ECONOMIC POLICIES FOR POST-CONFLICT RECOVERY: COMPARATIVE STUDY BETWEEN RWANDA AND SIERRA LEONE

Master’s Degree

Ahmed KEMOH

Eskisehir, 2019

ECONOMIC POLICIES FOR POST-CONFLICT RECOVERY: COMPARATIVE STUDY BETWEEN RWANDA AND SIERRA LEONE

Ahmed Kemoh

MASTER’S THESIS

Department of Economics

Supervisor: Assist. Pro Doc. Dr. Ismail Onur BAYCAN

Eskisehir

Anadolu University

Graduate School of Social Science

January 2019

FINAL APPROVAL FOR THESIS

This thesis titled “Economıc Policies for Post-Conflıct Recovery: Comparatıve Study Between Rwanda and Sierra Leone” has been prepared and submitted by Ahmed KEMOH in partial fulfillment of the requirements in “Anadolu University Directive on Graduate Education and Examination” for the Degree of Master of Science in Economics Department has been examined and approved on …../…../……..

Committee Members

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Member (Supervisor) :	Assistant Prof. Dr. Ismail Onur BAYCAN	………… .........
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Member :		……………….

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Name of Director

Director of Graduate School of Social Science

ÖZET

ÇATIŞMA SONRASI İYİLEŞME İÇİN EKONOMİ POLİTİKALARI: RWANDA VE SIERRA LEONE ARASINDAKİ KARŞILAŞTIRMALI BİR ÇALIŞMA

Ahmed KEMOH

İktisat Anabilim Dalı

Anadolu Üniversitesi Sosyal Bilimler Enstitüsü,

Ocak, 2019.

Danışman: Yard.Doç.Dr. Ismail Onur BAYCAN

Araştırma, ekonomik politikaların çatışma sonrası ekonomik iyileşmedeki rolünü incelemeye çalıştı. Ruanda ve Sierra Leone hükümetleri tarafından yapılan politika reformlarının ekonomik iyileşme ve gelişmelerine katkısı karşılaştırıldı. Çalışmanın temel amacı, dış yardımın doğrudan yabancı yatırım ile olan ilişkisini incelemek ve çatışma sonrası ekonomik iyileşmedeki yeni çatışma riskini azaltmada askeri harcamaların rolünü incelemek ve gayri safi yurtiçi hasıla, yerli yatırımın katkısını incelemek oldu. iki ülkenin ekonomik iyileşmesine. VECM modelinin sonucu, gayri safi yurtiçi hasıla, yurt içi yatırım, dış yardım ve askeri harcamaların Sierra Leone ve Ruanda'nın ekonomik büyümesinde uzun zamandır önemli bir etkiye sahip olduğunu göstermektedir. Gayri safi yurtiçi hasıla, doğrudan yatırım, dış yardım ve askeri harcamaların hem Ruanda hem de Sierra Leone için kısa vadede önemli bir etkisi yoktur. Granger Nedensellik testinin sonucu ayrıca Sierra Leone'de çift yönlü Granger'ın gayri safi yurtiçi hasılaya neden olduğunu ve yurtiçi yatırım Granger'in DYY'ye neden olduğunu gösteriyor. Dış yardımdan doğrudan yabancı yatırım yatırımına kadar tek yönlü bir etki söz konusudur. Öte yandan, Ruanda gayri safi yurtiçi hasıla için Granger, gerçek DYY'ye neden olmaktadır ve Ruanda'da DYY'ye yabancı yardım gelmesi yönünde iki yönlü nedensellik vardır ve tek yönlülük, doğrudan yabancı yatırımlara doğrudan yabancı yatırım gelmesine neden olur ve yabancı doğrudan yatırım dürtüsü askeri harcamalara neden olur.

