceptualization of PTAs that, in a dynamic time-path sense, contribute to the multilateral

freeing of trade either by progressively adding new members (down the PTA path to worldwide free trade) or by

prompting accelerated multilateral trade negotiations and are thus "building blocks" towards the multilateral

freeing of trade and those that do the opposite and hence are "stumbling blocks" to the goal of worldwide,

multilateral freeing of trade, owes to Bhagwati (1991, p. 77) and has been adopted by Lawrence (1991) and others”.

(Bhagwati and Panagariya, Page 3, 1996).


22

this “building bloc v/s stumbling bloc” debate. One view is that as countries form preferential agreements,

the preferential tariffs could lead to “trade diversion” , diverting trade away from more efficient producers

to less efficient ones (under classic Viner Theory). In a context of maximizing national welfare,

governments will match preferential tariffs with reductions in most-favored-nation, external, tariffs as a

way to bring imports back to the more efficient sources. Another view holds that in equilibrium, FTAs

could result in higher external tariffs by lowering the cost of FTA insiders to lobby against FTA outsiders

(Panagariya and Findlay, 1996). There is also the view that in customs unions, because of the

harmonization of external trade policies, CU members could exploit their joint market power in world

markets, leading to higher external tariffs (Bond and Syropoulos, 1996). Cadot, De Melo and Olarreaga

(2001) show that in a political economy setting where tariffs and duty drawbacks are endogenously

chosen through industry lobbying, full duty drawbacks are granted to exporters that use imported

intermediate goods in their production. This in turn decreases their incentives to counterlobby against high

tariffs on their inputs. Under a full duty drawback regime, tariffs on intermediate goods are irrelevant to

exporters because they are fully rebated. In equilibrium, higher tariffs will be observed on these goods.

However the creation of a regional trading bloc alters the incentives by eliminating duty drawbacks on

intraregional exports, which leads to lower tariffs for goods that intraregional exporters use as inputs.

They find evidence from MERCOSUR that the elimination of duty drawbacks for intra-regional exports

leads to increased counter lobbying against protection of intermediated goods and without this mechanism

the common external tariff would have been on average higher. The increased segmentation of production

in tasks, located in different geographic areas through the rise of Global Value Chains can indeed impact

on the interface between regionalism and multilateralism. For his part Limao (2007) shows that when

RTAs embrace non-trade objectives, they can become stumbling blocs to multilateralism since lower

external tariffs erode preferences and reduce incentives among members to engage in cooperation in non-

trade areas.

At an empirical level, Estevadeordal, Freund and Ornelas (2008) explored the interface between

regionalism and multilateralism in the context of 10 Latin American countries over the period 1990-2001.

Using data on preferential and most-favored-nation (MFN) applied tariffs, based on 100 ISIC 4-digit

industries, they investigated whether sectors that had relatively large preferences have been liberalized or

protected to the same extent as other sectors and whether these effects differ by type of RTA, free trade

areas (FTAs) or customs unions (CUs). Their results lent credence to the view that regionalism is a

building bloc for multilateralism. There was no clear evidence from their empirical investigations that

trade preferences lead to higher tariffs; on the contrary they found strong evidence that preferences

induced a faster decline in external tariffs in free trade areas.

Empirical research on the interface between regionalism and multilateralism based on the experiences of

developing countries have not been abundant of late and in the case of African RECs remain to the best of

our knowledge limited if not inexistent. The study by Foroutan dated from 1998 remains a classic in the

empirical literature on the interface between regionalism and multilateralism in developing countries even

though the study did not support the existence of a causal link between the two phenomena. Her study

showed that the Latin American countries that were members of an effective regional arrangement had

liberalized their trade regimes the most while the Middle East and Northern African countries had

implemented the least amount of trade liberalisation. Her study noted that the average rate of protection in

Sub-Saharan African had remained high at around 22 per cent with little difference between those

countries classified as belonging to an effective RTA and those that were not. The study found that


23

“belonging to a regional scheme was neither a necessary nor a sufficient condition for an open and

liberal trade regime” (Page 327, Foroutan, 1998).

Limited research on the interface between regionalism and multilateralism in Africa can perhaps be

explained by the fact that in the past, data on MFN and preferential tariff rates for African countries were

either limited in availability or unreliable and the fact that regional agreements were weakly implemented.

However since 2005, there have been an increased availability of more reliable data on preferential rates

for African countries in the WITS database and regional integration efforts have been intensified in some

regional economic blocs such as ECOWAS, EAC and SADC. The various RECs have gained in

eeffctiveness of late and over the past 10 years regional integration has been a policy priority for African

countries. All RECs, as can be seen from Table 4 have experienced an increase in their intra-bloc exports

since 2005.

B. Methodology of paper

This paper differs from other prior empirical literature in one major respect. While a few papers have

attempted to establish a causal link running from preferential tariffs on external, MFN tariffs, no paper, to

the best of our knowledge has attempted to establish a causal link the other way around. A priori it is

assumed that regionalism can serve as a building or stumbling bloc towards trade liberalization, while in

practice external liberalization pressures can also affect the degree and pace of regionalism in developing

countries such as in Africa. However the latter seems to have been occulted in past theoretical and

empirical research. Pressures can be exerted by large developed member countries on developing

countries at World Trade Organization (WTO) negotiations or through donor-led negotiations such as the

EU-led and WTO compatible Economic Partnership Agreements (EPAs) negotiations rounds, these

pressures often lead African countries with weaker bargaining and negotiating powers to engage in

commitments that place a burden on their administrative machinery and on their institutional and technical

capacities, blunting their incentives to engage in preferential trade policy and affecting their capacities at

implementing their regional trade agreements. Pressues to increase market access to non-African goods

and services can deter African countries from reducing their preferential rates on imports in order to avoid

a fiscal drain on government budgets in addition to having to fund external import bills from non-African

trading partners.

There is a literature centered on the impact of EPA negotiations on regionalism in Africa for instance that

argues that the insertion of MFN clauses in EPAs erode the scope for African countries to engage in

strategic partnership building and limit their space to develop preferential schemes with other countries.

African negotiators have often in the course of EPA negotiations pointed out the lack of coherence

between EPA commitments and regional integration processes. To start with, the regional groupings

within which African countries chose to negotiate their respective EPAs did not match the contours of the

formally recognised regional economic communities (RECs) to which they belong, the EAC excepted

(Bilal and Braun-Muzinger, 2008). If the reduction of tariffs towards the EU increases market access for

EU products in African markets, African countries will inevitably have to review their preferential tariffs

within their common strategy of building regional infant industries or to safeguard preferential market

access for African goods.


24

Multilateral think tanks such as UNCTAD and ECA have advised African countries to preserve their

industrial policy space in the course of WTO-led NAMA negotiations (UNCTAD and UNIDO, 2011).

African countries have been sensitized not to commit to trade liberalization policies that may preclude

their ability to formulate and effectively implement strategic regional industrial policies at later stages.

The tariff liberalization schedules African countries commit to at WTO circles is expected to affect the

future course and content of their regional integration policies. External trade liberalization by reducing

tariff revenues for countries can for example affect the timing and sequencing of reductions or increases in

their preferential rate schedules.

The paper by Estevadeordal, Freund and Ornelas (2008) provides a starting point for modelling

preferential rates in countries. Estevadeordal, Freund and Ornelas used the minimum preferential rate

offered to partners as a measure of preferential liberalization for a country j in a given sector or industry i

in year t, defined as follows:

Equation (1)

In our paper, the analysis is done for the aggregate economy as a whole in order to cover as many African

countries as possible in the analysis, given that disaggregated industry-level data on preferential rates is

not as equally reliable for all countries4. In addition, while Estevadeordal, Freund and Ornelas treats all

partners equally (assuming no strategic setting of preferential rates based on who the partner is), in this

paper the preferential rates are distinguished independently for 3 types of partners : African trading

partners that share a regional economic bloc with the given country j (ii) African trading partners that do

not share a regional economic bloc with a given country j but benefits from preferential rates and (iii) non-

African trading partners that benefit from a preferential tariff from country j. In setting preferential rates

for a given type of partner , country j strategically takes into account the MFN rate of other countries and

the preferential rates of other types of trading partners.

Estevadeordal, Freund and Ornelas (2008) models the setting of MFN rates as follows:

Equation (2)

Where: MFN ijt = MFN rate for country j in industry i in year t, PREF ijt-1 refers to the preferential tariff set

by country j on sector i imports from RTA partner in period t; αjt refers to country j year fixed effects such

as broad programs of trade liberalization that may have taken place and economic shocks that could affect

tariffs across industries in specific countries in specific periods, αij refers to country-industry fixed effects

meant to capture overall economic, political and historical factors that influence the level of protection

across industries in a given industry and country and the term αij.t to capture trends in these factors.

4 In a later paper, the author will extend the analysis to include disaggregated industry-level data for specific

countries for which reliable data are available.


25

Estevadeordal, Freund and Ornelas (2008) estimates a first difference of the above equation (2) to

eliminate the unobserved heterogeneity αij.