Anahtar Sözcükler:
Iyileşme, Ekonomik Politikalar, Doğrudan Yabancı Yatırım, Yurtiçi Yatırım

ABSTRACT

ECONOMIC POLICIES FOR POST-CONFLICT RECOVERY: COMPARATIVE STUDY BETWEEN RWANDA AND SIERRA LEONE

Ahmed KEMOH

Department of Economics

Anadolu University, Graduate School of Social Sciences,

January, 2019

Supervisor: Dr. Ismail Onur BAYCAN

This research tried to examine the role of economic policies in post-conflict economic recovery. The contribution of the policy reforms made by the governments of Rwanda and Sierra Leone to their economic recovery and development are compared. The main objectives of the study were to examine the relationship of foreign aid on foreign direct investment and examine and the role of military expenditure in reducing the risk of new conflict in post-conflict economic recovery and examine the contribution of gross domestic product, domestic investment to the economic recovery of the two countries. The result from the VECM model indicates that gross domestic products, domestic investment, foreign aid, and military expenditure have long run significant effect on economic growth of Sierra Leone and Rwanda. There is no short-run significant effect of the gross domestic product, direct investment, foreign aid and military expenditure to both Rwanda and Sierra Leone. Also, the result from the Granger Causality test shows that in Sierra Leone, There is bi-directional Granger causes gross domestic product, and domestic investment Granger causes FDI. There is a unidirectional effect coming from foreign aid to foreign direct investment. On the other hand, for Rwanda gross domestic product Granger causes real FDI and there is bi-directional causality coming foreign aid to FDI in Rwanda, and unidirectional causality coming domestic investment to foreign direct investment, and foreign direct investment Granger cause military expenditure.

Keywords:
Recovery, Economic Policies, Foreign Direct Investment

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DECLARATION

I declare that all information this thesis has been obtained and presented as academic rules and ethical conduct of Anadolu University. I also declare here this is my original work and all materials which are not my own work have been cited and acknowledged. I understand that the university deserves right to apply measures in the event that my work found to be breach of the academic rules and ethical conduct of the university.