Their modelling strategy and the assumptions underlining it can be subject to certain criticisms:

▪ First it assumes a one-way causal relationship running from preferential rates to MFN tariffs in

which countries first set their preferential rates through negotiations (renegotiations are costly and

these rates are expected to be sticky) and then later set MFN rates. In their own words

“preferential rates are pre-determined relative to MFN rates”. Estevadeordal, Freund and Ornelas

further argue that: “ the tariffs that each member applies to imports from non-members, on the

other hand can be altered independently and at a faster pace”. The sequencing of the tariff setting

in their paper can be contested. In developing countries that have weak negotiating powers in

negotiations fora, and are subject to donor-imposed conditionalities, the possibility of

exogenously given MFN tariffs vis a vis large trading partners cannot be ruled out. MFN rates

can be treated as a given on the part of African countries. Large trading partners that are donors or

potential donors can strategically bargain for increased market access in these countries in return

for doling out their financial support. Furthermore, in the African context, the formation of

customs unions and free trade areas is still an ongoing process (negotiations are under way for

example for the TFTA, CFTA and ECOWAS CET) and external negotiations with partners such

as the European Union through the Economic Partnership Agreements can influence the

finalization of their preferential rate schedules. Causality running from applied MFN tariffs to

applied or minimum preferential tariffs cannot be ruled out. In an environment where the

formation of regional trade policies is still ongoing and external trade liberalization pressures are

still being felt, the sequencing of tariff setting is not as clear-cut as Estevadeordal, Freund and

Ornelas assumed in their paper for the context of Latin America in the 1990s.

▪ Though Estevadeordal, Freund and Ornelas (2008) acknowledge that renegotiatins of tariffs can

be costly, their modelling does not allow for inertia in tariff setting. Both MFN rates and

preferential rates are likely to be sticky from one year to the next and changes sluggish over time.

In this paper, we start by modelling the setting of preferential rates within the regional economic bloc by

country j in year t as follows:

Equation (3)

PREFBLOCMINjt = α1 + β1.PREFBLOCMINjt-1 + β2.PREFNONBLOCMINjt +

β3.PREFNONAFRICANMINjt + β4.MFNjt + β5.Uj + β6.Xjt + ejt

PREFBLOCMINjt corresponds to the minimum preferential rate set by country j at time t on the trading

partners that belong to the same regional economic bloc as country j. In the African context where there

are overlapping memberships of RECs, the miminum preferential rate is taken over the whole subset of

countries that share a REC with country j. Country j can belong to more than one REC at any given time.

The explanatory variable on the right hand side include a lagged dependent variable to account for inertia

in the tariff setting process and for sluggishness in changes over time5. In determining the minimum

5 If residual autocorrelation is present in OLS regressions, the use of a lagged dependent variable (LDV) can cause

the coefficients on explanatory variables to be biased downwards. Keel and Kelly (2005) contends that "while the

lagged dependent variable is inappropriate in some circumstances, it remains the best model for the dynamic models


26

preferential rate to apply in a given year t to an African preferential partner from the same REC

(PREFBLOCMINjt), country j takes into account the minimum preferential rate applied to its other

African trading partners that lie outside its REC(s) (PREFNONBLOCMINjt) and the minimum

preferential rate applied to its non-African trading partners (PREFNONAFRICANMINjt). The “effective”

preference margin that a preferential partner benefit from country j depends on preferences being accorded

to other partners. Similarly it also depends on the MFN rate applied to external trading partners. There are

strategic interactions among the various tariffs by type of development partner.

The variable Uj captures country fixed effects. All other factors held constant, the preferential tariffs of

country j may be affected by country specific fixed factors such as liberalization policies implemented by

the different RECs it belongs to and shocks, economic and political, afflicting these various RECs. Other

explanatory variables Xjt may include the extent of aid dependence of country j as well as its dependence

on loans - the conditionalities attached to loans contracted from multilateral institutions such as the World

Bank can impact on trade policy given that the World bank is an institution that generally influences trade

policy of the beneficiaries of its loans6 . Other variables may include non-tariff barriers, and /or trade and

transaction costs faced by country j. In negotiating and setting their MFN and preferential tariffs, countries

may choose to set their tariff levels to "compensate" for higher trade and transaction costs. It is recognized

that non-tariff barriers are quite prohibitive to regional trade on the African continent. On the other hand,

non-tariff barriers may also be strategically used by some countries to deliberately restrain market access

to imports (UNCTAD, 2013). For instance, Cadot et al. (2015) use data from a few African countries to

estimate average ad-valorem equivalents AVEs for Sanitary and Phyto-sanitary (SPS), Technical Barriers

to Trade (TBT) and other measures for Africa. Their study estimated that the total AVEs range from 8.8

per cent on textile and clothing to 21.7 per cent on machinery (UNCTAD, 2014).

C. Description of data used and State of MFN and Preferential tariffs in RECs

(i) Data

A database was constructed, based on data from WITS and the World Bank Development Indicators

(WDI) for the period 1993 to 20157.

Measures of preferential rates and MFN rates are taken from the WITS Database (See Table A.1 in Annex

A for details). The simple MFN rate is used over the weighted one in order to avoid noise in the data due

to the inclusion of the imports data and to mimimize the number of missing observations. Whenever data

on MFN and preferential rates were not available for some years after 1993, data available for the earliest

most often encountered by applied analysts". By including the LDV, we are likely to underestimate the true impact

and statistical significance of the other explanatory variables. 6 33 out of 54 African countries are categorized by the United Nations as Least Developed Countries (LDCs) and as

such are beneficiaries of the World Bank International Development Association (IDA) programmes that are targeted

to the worlds' 75 poorest countries . IDA actually provides loans and grants to 40 African countries. Cameroon, Cabo

Verde, Republic of Congo, Côte d'Ivoire, Ghana, Kenya, Nigeria and Zimbabwe are not LDCs but are beneficiaries

of IDA. Angola is the only African LDC that does not benefit from IDA grants and loans. 7 For Nigeria and South Africa, MFN data are available as early as 1988 and for Tunisia as from 1990. However the

final sample size used in the econometric analysis is constrained by the more limited availability of data on

preferential rates.


27

immediate year was used. Table B.b and Table B.c in Annex B provides more details on the availability

of the tariffs data.

REC dummy variables are constructed for each country j to reflect their belonging or not to each REC, the

ommitted REC is ECCAS. The dummy variables are AMU, CENSAD, COMESA, EAC, ECOWAS,

IGAD and SADC. These dummy variable are meant to capture country fixed effects Uj.

Net ODA received as a percentage of Gross National Income (GNI) ( ODAGNI) from the WDI is used as

a measure of aid dependence for each country j. Public and publicly guaranted (PPG) multitateral loans as

a percentage of GNI (PPGGNI) is included to capture dependence on multilateral institutions for loans and

grants.

Two measures of non-tariff barriers/ trade and transation costs are used from the WDI. These are the

number of documents needed by enterprises to import and to export. These measures are used as

indicators of trade facilitation within country j and indirect measures of non-tariff barriers to trade.

Table A.2 in Annex A provides summary statistics (mean, variance, count, minimum and maximum

values) by regional economic bloc of all the variables used in the analysis. These statistics are for the

whole sample of African countries for which data are available.

On average, MFN was 15.78 per cent across all African countries over the period 1993 to 2015 (with the

exception of South Africa and Nigeria where data are available as from 1988 and Tunisia where data are

available as from 1990). In the sample of available data over the period 1993 to 2015, on average the

minimum preferential rate for REC members (mean value of PREFBLOCMINjt) was 1.77, the mean value

of the minimum preferential rate for African non-REC members (mean value of PREFNONBLOCMINjt)

was 5.33 and the mean value of the minimum preferential rate for non-African partners (mean value of

PREFNONAFRICANMINjt) was 1.78. The mean value of ODAGNI stood at 9.96, that of PPGGNI at

28.91, that of number of documents used to import at 9.06 and mean number of documents used to export

at 7.51.

The average minimum preferential rate for REC members (mean value of PREFBLOCMINjt ) was lowest

in ECOWAS (0.98) and highest in IGAD (3.53). The average minimum preferential rate for African non-

REC members (mean value of PREFNONBLOCMINjt ) was lowest in SADC (2.97) and highest in IGAD

(9.21). The average minimum preferential rate for non-African partners (mean value of

PREFNONAFRICANMINjt ) was lowest in ECCAS (0.00) and highest in ECOWAS (3.90). The average

vale of MFN rate was lowest in SADC (11.87) and highest in AMU (22.08).

(ii) MFN rates in Africa

Over the last twenty years or so (1995 to 2015), applied MFN rates have followed either a downward or if

not a flat trend in most African countries. Annex B charts the applied MFN simple and weighted rates by

country for the period under study. Notable exceptions are in Comoros and Madagascar.

In 2015, the three lowest MFN rates stood at 0.00, 1.08 and 2.06 in Libya, Mauritius and the Seychelles

respectively and the three highest MFN rates were 20.83, 20.52 and 18.33 in Djibouti, Sudan and Algeria

respectively. Ten countries had an applied MFN rate in the band of 0 to 10 (Libya, Mauritius, Seychelles,

Lesotho, Namibia, South Africa, Swaziland, Botswana, Eritrea and Liberia). 22 countries had an applied

MFN rate above 10 and less than 15. Ten countries had an MFN rate above 15 and less than 20 (Comoros,


28

Zimbabwe, Ethiopia, Egypt, Gabon, Central African Republic, Chad, Equatorial Guinea, Cameroon and

Algeria) and only two (Sudan and Djibouti) applied an MFN rate above 20.

(iii) Minimum Preferential rates in Africa

Table 7 shows the mean values for PREFBLOCMINjt, PREFNONBLOCMINjt and

PREFNONAFRICANMINjt for the sample of 44 African countries for which data are available over the

period 1995 to 2015, and covering years for which data are available.

On average, the minimum preferential rate among members of a given REC (mean values of

PREFBLOCMINj) range between 0 (Algeria, Botswana, Comoros, Gabon, Ghana, Lesotho, Namibia,

Swaziland) and 16.26 (Ethiopia). In 2015, the miminum preferential rate was 0 for 36 countries. Liberia

and Ethiopia had the two highest minimum preferential rates at 10.69 per cent and 16.19 per cent

respectively.