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Ahmed KEMOH

Table of Contents

TITLE PAGE.. i

FINAL APPROVAL FOR THESIS. ii

ÖZET.. iii

ABSTRACT.. iv

STATEMENT OF COMPLIANCE WITH ETHICAL PRINCIPLES AND RULES. v

TABLE OF CONTENTS. vi

LIST OF TABLES. ix

LIST OF FIGURES. x

SYMBOLS AND ABBREVIATIONS. xi

1. Introduction.. 1

1.1 Introduction and Motivation of the Study. 1

1.2 Statement of the Problem.. 2

1.3 Aims and objectives of the Study. 5

1.4 The Significance of the Study. 5

1.5 The Purpose of the Study. 7

1.6 Assumptions of the Study. 8

1.7 Limitations of the Study. 8

1.8 Definitions of Terms. 8

2. Literature Review... 9

2.1 Theoretical framework. 9

2.2 Major Reasons for Conflict 10

2.3 Competition for power and resources. 10

2.3.1 Competition of Power and Resources. 10

2.3.2 Extractive institutions. 13

2.3.3 Colonial legacy. 15

2.3.4 Poor economic performance. 16

2.4 Economic Policy Priorities for Post-Conflict Recovery. 17

2.4.2 The empirical evidence on the effects of military spending in reducing the risk of a new conflict 20

2.4.3 The effects of domestic investment on foreign direct investment 23

2.4.4 The effect of gross domestic product on foreign direct investment 27

3. Research Methodology.. 29

3.1 The Model Specification. 29

3.2 Stationarity Test 30

3.2.1 Augmented Dickey-Fuller test 31

3.3 Testing of Cointegration. 31

3.3.1 Johansen cointegration test 31

3.4 Vector Error Correction Model (VECM) 32

4. ANALYSIS. 34

4.1 Graphical Analysis. 34

4.2 Stationarity Test Results. 42

4.2.1 Augmented dickey-fuller test 42

4.3 Lag Length Determination of The Model 43

4.3.1 VAR lag order selection criteria (Rwanda) 44

4.3.2 VAR Lag order selection criteria (Sierra Leone) VAR lag order selection criteria (Sierra Leone) 44

4.3.3 Cointegration Testing. 44

4.3.4 Johansen cointegration (Rwanda) 45

4.3.5 Johansen cointegration (Sierra Leone) 45

4.4 Vector Error Correction Model (VECM) 46

4.4.1 VECM (Vector Error Correction Model) for Rwanda. 46

4.4.2 VECM (Vector error correction model) Sierra Leone. 47

4.5 Granger Causality Test 48

4.5.1 Granger causality test for Rwanda series. 48

4.5.2 Granger causality test for Sierra Leone series. 49

4.6 Checking Serial Correlation. 50

4.7 Serial correlation detection for Rwanda. 50

4.7.1 Serial correlation detection for Sierra Leone. 51

4.8 Checking Heteroskedasticity. 51

4.8.1 Checking heteroskedasticity for Rwanda. 51

4.8.2 Checking heteroskedasticity for Sierra Leone. 52

4.9 Cusum Test 52

4.10 Impulse Response. 53

4.10.1 The results of the impulse response for the series of Rwanda. 53

4.10.2 The results of the impulse response for the series of Sierra Leone 56

5. Overall Summary of the Empirical Results, Policy, and Conclusion.. 59

5.1 Overall Summary of the Empirical Results. 59

5.2 Policy and Recommendation. 62

5.3 Conclusion. 65

5.4 Recommendations for Further Study. 66

REFERENCES. 67

CV.. 70

LIST OF TABLES

Table 4.1.
Unit Root Test for the series of Rwanda based on Augmented Dickey-Fuller test and Lag Length Base on the Schwartz Bayesian Information Criterion. 43

Table 4.2.
Unit Root Test for the series of Sierra Leone based on Augmented Dickey-Fuller test and Lag Length Base on the Schwartz Bayesian Information Criterion. 43

Table 4.3.
VAR Lag Order Selection Criteria (Rwanda) 44

Table 4.4.
VAR Lag order selection criteria (Sierra Leone) VAR lag order selection criteria (Sierra Leone) 44

Table 4.5.
Johansen Cointegration test for the series of Rwanda. 45

Table 4.6.
Johansen Cointegration test for the series of Sierra Leone. 46

Table 4.7.
Vector Error Correction Model for Rwanda. 47

Table 4.8.
Vector Error Correction Model for Sierra Leone. 48

Table 4.9.
Granger causality for Rwanda. 49

Table 4.10.
Granger causality for the series of Sierra Leone. 50

Table 4.11.
Breusch-Godfrey serial correlation LM test for the variables of Rwanda. 51

Table 4.12.
Breusch-Godfrey serial correlation LM test for the variables of Rwanda. 51

Table 4.13.
Heteroskedasticity test: Breusch-Pagan-Godfrey for Rwanda. 51

Table 4.14.
Heteroskedasticity test: Breusch-Pagan-Godfrey for Sierra Leone. 52

LIST OF FIGURES

Figure 4.1. Foreign direct investments (FDI) of Rwanda. 34

Figure 4.2.
Foreign direct investments (FDI) of Sierra Leone. 35

Figure 4.3.
Gross domestic product (GDP) Rwanda. 36

Figure 4.4. Gross domestic product (GDP) Sierra Leone. 36

Figure 4.5. Domestic investment (DI) of Rwanda. 38

Figure 4.6.
Domestic investment (DI) of Sierra Leone. 38

Figure 4.7.
Foreign aid to Rwanda. 39

Figure 4.8.
Foreign aid to Sierra Leone. 40

Figure 4.9.
Military expenditure of Rwanda. 41

Figure 4.10.
Military expenditure of Sierra Leone. 41

Figure 4.11.
Checking the stability of the model using the Cusum test (Rwanda) 52

Figure 4.12.
Checking the stability of the model using the Cusum test (Sierra Leone) 53

Figure 4.13. Impulse response of FDI to changes in the gross domestic product in Rwanda 53