On average, the minimum preferential rate for African partners outside a REC (mean values of

PREFNONBLOCMINj) range between 0 (Algeria and Namibia) to a high of 26.5 (Djibouti). In 2015, the

miminum preferential rate for African partners outside a REC was 0 for 12 countries. Swaziland and

Djibouti had the two highest minimum preferential rates at 23.24 and 26.50 per cent respectively.

On average, the minimum preferential rate for non-African partners (mean values of

PREFNONAFRICANMINj) range between 0 (Algeria, Burundi, Chad, Libya, Nigeria, Rwanda,

Tanzania, Tunisia and Uganda) to a high of 10 per cent (Central African Republic). In 2015, the minimum

preferential rate for non-African trading partners was 0 for 15 countries. Seychelles and The Gambia had

the two highest minimum preferential rate for non-African trading partners at 10.64 and 11.88 per cent

respectively.

What is clear from Table 7 is that in some African countries, the preference margin given to an African

trading partner sharing the same regional economic bloc over a non-African partner is not significant (e.g.

Kenya, Egypt, Libya, Mauritius and Rwanda). For the whole sample, based on available data, the mean

value of PREFBLOCMINjt stood at 1.77 based on 635 observations while the mean value of

PREFNONAFRICANMINjt was 1.78 based on 370 observations.


29

Table 7 Preferential Rates in Africa

Country Prefsrateblocmin Prefsratenonblocmin Prefsratenonafricanmin

1. Algeria

Mean 0 0 0

Count 11 23 7

2. Benin

Mean 0.085 .. ..

Count 10 0 0

3. Botswana

Mean 0 2.60 0.79

Count 15 15 15

4. Burkina Faso

Mean 0.08 .. ..

Count 10 0 0

5. Burundi

Mean 1.57 4.43 0

Count 14 14 7

6. Cameroon

Mean 2.11 .. ..

Count 21 0 0

7.Central African Republic

Mean 1.16 20 10

Count 21 19 19

8. Chad

Mean 1.17 5 0

Count 21 21 21

9. Comoros

Mean 0 .. ..

Count 8 0 0

10. Congo Republic

Mean 0 .. ..

Count 9 0 0

11.Côte d'Ivoire

Mean 0.11 .. ..

Count 10 0 0

12. Djibouti

Mean 0.96 26.5 2.17

Count 18 18 18

13. Egypt

Mean 3.05 1.83 1.81

Count 21 21 21

14. Equatorial Guinea

Mean 1.81 .. ..

Count 18 0 0

15. Eritrea

Mean 1.58 .. ..

Count 10 0 0

16.Ethiopia

Mean 16.26 16.26 ..

Count 8 8 0


30


17. Gabon

Mean 0 .. ..

Count 9 0 0

18. Gambia

Mean 10 15 11.88

Count 7 7 7

19.Ghana

Mean 0 .. ..

Count 9 0 0

20. Guinea Bissau

Mean 0.13 .. ..

Count 10 0 0

21.Kenya

Mean 4.54 5.11 0.18

Count 22 22 22

22.Lesotho

Mean 0 10.48 1.82

Count 15 15 15

23.Liberia

Mean 10.69 0.91 1.94

Count 3 4 4

24. Libya

Mean 6.95 15.6 0

Count 20 20 20

25.Madagascar

Mean 0.10 0.13 ..

Count 11 9 0

26. Malawi

Mean 0.77 2.92 ..

Count 20 20 0

27. Mali

Mean 0.09 .. ..

Count 10 0 0

28. Mauritius

Mean 2.39 2.39 0.18

Count 21 21 14

29. Morocco

Mean 0.07 0.66 0.07

Count 11 11 11

30. Mozambique

Mean 1.87 .. 0.05

Count 15 0 2

31. Namibia

Mean 0 0 2.04

Count 15 15 15

32. Niger

Mean 0.08 .. ..

Count 10 0 0


31


33.Nigeria

Mean 0.05 0.03 0

Count 21 21 21

34. Rwanda

Mean 0.55 0.55 0

Count 15 15 7

35. Senegal

Mean 0.08 .. ..

Count 10 0 0

36. Seychelles 0.29 0.06 0.97

Mean 11 11 11

Count

37. South Africa

Mean 1.75 0.64 2.83

Count 26 26 28

38. Sudan

Mean 0.80 0.80 3.21

Count 20 20 10

39. Swaziland

Mean 0 6.65 2.04

Count 15 15 15

40. Tanzania

Mean 1.61 2.27 0

Count 18 18 11

41. Togo

Mean 0.08 .. ..

Count 10 0 0

42. Tunisia

Mean 2.14 7.5 0

Count 14 14 14

43. Uganda

Mean 3.37 4.22 0

Count 22 22 15

44. Zimbabwe

Mean 4.98 3.02 3.55

Count 20 20 20

Total

Mean 1.77 5.33 1.78

Count 635 465 370

Source: Author based on data from WITS.


32

D. Estimation results

In this paper, the two single equations, Equation (3) and Equation (4) are estimated.

Equation (3)

PREFBLOCMINjt = α1 + β1.PREFBLOCMINjt-1 + β2.PREFNONBLOCMINjt +

β3.PREFNONAFRICANMINjt + β4.MFNjt + β5.Uj + β6.Xjt + ejt

Equation (4)

MFNjt = α1 + γ1.PREFBLOCMINjt + γ 2.PREFNONBLOCMINjt + γ 3.PREFNONAFRICANMINjt +

γ 4. MFNjt-1 + γ 5.Uj + γ 6.Xjt + vjt

In a first instance, the setting of minimum preferential rates for African partners sharing the same REC is

modelled and in a second instance the MFN rate accorded to external trading partners is also modelled. It

is hypothesized that there are contemporaneous strategic interactions in the setting of the preferential rates

for REC members (PREFBLOCMINjt) and the MFN rate (MFNjt). It is also hypothesized that there is

inertia in the tariff setting process since renegotiations are costly and that past values predetermine current

values of the tariffs. While Estevadeordal, Freund and Ornelas assume that renegotiations are costly only

for preferential rates and not for MFN rates, this paper assumes that renegotiations are costly for both.

Equation (3) was estimated using pooled Ordinary Least Squares, Generalized Least Squares (GLS), and

then Fixed effets (FE) and Random effects (RE) regression methods to account for unobserved

heterogeneity (Table 3a in Annex A). The use of lagged dependent variables8 in regression models often

lead to the peculiarity that the coefficient on the lagged dependent variable is large and statistically

significant. While its inclusion improves the overall fit of the model, the coefficients on the other

explanatory variables tend to become small and less statistically significant (Achen, 2001). The Arellano-

Bond (AB) regression technique is meant to address the issues of inconsistency in estimators that arise

when static panel data regression methods (such as fixed or random effects) are used in the presence of a

lagged dependent variable. We thus also report results using the Arellano Bond regression technique.

Greater weight is given to the interpretation of the results under the AB regression technique.

Table 3a. in Annex A report the results under pooled OLS, GLS, FE, RE and AB regression techniques for

two versions of Equation (3). In a first version, the equation is estimated without ODAGNI, PPGGNI and

the two measures of trade/transaction costs. In a second version, these 4 additional variables are included.

All independent variables are assumed to be exogenous.

8 According to Keele and Kelly (2005) " the properties of lagged dependent variable models estimated with OLS are

not perfect and, worse, these imperfections are not as well understood as they should be. As a result of the

uncertainties that surround these models, the lagged dependent variable model is often much maligned. In reality,

the problems with lagged dependent variable models are often trivial and confined to situations that are rarely

encountered in applied data". (Page 4, 2005).


33

In the first version of Equation (3), as expected the coefficient on lagged PREFBLOCMINjt is always

large and statistically significant. Under the AB regression technique, there is evidence at a 109 per cent

level that the current minimum preferential rate set for a REC member is positively determined by its

lagged value and the current MFN rate and negatively determined by the preferential rate accorded to non-

African trading partners. When ODAGNI, PPGGNI and the two measures of trade costs are added, there

is evidence at a 10 per cent level that the significant explanatory factors are: lagged past value of

PREFBLOCMINjt , MFN rate (but the coefficient changes sign and becomes negative), PPGGNI and the

two measures of trade costs. These last two additional variables as proxies of non-tariff barriers are

statistically significant with the same signs under all 5 regression methods.

Table 3c. reports results under AB, FE and RE regression methods but using instrumental variables for the

MFN rate, PREFNONBLOCMINjt and PREFNONAFRICANMINjt. The assumption of exogeneity of

these variables is relaxed. The one-period lagged values of the MFN rate and 3 types of preferential rates,

the dummy variables for RECs and the 4 additional variables - ODAGNI, PPGGNI and the two measures

of transaction costs - are chosen as instrumental variables. Using a 10 per cent level of significance, the

results using the AB regression technique are that the current minimum preferential rate set for African

REC members are positively explained by its own one-period lagged value, PPGGNI and the number of

documents to export and negatively determined by the MFN rate and the number of documents to import.

This is is in line with the results reported under Table 3a. There is no evidence to suggest that African

countries take into account the preferential rates of its other type of trading partners (African countries

outside their RECs or non-African trading partners) when setting their preferential rates for the African

trading partners with whom they share a REC.

There is preliminary evidence to suggest that African countries respond to reductions in the MFN rate

(that is to increased external liberalization), to increased non-tariff barriers to exports and to greater

dependence on multilateral loans by increasing the preferential rate (decreasing the preference margins) of

their REC trading partners. Multilateralism in this sense hurts regionalism. Greater dependence on

multiltateral finance, that often comes with conditionalities also hurts regionalism. Losses in export

competitiveness does not help regionalism neither, this is perhaps tied to a rationale to make up for lost

export revenues by avoiding import tariff reductions and avoid lost fiscal revenues. On the other hand,

when REC trading partners face increased non-tariff barriers to imports, they are "compensated" through

reductions in the preferential rate charged to them in order to increase their preference margins.

Table 3b. reports results for the estimation of Equation (4), using pooled OLS, GLS, FE, RE and AB

regression techniques, again under two versions. In the first version, MFN rate is explained by its own

one-year lagged value and by the 3 different types of preferential rates, PREFBLOCMINjt,

PREFNONBLOCMINjt and PREFNONAFRICANMINjt as well as by the dummy variables for RECs. In

the second version the 4 additional variables, ODAGNI, PPGGNI and the two measures of

trade/transaction cost are added. Table 3d. reports the results under AB, FE and RE regression methods

but using instrumental variables for PREFBLOCMINjt, PREFNONBLOCMINjt and

PREFNONAFRICANMINjt. The set of instruments are again the one-year lagged values of the MFN rate

and the 3 different types of preferential rates along with the set of dummy variable for the RECs and the 4

9 Given that the inclusion of lagged dependent variables tend to bias downwards the coefficients on the other

explanatory variables and gven the smallness of the final sample size, a 10 per cent level instead of a 5 per cent level

of significance is used for statistical inference.


34

additional variables. By giving greater weight to the results using instrumental variables, estimated under

the AB regression technique, evidence is found at a 10 per cent level of significance that the MFN rate is

determined positively by its own one-period lagged value, the number of documents to exports and

PPGGNI and negatively by the number of documents to import. A priori there is statistical evidence that

in the African context, regionalism neither hurts nor helps multilateralism. However in setting their MFN

rates, African countries take into account non-tariff barrier constraints and their dependence on

multilateral institutions for financial support. Losses in export competitiveness tend to lead African

countries to charge higher MFN rates while prohibitive barriers to imports lead them to "compensate"

importers with lower import tariffs.

Table 3e. reports a set of results under which Equation (3) and Equation (4) are simultaneously estimated

under three-stage least squares. Under columns (i), (ii), (v) and (vi), the endogenous variables are MFN

rate and PREFBLOCMINjt, with and without the inclusion of the 4 additional variables in the estimation.

In columns (iii), (iv), (vii) and (viii), the 2 other type of preferential rates (PREFNONBLOCMINjt and

PREFNONAFRICANMINjt) are also treated as endogenous, with and without the inclusion of the 4

additional variables in the estimation.

Focusing on columns (ii) and (vi), where only the MFN rate and PREFBLOCMINjt rate are treated as

endogenous variables (the exogenous variables of the model are used as instruments), and including the 4

additional variables, there is evidence at a 10 per cent level of significance that the MFN rate can be

explained positively only by its own one-period lagged value and the number of documents to export and

negatively by ODAGNI. None of the preferential rates are significant determinants of the MFN rate. On

the other hand, PREFBLOCMINjt rate is explained positively by its own one-period lagged value,

PREFNONAFRICANMINjt, ODAGNI, the number of documents to export and negatively by the number

of documents to import. For the first time there is evidence that there could be a strategic interaction

between the preferential rate set on REC members and the preferential rate set for non-African members,

with both moving in the same direction. There is also evidence for the first time that increases in

ODA/GNI facilitate reductions in the preferential rate towards REC members and contrary to PPG/GNI

does not hurt regionalism. One rationale could be that increases in aid eases the pain for African countries

to reduce their import tariffs on their fellow REC members since reductions in import tariff revenues can

be absorbed by larger amounts of aid.

When the 2 other types of preferential rates (PREFNONBLOCMINjt and PREFNONAFRICANMINjt ) are

also treated as endogenous, an interesting set of results emerges in columns (iv) and (viii). At a 10 per cent

level of significance, again there is no evidence that the MFN rate is affected by preferential rates of any

type. Regionalism is neutral to multilateralism in Africa. Only the number of documents to export is

positively causally correlated with the MFN rate. However for the first time there is evidence that there

could be strategic interactions between the setting of preferential rates towards REC members and towards

non-REC members and non-African trading partners. PREFBLOCMINjt is causally positively correlated

by PREFNONAFRICANMINjt but negatively causally correlated with PREFNONBLOCMINjt. This

could be interpreted as African countries extending preference margins in the same direction towards its

REC members and non-African trading partners but in opposite direction towards its African non-REC

members. There is also evidence that PREFBLOCMINjt is positively determined by the number of

documents to export, ODA/GNI and PPG/GNI but negatively determined by the number of documents to

imports. The previous result of a negative correlation between ODA/GNI and PREFBLOCMINjt is here

contradicted.


35

Based on all the above estimation results, a set of consistent inferences emerges, namely that in general,

regionalism neither hurts nor helps multilateralism but that multilateralism may be hurting regionalism in

Africa. It is also clear that non-tariff barriers or trade/transaction costs to export and import matter in the

setting of preferential rates towards REC members. This is coherent with the current empirical literature

and discourse by multilateral think-tanks that trade facilitation measures matter for regional integration in

Africa. There is also preliminary evidence that there is an interplay between dependence on aid and/or

dependence on multilateral loans and regional preferential rate setting in Africa. Conditionalities imposed

on aid or loan disbursements by externals could be either hurting regionalism or helping it, depending on

whether these grants and loans go towards propping up government revenues and facilitating reductions in

preferential import tariffs.

However these preliminary conclusions need to be confirmed by more research, using sectoral-level data

on preferential rates for countries for which reliable data are available on preferential rates at a sectoral

level. There are 16 countries that satisfy this condition and they are: Madagascar, Malawi, Mali,

Mauritius, Morocco, Namibia, Niger, Nigeria, Rwanda, Senegal, South Africa, Swaziland, Tanzania,

Togo, Tunisia and Uganda. The next step of this current research is to extend the above analysis based on

these 16 countries using data at a sectoral level.

To conclude, going back to the two empirical questions posed at the start of this section: i) whether Most

Favored Nation (MFN) applied tariffs set by African countries exert an influence on the preferential tariffs

that they impose on members of their own regional economic community? and (ii) whether preferential

tariffs set by African countries on their REC members have an influence on MFN applied tariffs set for

members outside their regional economic community? The answers, based on the available evidence is yes

to the first question and no to the second. While this paper finds no evidence that regionalism helps or

hurts multilateralism in Africa, it finds evidence on the other hand that multilateralism hurts regionalism

in Africa.


36

Conclusions and Recommendations

Summary of main parts of report

Section I.A of this report offers a brief review of the history of regional integration in Africa. Though

regional integration has a long standing history in Africa, so far progress at establishing a unified

continent as proposed in the Abuja Treaty has been slow both for economic and political reasons. There

are 8 main regional economic communities (RECs) recognized by the African Union as building blocs for

advancing continental integration in Africa. These are the Arab Maghreb Union (AMU), the Community

of Sahel-Saharan States (CEN-SAD), the Common Market for Eastern and Southern Africa (COMESA),

the Economic Community of Central African States (ECCAS), the Economic Community for Western

African States (ECOWAS), the Eastern African Community (EAC), the Inter-governmental Authority on

Government (IGAD), and the Southern African Development Community (SADC). Out of these 8 RECs,

so far in 2017, only EAC, ECOWAS and COMESA have established a Customs Union while ECCAS and

SADC are FTAs. However, their operationalization, within a linear model to regional integration, is yet to

become fully effective. There are several hurdles to regional integration in Africa and these range from the

geography of African trade, low trade complementarity, non-tariff barriers to trade, prevalence of large

informal economies and informal trade, insufficient infrastructure and lack of economic diversification

and productive capacities.

Section I.B reviews the state of intra-African trade by regional economic bloc for the period 1995 to 2015.

This section notes that, while the shares of intra-trade tend to be low within each bloc, a more substantial

level of trade occurs outside regional economic blocs within the region. Significant heterogeneity also

exists in intra-bloc trade performance among the 8 blocs. EAC, ECOWAS, IGAD and SADC had the

largest shares of intra-bloc exports both in 1995 and in 2016. EAC, ECOWAS and SADC were also the 3

blocs with the largest shares of intra-bloc imports both in 1995 and 2016. All RECs over the period had

increased their share of intra-bloc trade on the export side but on the import side, the picture is more

mixed; the share of intra-bloc imports fell in AMU, EAC, and IGAD. In all regional economic blocs,

intra-bloc exports are far more intensive in manufactures than exports with the rest of the world and this

holds both in 1995 and 2016. Intra-bloc imports on the other hand are less intensive in manufactures than

imports with the rest of the world, and this reflects the region’s poor and undiversified manufacturing

base.

Section II covers the major part of the Report. The major focus of this report is to explore the interface

between regionalism and multilateralism in Africa empirically by addressing two empirical questions: (i)

whether Most Favored Nation (MFN) applied tariffs set by African countries exert an influence on the

preferential tariffs that they impose on members of their own bloc? and (ii) whether preferential tariffs set

by African countries on their bloc members have an influence on MFN applied tariffs set for members

outside their regional economic bloc?

Section II.A offers a brief review of the literature on the interface between regionalism and

multilateralism. It reviews briefly the debate among economists as to whether regionalism is a building or

a stumbling bloc to multilateralism. It notes that both the theoretical and empirical economic literature

yields ambiguous results on that debate. It highlights the result found by Estevadeordal, Freund and


37

Ornelas (2008) in the context of Latin America for the period 1990-2001 that regionalism is a building

bloc for multilateralism. It notes that empirical research on the interface between regionalism and

multilateralism based on the experiences of developing countries have not been abundant of late and in the

case of African RECs remains limited if not inexistent.