Figure 4.14.
The impulse response of FDI to changes in domestic investment in Rwanda. 54

Figure 4.15. The impulse response of FDI to one standard shock in foreign aid in Rwanda 54

Figure 4.16.
The impulse response of FDI to changes in military expenditures in Rwanda 55

Figure 4.17.
The impulse response of Foreign Direct Investment to changes in the Gross domestic product in Sierra Leone. 56

Figure 4.18.
The impulse response of Foreign Direct Investment to change in Direct Investment in Sierra Leone. 56

Figure 4.19.
The impulse response of Foreign Direct Investment to one standard shock in Foreign Aid in Sierra Leone. 57

Figure 4.20.
The impulse response of foreign direct investment to changes in Military expenditures in Sierra Leone. 58

SYMBOLS AND ABBREVIATIONS

RPF: Rwandan Patriotic Front

VECM: Vector Error Correction Model

ADF: Augmented Dickey-Fuller Test

FDI: Foreign Direct Investment

DDR : Disarmament, Demobilization and Reintegration

1. Introduction

1.1 Introduction and Motivation of the Study

Rwanda and Sierra Leone are both located in East and West region of Africa, Sierra Leone is approximately three times bigger than Rwanda, with the former be approximately 71,740 sq. km and the latter be approximately 26,338 sq. km while, the population of Rwanda is 13 million people compared to the 7 million people in Sierra Leone, and share a different colonial legacy with Sierra Leone being a British Colony and Rwanda being a Belgian Colony but share a terrible saga of genocide and civil unrest respectively. Despite this country share a tragic history of genocide and civil war, the restoration of the economy of Rwanda has been more effective since the end of the genocide, whereas the restoration of the economy in Sierra Leone has been hit by series of corruption scandal of high government stakeholders with a large number of the population living on $1 a day. Growth and development have been booming in Rwanda than in Sierra Leone since the end of their respective conflict. This study carries out relative research of Rwanda and Sierra Leone to evaluate the reasons for the decline of growth in conflict affected countries, whereas growth has been perpetual in conflicted countries. The research investigates the different policies implemented by both Rwanda and Sierra Leone in their transition from war to peace. It concludes the growth and development was as a result of the political revolution to deliver to the people they govern. A comprehensive and detailed challenges in attracting foreign direct investors and fiscal recovery in post-conflict countries. The economies of these two countries shows once on brutal civil war, are now worlds apart. Minerals, Coffee and tea are mainly the foreign exchange earnings for both countries, as also subsistence agriculture is the main source of employment for these countries. About 50% of the national incomes from foreign aid. Rwanda and Sierra Leone both have a history of one on the worst humanitarian crisis in history but economically in present times Rwanda is far away ahead of Sierra Leone. Rwanda and Sierra Leone gained independence in 1960 and 1961 respectively. Socio- economic development approach has not been prioritize in Sierra Leone since the end of the colonial era in the 1960s, as their has been some turmoil in the political landscape in Sierra Leone. Food insecurity and the rapidly growing population during the 1980s affected economic growth. Sierra Leone civil unrest started in 1991, while Rwanda experienced one of the world worst genocide in 1994 which left both countries unable to attract foreign investors which has negative impacts on both countries’ economy. Both the private and public sector has been adversely affected especially those that highly relied on experienced personnel and foreign market. In order to attract foreign direct investment for post-war socio-economic development and growth both countries utilized distinct approaches. The urban-based growth-first strategy, the service sector and information technology development that prioritized higher education were employed by the Rwandan government which was the same strategy employed by Singapore. In a quarter of century, Kigali has transformed into a commercial hub. The metropolitan instituted approach by the Rwandan government has facilitated income inequality in the midst of big and small towns among the Tutsi in the urban city and the Hutu in the rural areas.

After the July 7, 1991 signing of the Lomé Peace Agreement which ended one of the worlds devastating civil unrest. In an effort to achieve socio-economic development and growth the government of Sierra Leone focused on the challenges in the resolution from post-war by establishing the market structure to attract foreign direct investment, proving nationwide safe houses for refugees, by instituting governmental jurisdiction and embark on restoring infrastructure.