Section II. B outlined the methodology used in this paper to address the two empirical questions

mentioned above. It notes that the paper differs from other prior empirical literature in one major respect.

While a few papers have attempted to establish a causal link running from preferential tariffs on external,

MFN tariffs, this paper attempts to establish a causal link the other way around. This paper recognizes that

external liberalization pressures can also affect the degree and pace of regionalism in developing countries

such as in Africa. The paper distinguishes among preferential rates for 3 types of partners : African trading

partners that share a regional economic bloc with the given country j (ii) African trading partners that do

not share a regional economic bloc with a given country j but benefits from preferential rates and (iii) non-

African trading partners that benefit from a preferential tariff from country j. It is assumed that in setting

preferential rates for a given type of partner, country j strategically takes into account the MFN rate it sets

for other countries and the preferential rates of other types of trading partners. The paper sets out two

equations to be estimated by econometric methods that hypothesizes the determination of MFN rates and

the minimum preferential rate accorded by a given country j to its REC trading partners.

In a first instance, the setting of minimum preferential rates for African partners sharing the same REC is

modelled and in a second instance the MFN rate accorded to external trading partners is also modelled. It

is hypothesized that there are contemporaneous strategic interactions in the setting of the preferential rates

for REC members (PREFBLOCMINjt) and the MFN rate (MFNjt). It is also hypothesized that there is

inertia in the tariff setting process since renegotiations are costly and that past values predetermine current

values of the tariffs.

Section II.C described the data used for the empirical analysis and Section II.D described and discussed

the estimation results. A database was constructed, based on data from WITS and the World Bank

Development Indicators (WDI) for the period 1993 to 2015. Measures of preferential rates and MFN rates

are taken from the WITS Database. On average, MFN was 15.78 per cent across all African countries over

the period 1993 to 2015. In the sample of available data over the period 1993 to 2015, on average the

minimum preferential rate for REC members was 1.77, the mean value of the minimum preferential rate

for African non-REC members was 5.33 and the mean value of the minimum preferential rate for non-

African partners was 1.78. The average minimum preferential rate for REC members was lowest in

ECOWAS (0.98) and highest in IGAD (3.53). The average minimum preferential rate for African non-

REC members was lowest in SADC (2.97) and highest in IGAD (9.21). The average minimum

preferential rate for non-African partners was lowest in ECCAS (0.00) and highest in ECOWAS (3.90).

The average vale of MFN rate was lowest in SADC (11.87) and highest in AMU (22.08).

There is preliminary evidence to suggest that African countries respond to reductions in the MFN rate

(that is to increased external liberalization), to increased non-tariff barriers to exports and to greater

dependence on multilateral loans by increasing the preferential rate (decreasing the preference margins) of

their REC trading partners. Multilateralism in this sense hurts regionalism. Greater dependence on

multiltateral finance, that often comes with conditionalities also hurts regionalism. Losses in export

competitiveness does not help regionalism neither, this is perhaps tied to a rationale to make up for lost

export revenues by avoiding import tariff reductions and avoid lost fiscal revenues. On the other hand,


38

when REC trading partners face increased non-tariff barriers to imports, they are "compensated" through

reductions in the preferential rate charged to them in order to increase their preference margins.

There is also statistical evidence that in the African context, regionalism neither hurts nor helps

multilateralism. However in setting their MFN rates, African countries take into account non-tariff barrier

constraints and their dependence on multilateral institutions for financial support. Losses in export

competitiveness tend to lead African countries to charge higher MFN rates while prohibitive barriers to

imports lead them to "compensate" importers with lower import tariffs.

Based on all the estimation results, a set of consistent inferences emerges, namely that in general,

regionalism neither hurts nor helps multilateralism but that multilateralism may be hurting regionalism in

Africa. It is also clear that non-tariff barriers or trade/transaction costs to export and import matter in the

setting of preferential rates towards REC members. This is coherent with the current empirical literature

and discourse by multilateral think-tanks that trade facilitation measures matter for regional integration in

Africa. There is also preliminary evidence that there is an interplay between dependence on aid and/or

dependence on multilateral loans and regional preferential rate setting in Africa. Conditionalities imposed

on aid or loan disbursements by externals could be either hurting regionalism or helping it, depending on

whether these grants and loans go towards propping up government revenues and facilitating reductions in

preferential import tariffs.

Concluding statement

Going back to the two empirical questions posed in the paper: i) whether Most Favored Nation (MFN)

applied tariffs set by African countries exert an influence on the preferential tariffs that they impose on

members of their own regional economic community? and (ii) whether preferential tariffs set by African

countries on their REC members have an influence on MFN applied tariffs set for members outside their

regional economic community? The answers, based on the available evidence is yes to the first question

and no to the second. While this paper finds no evidence that regionalism helps or hurts multilateralism in

Africa, it finds evidence on the other hand that multilateralism hurts regionalism in Africa.

Limitations

However the empirical analysis of this paper suffers from several limitations and these limitations will

have to be addressed in subsequent drafts:

▪ There are issues with the availability of data on preferential rates in Africa. The econometric

findings are based on a small sample size due to a large number of missing observations for some

countries. The preliminary conclusions presented in this paper need to be confirmed by more

research, using sectoral-level data on preferential rates for countries for which reliable data on

preferential rates are available at a sectoral level. There are 16 countries that satisfy this condition

and they are: Madagascar, Malawi, Mali, Mauritius, Morocco, Namibia, Niger, Nigeria, Rwanda,

Senegal, South Africa, Swaziland, Tanzania, Togo, Tunisia and Uganda. The next step of this

current research is to extend the above analysis based on these 16 countries using data at a sectoral

level.


39

▪ There are econometric issues to be addressed. The choice of instrumental variables needs to be

refined. Weighted regressions could also be used, whereby greater weight is given to observations

with more reliable information.

Recommendations

▪ This report could be used by the organization, especially UNCTAD to make specific policy

recommendations to African policy makers on the interface between regionalism and

multilateralism. African countries should strategically set their MFN rates and the preferential

rates of their different types of trading partners with a view to deepening regional integration in

Africa. Policies for removing non-tariff barriers or lowering trade costs must be effectively

implemented in order to boost intra-African trade.


40

Annex A-Estimation results


41

Table A.1: List of variables and basic statistics

Variable name Description Datasource

MFN simple Simple MFN rate (Partner:World) WITS database

Prefsrateblocmin Minimum Preferential rate (based on tariff year), minimum rate

across all African partners (for which data are available) that share a

REC with the country

" "

Prefsratenonblocmin Minimum Preferential rate (based on tariff year), minimum rate

across all African partners (for which data are available) that does not

share a REC with the country

" "

Prefsratenonafricamin Minimum Preferential rate (based on tariff year), minimum rate

across all non-African partners (for which data are available)

" "

Dummy variables

REC:

" "

AMU Dummy variable, equals one if the country is a member of AMU Economic

commission for

Africa

CENSAD Dummy variable, equals one if the country is a member of CENSAD " "

COMESA Dummy variable, equals one if the country is a member of COMESA " "

EAC Dummy variable, equals one if the country is a member of EAC " "

ECOWAS Dummy variable, equals one if the country is a member of ECOWAS " "

IGAD Dummy variable, equals one if the country is a member of IGAD " "

SADC Dummy variable, equals one if the country is a member of SADC " "

No. Docs to import Documents to import (number): All documents required per shipment

to import goods are recorded. It is assumed that the contract has

already been agreed upon and signed by both parties. Documents

required for clearance by government ministries, customs authorities,

port and container terminal authorities, health and technical control

agencies and banks are taken into account.

World Bank

Development

Indicators

(WDI)

ODA/GNI Net ODA received (% of GNI): Net official development assistance

(ODA) consists of disbursements of loans made on concessional

terms (net of repayments of principal) and grants by official agencies

of the members of the Development Assistance Committee (DAC),

by multilateral institutions, and by non-DAC countries to promote

economic development and welfare in countries and territories in the

DAC list of ODA recipients. It includes loans with a grant element of

at least 25 percent (calculated at a rate of discount of 10 percent).

" "

PPG/GNI PPG, multilateral (DOD, current US$)/GNI: PPG =Public and

publicly guaranteed multilateral loans include loans and credits from

the World Bank, regional development banks, and other multilateral

and intergovernmental agencies. Excluded are loans from funds

administered by an international organization on behalf of a single

donor government; these are classified as loans from governments.

Data are in current U.S. dollars.

" "

Source: Author.


42

Table A.2a. Summary Statistics: All countries

Statistics MFNSimple2 Prefsrate

blocmin

Prefsrate

nonblocmin

Prefsrate

nonafricanmin

Docexport Docimport ODA

GNI

PPG

GNI

Mean 15.78 1.77 5.33 1.78 7.51 9.06 9.96 28.91

Count 930 635 465 370 429 429 977 899

Min 0 0 0 0 4 5 -0.26 0

Max 70.59 16.6 31.25 23.81 14 21 181.10 215.97

Variance 71.64 12.40 57.80 16.20 3.47 7.83 165.37 854.07

Table A.2b. Summary Statistics: AMU


blocmin

Prefsrate

nonblocmin

Prefsrate

nonafricanmin


GNI

PPG

GNI

Mean 22.08 3.03 6.25 0.02 5.83 7.10 0.96 12.21

Count 95 56 68 52 30 30 76 69

Min 0 0 0 0 4 6 0.01 0.00

Max 64.97 15 17.33 0.25 9 9 2.55 24.22

Variance 156.28 23.77 45.59 0.00 3.32 1.96 0.43 48.55

Table A.2c. Summary Statistics: CENSAD


blocmin

Prefsrate

nonblocmin

Prefsrate

nonafricanmin


GNI

PPG

GNI

Mean 16.44 1.46 8.99 2.36 7.33 9.17 9.48 31.80

Count 443 281 172 162 200 200 451 443

Min 0 0 0 0 4 5 0.01 1.23

Max 70.59 15 26.5 11.88 14 17 78.71 215.97

Variance 89.59 9.18 84.01 15.46 3.42 9.26 79.00 794.31

Table A.2d. Summary Statistics: ECOWAS


blocmin

Prefsrate

nonblocmin

Prefsrate

nonafricanmin


GNI

PPG

GNI

Mean 13.99 0.98 8.25 3.90 7.57 9.94 13.51 38.49

Count 283 162 72 72 139 139 316 316

Min 3.35 0 0.03 0 6 6 0.42 1.23

Max 70.59 10.69 20 11.88 11 17 181.10 215.97

Variance 38.88 6.13 67.61 25.50 2.54 9.69 295.69 1153.42


43

Table A.2e. Summary Statistics: SADC


blocmin

Prefsrate

nonblocmin

Prefsrate

nonafricanmin


GNI

PPG

GNI

Mean 11.87 1.00 2.97 1.53 7.06 7.78 7.21 21.09

Count 211 171 156 126 100 100 230 183

Min 1.08 01 0 0 4 5 -0.26 0

Max 30.74 12.49 31.25 23.81 11 17 52.00 140.27

Variance 46.51 5.63 37.89 13.94 2.95 4.72 88.08 672.33

Table A.2f. Summary Statistics: EAC


blocmin

Prefsrate

nonblocmin

Prefsrate

nonafricanmin


GNI

PPG

GNI

Mean 18.12 3.00 3.40 0.91 7.93 10.65 14.65 36.08

Count 132 111 111 82 60 60 138 138

Min 7.84 0 0 0 7 9 2.45 7.99

Max 41.73 16.60 11.79 23.68 13 21 94.95 140.97

Variance 70.72 17.70 11.94 20.11 2.13 8.74 122.09 893.87

Table A.2g. Summary Statistics: ECCAS


blocmin

Prefsrate

nonblocmin

Prefsrate

nonafricanmin


GNI

PPG

GNI

Mean 17.65 1.39 4.43 0 8.56 9 8.70 27.66

Count 107 71 14 7 50 50 115 92

Min 11.86 0 0 0 5 6 -0.19 1.52

Max 23.43 4.55 8.33 0 11 12 40.41 140.97

Variance 5.04 3.44 8.08 0 4.13 3.88 121.00 1302.26

Table A.2h. Summary Statistics: COMESA


blocmin

Prefsrate

nonblocmin

Prefsrate

nonafricanmin


GNI

PPG

GNI

Mean 16.76 2.74 5.94 1.27 7.70 9.05 10.66 30.05

Count 356 276 256 180 160 160 361 330

Min 0 0 0 0 4 5 -0.26 2.66

Max 58.44 16.60 26.50 23.68 14 21 94.95 141.0

Variance 92.53 19.70 63.14 12.76 4.26 8.30 103.28 865.87


44

Table A.2i. Summary Statistics: IGAD


blocmin

Prefsrate

nonblocmin

Prefsrate

nonafricanmin


GNI

PPG

GNI

Mean 17.84 3.53 9.21 1.15 8 9.7 10.77 23.72

Count 130 100 90 65 60 60 124 123

Min 5.38 0 0 0 5 5 1.02 3.49

Max 35.20 16.60 26.50 11.03 14 20 38.0 60.85

Variance 74.17 25.40 100.31 4.04 3.83 9.64 60.97 218.38


45

Table A.3a.: Single-equation regressions (all independent variables assumed to be exogenous)

Dependent variable: Minimum Preferential rate vis-a-vis REC members (prefsrateblocmin)

Variables in levels Pooled

OLS

GLS* Fixed

effects

Random

effects

Arellano-

Bond

Lagged Prefsrateblocmin 0.82(0.00) 0.50(0.00) 0.86(0.00) 0.58(0.00) 0.70(0.00) 0.42(0.00) 0.82(0.00) 0.50(0.00) 0.70 (0.00) 0.42(0.00)

MFN simple 0.03(0.04) -0.03(0.35) 0.002(0.76) 0.01(0.37) 0.08(0.00) -0.07(0.14) 0.03(0.03) -0.03(0.34) 0.08(0.00) -0.07(0.08)

Prefsratenonblocmin 0.01(0.29) -0.02(0.35) 0.001(0.64) -0.004(0.63) 0.02(0.43) -0.01(0.72) 0.01(0.29) -0.02(0.35) 0.03(0.45) -0.01(0.64)

Prefsratenonafricanmin -0.01(0.80) 0.16(0.00) 0.002(0.72) 0.09(0.00) -0.05(0.12) 0.01(0.81) -0.01(0.80) 0.16(0.00) -0.06(0.10) 0.02(0.77)

Dummy variables REC:

AMU 0.17(0.71) 0.32(0.58) -0.09(0.67) 0.53(0.05) - - 0.17(0.71) 0.32(0.58) - -

CENSAD -0.64(0.15) 0.07(0.88) -0.13(0.49) -0.39(0.03) - - -0.64(0.15) 0.07(0.88) - -

ECOWAS 0.42(0.39) 1.29(0.02) -0.06(0.79) 1.44(0.00) - - 0.42(0.39) 1.29(0.02) - -

SADC -0.20(0.70) -0.12(0.83) -0.21(0.32) 0.31(0.22) - - -0.20(0.70) -0.12(0.83) - -

EAC -0.09(0.82) 0.58(0.20) -0.17(0.31) 0.42(0.04) - - -0.09(0.82) 0.58(0.20) - -

COMESA 0.26(0.37) -0.18(0.61) -0.02(0.76) -0.14(0.18) - - 0.26(0.37) -0.18(0.60) - -

IGAD -0.36(0.27) -0.27(0.39) -0.15(0.44) 0.20(0.43) - - -0.36(0.26) -0.27(0.39) - -

Additional variables: - - - - - -

No. Docs to import - -0.34(0.00) - -0.23(0.00) - -0.71(0.00) - -0.34(0.00) - -0.72(0.00)

No. Docs to export 0.32(0.00) 0.10(0.02) - 1.15(0.00) 0.32(0.00) - 1.18(0.00)

ODA/GNI - 0.04(0.03) - 0.03(0.02) - 0.03(0.36) - 0.04(0.03) - 0.02(0.43)

PPG/GNI - 0.02(0.14) - 0.01(0.17) - 0.03(0.03) - 0.02(0.14) - 0.03(0.02)

Constant -0.21(0.74) 0.48(0.62) 0.18(0.42) 0.44(0.23) -0.76(0.01) -1.20(0.35) -0.21(0.74) 0.48(0.62) -0.91(0.01) -1.18

R squared 0.78 0.75 - - 0.76 0.34 0.78 0.75 - -

F-stat - - - - 144.33 12.66 - - - -

Wald Chi-sq - - 1242.40 560.28 - - 1222.54 512.09 557.75 129.20

No.observations. 348 183 348 183 348 183 348 183 323 161

Note: p-levels are in parentheses.* Assumes heteroskedastic error structure with no cross-sectional correlation.


46

Table A.3b.: Single-equation regressions (all independent variables assumed to be exogenous)

Dependent variable: MFN rate (mfnsimple)

Variables in levels

Pooled

OLS

GLS* Fixed

effects

Random

effects

Arellano-

Bond

Lagged MFN rate 0.71 (0.00) 0.67 (0.00) 0.82(0.00) 0.77 (0.00) 0.63 (0.00) 0.56 (0.00) 0.71 (0.00) 0.58(0.00) 0.58 (0.00) 0.57 (0.00)

Prefsratebloc 0.14(0.04) -0.01 (0.93) 0.05(0.10) -0.003 (0.95) 0.34 (0.00) 0.02 (0.84) 0.14 (0.04) -0.01 (0.93) 0.24 (0.02) 0.01 (0.80)

Prefsratenonblocmin 0.02(0.45) 0.01 (0.63) 0.01(0.10) -0.005 (0.66) 0.03 (0.61) -0.01 (0.75) 0.02 (0.45) 0.001 (0.98) -0.01 (0.90) -0.01 (0.75)

Prefsratenonafricanmin -0.05(0.38) 0.07 (0.20) -0.02(0.08) 0.01 (0.72) 0.03 (0.71) 0.03 (0.71) -0.05 (0.38) 0.06 (0.33) 0.05 (0.54) 0.03 (0.65)

Dummy variables

REC:

AMU -3.66 (0.00) -0.14 (0.85) -1.45(0.01) 0.36 (0.42) - - -3.66 (0.00) 0.49(0.73) - -

CENSAD 1.54(0.16) 1.66 (0.00) 1.38(0.01) 1.07 (0.01) - - 1.54 (0.16) 2.50(0.01) - -

ECOWAS -3.12(0.01) -1.98 (0.01) -0.49(0.36) -0.50 (0.24) - - -3.12(0.01) -1.65(0.23) - -

SADC -3.51(0.01) -2.06 (0.00) -0.80(0.10) -0.88 (0.01) - - -3.51(0.01) -2.30(0.07) - -

EAC -0.51(0.62) 0.86 (0.13) 0.45(0.21) 0.48 (0.15) - - -0.51 (0.62) 1.54(0.11) - -

COMESA -2.04(0.00) -1.18 (0.01) -0.56(0.07) -0.35(0.06) - - -2.04 (0.00) -1.46(0.10) - -

IGAD 0.21(0.79) -0.16 (0.69) 0.34(0.33) -0.07 (0.77) - 0.21(0.79) -0.05(0.94) - -

Additional variables: - - - - -

No. Docs to import - -0.05 (0.50) - 0.05(0.26) - -0.70 (0.00) - -0.23(0.03) - -0.71 (0.00)

No. Docs to export 0.49 (0.00) 0.22 (0.01) 1.53 (0.00) - 0.74(0.00) 1.53 (0.00)

ODA/GNI - -0.04 (0.11) - -0.02 (0.08) - -0.04(0.28) - -0.04(0.17) - -0.04 (0.15)

PPG/GNI - 0.01 (0.30) - 0.01 (0.13) - 0.04 (0.04) - 0.01(0.32) - 0.04 (0.01)

Constant 6.29(0.00) 1.61 (0.20) 2.18 (0.00) 0.76 (0.24) 4.31 (0.00) 0.84 (0.58) 6.29 (0.00) 2.33(0.25) 5.55 (0.00) 0.81 (0.48)

R squared 0.76 0.92 - - 0.73 0.70 0.76 0.92 - -

F-stat 103.74 - - - 102.58 32.20 - - - -

Wald Chi-sq - - 14739.61 8370.51 - - 1141.12 779.07 248.68 442.20

No.observations. 365 186 365 186 365 186 365 186 340 164

Note: p-levels are in parentheses.* Assumes heteroskedastic error structure with no cross-sectional correlation.