1.2 Statement of the Problem

The significance of foreign aid to underdeveloped and conflict affected countries has focused on socio economic growth and development, sustainability of peace and security, rehabilitation of roads, factories, educational infrastructure etc and enhancing human resource. (Collier and Hoeffler (2002, p. 45) and (2004, p. 40). Research on post-conflict countries have also been based on foreign aid policy and growth (Collier and Hoeffler (2004, p. 40); humanitarian assistance and armed conflict (Addison (2000, p. 25)]; humanitarian aid and rehabilitation aid (Damekas et al. (2002, p.1); component of conflicted affected countries on economic aid (Kang and Meernik (2004, p.5);also state of behavior before war by employing the opinion survey data (Hermann et al. (2002, p. 20), Mi Ari (1999, p. 20), Wilcox et al. (1996, p.40), Gwartney-Gibbs and Lach (1991, p.45)].

The risk of conflict renewal is very high in a post-conflict situation since there are many economic and political problems that may lead to another conflict. After the internal conflict, per capita income falls dramatically, there are different armed groups and the high percentage of unemployed youth can be hired by rebel groups. The post-conflict government must set economic policy priorities for reducing the risk of new conflict and tackling the economic problems because according to African-Bank (2008, p. 46), there is significant risk of another conflict in conflicted affected countries .As a result of significant risk of conflict renewal in post-conflict countries, government should therefore employ a vice versa approach on both economic recovery and implementing policies that mitigate the risk of another war. After the civil war, the biggest challenge is to identify where to start the peacebuilding process and how the various political parts can be included in the rebuilding process. The capacity is very limited because the war destroys the physical and human capital and all government institutions, so setting economic policy priorities are very necessary because at that time everything seems to have priority. Post conflict affected economies are normally in disarray with lack of accountability, bad governance, perverted constitutional system, inefficiency fiscal system, with 50% of their budget is made up of foreign aid Phelps (2008, p.31).

In the early 1990s civil wars broke up in many African countries for different reasons but after internal and external efforts most of those conflicts came to an end and now there are many post-conflict cases in Africa. The reduction in the poverty rate, the booming of the tourism industry and the huge foreign investment are the results of macroeconomic policy reforms made by several post-conflict governments. Rwanda is considered one of the countries that have success stories in setting economic policy priorities for achieving recovery and development. The growth rate of Rwanda was very high after the genocide because the government set new economic policies and made many reforms to increase the economic performance of the country.

In relation to post- conflict countries, African countries still have a high risk of new conflict because of exclusive political institutions and bad economic conditions. Dictatorship system dominated in many post-conflict countries and few individuals exploit the public resources while most of the citizens are suffering from a high poverty rate. Both Rwanda and Sierra Leone shared history of brutal genocide and civil war respectively but Sierra Leone is yet to achieve economic recovery because of the different post-conflict economic recovery approach. This includes the contemporary shortage of extensive strategy development and explicit primary objective for key economic areas. As a result, current economic recovery efforts in Sierra Leone consists of a variety of small-scale programs that are predominantly of a standard development nature, instead of being aimed to contribute to peacebuilding efforts” (Specker, Briscoe, & Gasana, 2010, p. 1). The international community works to develop policies to rebuild war-ravaged countries and inject large amounts of aid for emergency and development purposes but most of the post-conflict nations still remain fragile, mainly dependent on foreign aid and unable to provide public goods to the people. According to Ehrenreich (2012, p. 1161), they cannot ascertain economic growth or any rational distribution of social goods: They are generally characterized by extensive economic inequities, factionalism, and fierce competition for resources. Recent precedent of malfunctioned states is accustomed to us all, from the absolute disintegration of state institutions in Somalia and the disintegration of the former Yugoslavia to the different crises in Rwanda, Haiti, Liberia, Congo, Sierra Leone, and Afghanistan.