47

Table A.3c.: Single-equation regressions (a few independent variables are endogenous)

Dependent variable: Minimum Preferential rate vis-a-vis REC members (prefsrateblocmin)

Arellano-

Bond

IV-Fixed

effects

IV-

Random

effects

Lagged Prefsrateblocmin 0.70 (0.00) 0.42 (0.00) 0.73(0.00) 0.40(0.00) 0.83(0.00) 0.45(0.00)

MFN simple 0.08(0.00) -0.07(0.09) 0.05 (0.10) 0.0001(1.00

)

0.02(0.33) -0.01(0.82)

Prefsratenonblocmin 0.02(0.43) -0.01(0.68) 0.06(0.16) -0.04(0.78) 0.005(0.79) -0.08(1.00)

Prefsratenonafricanmin

-0.05(0.11) 0.01(0.79) 0.06(0.44) -0.06(0.90) 0.08(0.06) 0.27(0.00)


AMU - - - - 0.37(0.47) 0.73(0.33)

CENSAD - - - - -0.44(0.36) -0.02(0.97)

ECOWAS - - - - 0.31(0.56) 1.69(0.02)

SADC - - - - -0.07(0.91) 0.20(0.78)

EAC - - - - 0.10(0.82) 0.67(0.22)

COMESA - - - - 0.32(0.31) 0.03(0.95)

IGAD - - - - -0.25(0.47) -0.41(0.29)

Additional variables: - -

No. Docs to import - -0.71(0.00) - -0.71(0.00) - -0.38(0.00)

No. Docs to export - 1.15(0.00) - 1.13(0.00) - 0.41(0.00)

ODA/GNI - 0.03(0.29) - 0.03(0.30) - 0.05(0.03)

PPG/GNI - 0.03(0.02) - 0.03(0.03) - 0.03(0.06)

Constant -0.76(0.01) -1.20 (0.29) -0.85(0.05) -1.76(0.23) -0.33(0.66) -0.42(0.75)

R squared - - 0.74 0.29 0.78 0.74

F-stat - - - - - -

Wald Chi-sq 566.78 129.80 904.68 143.00 1177.54 427.59

No.observations. 323 161 340 178 340 178

Endogenous variables (AB): MFNsimple, Prefsratenonblocmin, Prefsratenonafricanmin

Instrumented variables (IV): MFNsimple, Prefsratenonblocmin, Presratenonafricanmin

Instruments (IV): lagged prefsrateblocmin, lagged prefsratenonblocmin, lagged prefsratenonafricanmin, lagged MFNsimple, REC dummy variables +

ODA/GNI, PPGGNI, Docexport, Docimport when included.


48

Table A.3d.: Single-equation regressions (a few independent variables are endogenous)

Dependent variable: MFN rate (mfnsimple)

Arellano-

Bond

IV-Fixed

effects

IV-

Random

effects

Lagged MFNsimple 0.63(0.00) 0.56(0.00) 0.54(0.00) 0.55(0.00) 0.65(0.00) 0.58(0.00)

Prefsrateblocmin 0.35(0.00) 0.02(0.79) 0.44(0.00) 0.49(0.00) 0.14(0.06) 0.14(0.26)

Prefsratenonblocmin 0.03(0.59) -0.01(0.68) -0.02(0.82) 0.07(0.68) 0.02(0.55) 0.03(0.69)


0.02(0.79) 0.03(0.63) 0.18(0.23) -0.14(0.81) 0.01(0.89) 0.02(0.89)


AMU - - - - -4.11(0.00) 0.04(0.97)

CENSAD - - - - 1.83(0.07) 2.50(0.00)

ECOWAS - - - - -4.18(0.00) -2.54(0.05)

SADC - - - - -4.08(0.00) -2.46(0.04)

EAC - - - - -0.66(0.48) 1.43(0.12)

COMESA - - - - -2.20(0.00) -1.48(0.06)

IGAD - - - - 0.40(0.59) -0.11(0.88)

Additional variables: - -

No. Docs to import - -0.70(0.00) - -0.65(0.00) - -0.10(0.38)

No. Docs to export - 1.53(0.00) - 1.54(0.00) - 0.61(0.01)

ODA/GNI - -0.04(0.16) - -0.07(0.10) - -0.05(0.09)

PPG/GNI - 0.04(0.01) - 0.01(0.62) - -0.0003(1.00)

Constant 4.31(0.00) 0.84(0.47) 5.40(0.00) 0.64(0.73) 7.47(0.00) 2.57(0.23)

R squared - - 0.72 0.62 0.80 0.92

F-stat - - - - - -

Wald Chi-sq 319.16 442.41 6372.20 17456.38 1298.47 867.94

No.observations. 340 164 340 178 340 178

Endogenous variables: Prefsrateblocmin, Prefsratenonblocmin, Prefsratenonafricanmin

Instrumented variables (IV): MFNsimple, Prefsratenonblocmin, Presratenonafricanmin

Instruments (IV): lagged prefsrateblocmin, lagged prefsratenonblocmin, lagged prefsratenonafricanmin, lagged MFNsimple, REC

dummy variables + ODA/GNI, PPGGNI, Docexport, Docimport when included.


49

Table A.3e.: Simultaneous estimations

Dependent variable: Prefsrateblocmin Dependent variable: MFNsimple

(i) (ii) (iii) (iv) (v) (vi) (vii) (viii)

Lagged MFNsimple - - - - 0.65(0.00) 0.67 (0.00) 0.65(0.00) 0.69(0.00)

Lagged Prefsrateblocmin 0.83 (0.00) 0.50(0.00) 0.83(0.00) 0.47(0.00) - - - -

MFNsimple 0.02(0.42) -0.03(0.48) 0.02(0.32) -0.01(0.79) - - - -

Prefsrateblocmin - - - - 0.14(0.05) 0.03(0.73) 0.14(0.05) 0.01(0.95)

Prefsratenonblocmin 0.01(0.25) -0.02(0.32) 0.005(0.78) -0.08(0.06) 0.05(0.08) 0.02(0.52) 0.02(0.54) 0.01(0.78)


-0.01(0.77) 0.17(0.00) 0.08(0.06) 0.27(0.00) -0.08(0.14) 0.05(0.35) 0.01(0.89) 0.07(0.47)


AMU -0.02(0.97) 0.32(0.57) 0.37(0.46) 0.62(0.32) -4.26(0.00) -0.14(0.84) -4.11(0.00) -0.32(0.68)

CENSAD -0.54(0.22) 0.04(0.92) -0.44(0.35) -0.04(0.94) 1.46(0.12) 1.74(0.00) 1.83(0.07) 1.72(0.00)

ECOWAS 0.24(0.64) 1.31(0.02) 0.31(0.55) 1.53(0.01) -4.04(0.00) -2.14(0.00) -4.19(0.00) -2.17(0.00)

SADC -0.40(0.46) -0.10(0.85) -0.07(0.91) 0.12(0.84) -4.18(0.00) -2.05(0.00) -4.08(0.00) -2.01(0.00)

EAC -0.12(0.76) 0.57(0.19) 0.10(0.82) 0.66(0.15) -0.88(0.31) 0.86(0.12) -0.66(0.48) 0.93(0.10)

COMESA 0.16(0.58) -0.17(0.61) 0.32(0.30) 0.01(1.00) -2.27(0.00) -1.19(0.01) -2.20(0.00) -1.15(0.01)

IGAD -0.35(0.27) -0.27(0.37) -0.25(0.46) -0.47(0.16) 0.16(0.81) -0.14(0.72) 0.40(0.58) -0.24(0.57)

Additional variables: - - - -

No. Docs to import - -0.34(0.00) - -0.36(0.00) - -0.02(0.78) - -0.04(0.62)

No. Docs to export - 0.32(0.00) - 0.36(0.00) - 0.48(0.00) - 0.47(0.00)

ODA/GNI - 0.04(0.02) - 0.04(0.03) - -0.04(0.08) - -0.03(0.20)

PPG/GNI - 0.02(0.12) - 0.02(0.05) - 0.01(0.45) - 0.01(0.52)

Constant 0.16(0.82) 0.46(0.63) -0.33(0.65) 7.67(0.00) 1.58(0.20) 7.47(0.00)

R squared 0.78 0.75 0.78 0.75 0.80 0.92 0.80 0.93

F-stat - - - - - - - -

Wald Chi-sq 1257.86 560.65 1220.63 530.21 1375.19 2175.71 1345.98 2222.68

No.observations. 348 183 340 178 348 183 340 178

Endogenous variables: Prefsrateblocmin; MFNsimple Prefsrateblocmin; MFNsimple

Exogenous variables: columns (i) (ii) (v) (vi): Lagged MFNsimple, lagged prefsrateblocmin, prefsratenonblocmin, prefsratenonafricanmin, REC dummy

variables +ODAGNI, PPGGNI, Docexport, Docimport when included. Exogenous variables: columns (iii) (iv) (vii) (viii): Lagged MFNsimple, lagged prefsrateblocmin, lagged prefsratenonblocmin, lagged

prefsratenonafricanmin, REC dummy variables +ODAGNI, PPGGNI, Docexport, Docimport when included.


50

Table A.4. Stationarity tests:

Fisher-type unit-root test, Based on augmented Dickey-Fuller tests

Ho: All panels contain unit roots Ha: At least one panel is stationary

AR parameter: Panel-specific Asymptotics: T -> Infinity

Panel means: Included

Time trend: Not included

Drift term: Not included ADF regressions: 0 lags

Variable Test Statistic P-value

MFNsimple2 Inverse chi-squared P 68.04 0.94

Inverse normal Z 0.72 0.76

Inverse logit t(159) L* 0.67 0.75

Modified inv. chi-squared Pm -1.50 0.93

Prefsrateblocmin Inverse chi-squared P 151.94 0.00

Inverse normal Z -2.16 0.01

Inverse logit t(159) L* -5.01 0.00

Modified inv. chi-squared Pm 4.82 0.00

Prefsratenonblocmin Inverse chi-squared P 42.82 0.90




Prefsratenonafricanmin Inverse chi-squared P 64.09 0.09




Docimport Inverse chi-squared P 22.48 1.00




Docexport Inverse chi-squared P 23.94 1.00




ODAGNI Inverse chi-squared P 254.59 0.00




PPGGNI Inverse chi-squared P 72.26 0.72

Inverse normal Z 2.57 0.99

Inverse logit t(159) L* 1.93 0.97



51

Annex B

a. MFN Rates Profiles of African Countries

Source: WITS Database (accessed April , 2017)

Sabbatical leave programme 2016-2017 Report prepared by the UN staff member

52

0

5

10

15

20

25

30

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Algeria

MFNsimple MFNweighted

0,00

2,00

4,00

6,00

8,00

10,00

12,00

14,00

16,00

18,00

20,00

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Benin

MFNsimple .. .. .. .. .. .. .. .. MFNweighted .. .. .. .. .. .. .. ..

0

2

4

6

8

10

12

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Botswana

MFNsimple .. .. .. .. .. .. .. .. MFNweighted .. .. .. .. .. .. .. ..


53

0,00

2,00

4,00

6,00

8,00

10,00

12,00

14,00

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Burkina Faso


0

5

10

15

20

25

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Burundi

MfNsimple MFNweighted


54

0

2

4

6

8

10

12

14

16

18

20

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

Cameroon


0

5

10

15

20

25

30

35

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Central African Republic

MFNsimple .. .. MFNweighted .. ..

0

2

4

6

8

10

12

14

16

18

20

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Chad

MFNsimple .. .. MFNweighted .. ..


55

0

2

4

6

8

10

12

14

16

18

2008 2009 2010 2011 2012 2013 2014 2015

Comoros


0

2

4

6

8

10

12

14

16

18

20

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Congo Rep.

MFNSimple .. MFNweighted ..


56

0

2

4

6

8

10

12

14

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Cote d'Ivoire


0

50

100

150

200

250

Djibouti


0

10

20

30

40

50

60

70

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Egypt



57

0

2

4

6

8

10

12

14

16

18

20

Equatorial Guinea


0

1

2

3

4

5

6

7

8

9

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Eritrea


0

5

10

15

20

25

30

35

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Ethiopia (excludes Eritrea)



58

0

2

4

6

8

10

12

14

16

18

20

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Gabon


0

2

4

6

8

10

12

14

16

18

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Gambia


0

2

4

6

8

10

12

14

16

18

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Ghana



59

10

10,5

11

11,5

12

12,5

13

13,5

14

14,5

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Guinea Bissau


0

5

10

15

20

25

30

35

40

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Kenya



60

0

2

4

6

8

10

12

14

16

18

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Lesotho


0

2

4

6

8

10

12

14

2012 2013 2014 2015

Liberia


0

5

10

15

20

25

30

35

40

Libya



61

0

2

4

6

8

10

12

14

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Madagascar


0

5

10

15

20

25

30

35

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Malawi


0

2

4

6

8

10

12

14

16

18

Mali

Mfnsimple MFNweighted


62

0

5

10

15

20

25

30

35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Mauritius


0

10

20

30

40

50

60

70

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Morocco


0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Mozambique



63

0

2

4

6

8

10

12

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Namibia


0

2

4

6

8

10

12

14

16

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Niger


0

10

20

30

40

50

60

70

80

90

100

19

88

19

89

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Nigeria



64

0

10

20

30

40

50

60

70

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Rwanda


0

2

4

6

8

10

12

14

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Senegal


0

5

10

15

20

25

30

35

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Seychelles



65

0

2

4

6

8

10

12

14

16

18

19

88

19

89

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

South Africa


0

5

10

15

20

25

30

1996 2002 2006 2008 2009 2010 2011

Sudan



66

0

2

4

6

8

10

12

14

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Swaziland


0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Tanzania


0

2

4

6

8

10

12

14

16

Togo



67

0

5

10

15

20

25

30

35

40

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Tunisia


0

2

4

6

8

10

12

14

16

18

20

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Uganda


0

5

10

15

20

25

30

35

40

45

Zimbabwe



68

B.b. Data Availability per African country: MFN rates

Country First available

year: WITS

First available year:

Estimation

Missing observations

added

1.Algeria 1993 1993 10

2.Benin 2001 1998 3

3.Botswana 2001 1998 4

4.Burkina Faso 1993 1993 7

5.Burundi 2002 1999 4

6.Cameroon 1994 1993 7

7.Central African Republic 1995 1993 7

8.Chad 1995 1993 8

9.Comoros 2008 2005 4

10.Congo Rep. 1994 1993 7

11.Cote d'Ivoire 1993 1993 6

12.Djibouti 1998 1995 12

13.Egypt 1995 1993 3

14.Equatorial Guinea 1998 1995 16

15.Eritrea 2002 1999 15

16.Ethiopia (excludes Eritrea) 1995 1993 12

17.Gabon 1995 1993 7

18.The Gambia 2003 2000 8

19.Ghana 1993 1993 12

20.Guinea-Bissau 2001 1998 4

21.Kenya 1994 1993 6

22.Lesotho 2001 1998 5

23.Liberia 2012 2009 4

24.Libya 1996 1993 20

25.Madagascar 1993 1995 4

26.Malawi 1994 1993 6

27.Mali 1995 1993 2

28.Mauritius 1995 1993 2

29.Morocco 1993 1993 7

30.Mozambique 1994 1993 9

31.Namibia 2001 1998 4

32.Niger 2001 1998 4

33.Nigeria 1988 1988 6

34.Rwanda 1993 1993 8

35.Senegal 2001 1998 3

36.Seychelles 2000 1997 13

37.South Africa 1988 1988 5

38.Sudan 2012 2009 6

39.Swaziland 2001 1998 4

40.Tanzania 1993 1993 7

41.Togo 1996 1993 4

42.Tunisia 1990 1990 9

43.Uganda 1994 1994 6

44.Zimbabwe 1996 1993 10

Source: Author.


69

B.c. Data Availability per African country: Preferential rates

Country First available year:

Preferential rate

within bloc

Preferential rate

outside bloc within

Africa

Preferential rate

outside Africa

1.Algeria 2005 1993 2009

2.Benin 2006 …. …..

3.Botswana 2001 2001 2001

4.Burkina Faso 2006 .. ..

5.Burundi 2002 2002

6.Cameroon 1995 …. ….

7.Central African

Republic

1995 1997 1997

8.Chad 1995 1995 1995

9.Comoros 2008 … ….

10.Congo Rep. 2007 …. …

11.Cote d'Ivoire 2006 …. ….

12.Djibouti 1998 1998 1998

13.Egypt 1995 1995 1995

14.Equatorial

Guinea

1998 …. ….

15.Eritrea 2006 …. ….

16.Ethiopia

(excludes Eritrea)

2008 2008 ….

17.Gabon 2007 …. ….

18.The Gambia 2009 2009 2009

19.Ghana 2007 … …

20.Guinea-Bissau 2006 … …

21.Kenya 1994 1994 1994

22.Lesotho 2001 2001 2001

23.Liberia 2013 2012 2012

24.Libya 1996 1996 1996

25.Madagascar 2005 2007 ….

26.Malawi 1996 1996 …

27.Mali 2006 … …

28.Mauritius 1995 1995 2002

29.Morocco 2005 2005 2005

30.Mozambique 2001 … 2014

31.Namibia 2001 2001 2001

32.Niger 2006 … …

33.Nigeria 1995 1995 1995

34.Rwanda 2001 2001 2009

35.Senegal 2006 … …

36.Seychelles 2005 2005 2005

37.South Africa 1990 1990 1988

38.Sudan 1996 1996 2006

39.Swaziland 2001 2001 2001

40.Tanzania 1998 1998 2005

41.Togo 2006 … …

42.Tunisia 2002 2002 2002

43.Uganda 1994 1994 2001

44.Zimbabwe 1996 1996 1996

Source: Author.


70

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