This study investigates the economic policies which are necessary for post-conflict recovery and how the government can prioritize the activities of the peacebuilding process. Also, the challenges and potential opportunities of the post-conflict government are discussed in this study. In this study, it is tried to present how a government and donors can develop policy coordination for the peacebuilding process and how the government can take a leading role in sustainable peace and development. So ultimately turn the peace project to a locally owned one.

1.3 Aims and objectives of the Study

The foremost aim of this research is to provide an empirical analysis of economic policies in achieving economic recovery for post-conflict countries. The first objective is to examine the relationship between foreign aid and foreign direct investment and also the impacts of military expenditure in reducing the risk of new conflict in post-conflict countries since there is a high possibility of new conflict after the civil war and the study is based on the cases of Sierra Leone and Rwanda. It also examines the effect of domestic investment on foreign direct investment in post-conflict situations. Finally, the study examines the impacts of a gross domestic product on foreign direct investment in the economic growth of post-conflict countries. The research is based on comparative time series study between Rwanda and Sierra Leone; and looks at the role of the economic policies in the economic performance of these two countries, taking the foreign direct investment as the measurement of their economic recovery. Pre-conflict economic conditions of the two countries, the reasons behind the conflict and the economic policies that developed by both governments after the civil war were investigated in detail.

1.4 The Significance of the Study

The research is important for post-conflict governments and the international community or donors. It is important for the post-conflict government because high risks of new conflict caused by economic factors such as high unemployment, high inflation rate, and poverty; so economic policies are necessary in post-conflict times. Also, the study tried to examine economic policies and reforms made b y post-conflict countries and how these policies contributed to the economic growth and recovery after the wartime.

It is also important for the donors since they want to help the nations emerging from wars in terms of developing policy priorities and providing humanitarian aid and development assistance; so this study explains the ways that the role of the international community can be very useful for the peace-building process and recovery of post-conflict countries. This research paper closely examines the relationship of foreign aid on economic recovery in the post-war state of affairs and the contribution of aid in an institutional building, job creation, the rehabilitation of infrastructure and achieving sustainable economic growth and development.

Due to ethnic tensions, civil war and corruption, Rwanda and Sierra Leone had experienced severe civil conflicts and genocides in 1994 and 1991 that devastated the physical and human capital in both countries. İn 1994, an approximately 800,000 to one million Tutsis and some Hutus were killed in Rwandan genocide saga and approximately 300,000 people were killed in Sierra Leone at the same year. The civil war lasted from 1991 up to 2002 in Sierra Leone; the warring sides have signed a peace agreement at Abuja in May 2001, set the stage for a re-establishment of DDR on a large scale and a considerable reduction in hostilities that ended the Sierra Leone civil war. Similarly, the Rwandan civil war began in 1990 and ended with an RPF victory on July 18, 1994. There is political stability in Rwanda since 1994 and inclusive government institutions were formed; two presidential elections were held in the country that the current president Paul Kagame has won both of them. Rwanda set its long-term development goal that is defined in a strategy known as “vision 2020” that targets to transform the country from an agricultural-based economy to an industrialized and knowledge-based economy. In 2016 gross domestic product of Rwanda is $21.97 billion and its growth rate is 6% and the main sectors that contribute to the economic growth are Agriculture 34%, industry 15.1% and services 50.3%. Rwanda has a great economic success story after many economic reforms and policy that enabled the country to achieve growth and recovery within two decades.

The main challenge for Rwandan economy is its dependency on foreign aid while a high percentage of government expenditures are financed from foreign aid and the government tries to develop the private sector in order to play a major role in ensuring economic growth. The government tries to develop policies to attract foreign direct investment to create job opportunities, help in the skill transfer and promote the export of the country. Sierra Leone has maintained relative political stability since 2002 but with the Ebola crisis in 2015 and the mud-slide in 2017 affected the economy. Although Sierra Leone has its own development goal, it has no economic transformation like Rwanda because a high percentage of Sierra Leoneans live under the poverty line and there are large budget deficits over the past years and estimations forecast that the public debt ratio is expected to exceed the real gross domestic product. The gross domestic product of Sierra Leone grew 6.3% in 2016 compared to 2015. The proportion is 268 -tenths of 1% percent greater than the figure of -20.5% published in 2015. The gross domestic product sum in 2016 was $3,785 million, and it was 159 in the ranking of gross domestic product of the 196 countries that was published. The absolute value of the gross domestic product in Sierra Leone declined by $467 million with respect to 2015. The gross domestic product per capita of Sierra Leone in 2016 was $522, $78 less than in 2015 when it was $600. If we order the countries according to their gross domestic product per capita, Sierra Leone is in 185th position. According to this parameter, its population is among the poorest of the 196 countries whose gross domestic product was published. So this study extensively investigates economic policies and reforms made by the made by the governments of Rwanda and Sierra Leone after the conflict and it also examines the role of these policies in the economic growth and recovery in these two countries made by the governments of Rwanda and Sierra Leone after the conflict and it also examines the relationship of these policies in the economic growth and recovery in these two countries.

1.5 The Purpose of the Study

The purpose of this thesis is to explain the importance of economic policies for achieving post-conflict recovery. In the early 1990s civil wars started in many African countries for several reasons, but at the middle and the end of 1990s peace agreements were reached, and many post-conflict situations emerged in many parts of the continent. The civil war lasted more than one or two decades in some countries like Burundi and Somalia, and now other civil wars are still going on in certain countries like the civil wars in Libya and Congo.

This study will deeply investigate the economic policies developed by the governments of Rwanda and Sierra Leone and how these policy reforms contributed to foreign direct investment on the economic recovery and development of these countries. The role of the international community in the peace building process in the countries, which are emerging from conflict, will be examined extensively. Also, comparison analysis between Rwanda and Sierra Leone in terms of FDI and reducing the risk of new conflict, by increasing the gross domestic product through domestic investment and benefiting from foreign aid flows will be the main body that this research work will concentrate.

1.6 Assumptions of the Study

The study assumes that foreign aid has a positive effect on foreign direct investment in post-conflict countries. Also, it assumes that gross domestic product and domestic investment have a positive effect on foreign direct investment since these financial flows are expected to increase foreign direct investment in post-conflict situations. Finally, the study assumes that increasing military expenditure promotes economic growth by reducing the risk of new conflict in post-conflict situations.

1.7 Limitations of the Study

One of the limitations of the study that some variables which may explain foreign direct investment are not included in the model because of lack of time series data. Human capital, corruption index, and political stability are some of the variables that may affect foreign direct investment the in post-conflict countries, but the time series of these variables are not available for the countries taken as case study.

1.8 Definitions of Terms

Economic recovery: In this study, economic recovery is not referred only to the stage of the business cycle following a recession, but the recovery has a broader definition. It is related to reforming in the sea curity sector, forming include sive political and economic institutions and achieving sustainable economic growth and development.

Post-conflict: it is the situation after the conflict which open warfare has ended but still there is a high risk of new conflict and this situation may last more than a decade. Domestic investment consists of public and private investment. Public investments are the money spent on public goods such as roads and education. Private investment is the purchase of a capital asset with the aim of making a profit. Capital assets include land, building, and equipment.

2. Literature Review

2.1 Theoretical framework

The countries emerging from a prolonged conflict are struggling to restore peace and stability and achieve recovery. Also, the international community develop policies, arrange reconciliation conferences and offer humanitarian and development aid to war-torn countries to achieve post-conflict recovery. In order to measure the performance and the success of the countries coming from the conflict, we need to understand or agree on what recovery really means in the post-conflict peace-building process. When many researchers and organizations define recovery; they refer it to returning to the status quo before the conflict, for instance, Ohiorhenuan (2011, p.3) quotes from Flores and Noorudin that recovery has different names such as reconstruction, rebuilding, and recovery and all suggest a return to the condition before the conflict. They indicate that after the conflict, recovery means a return to the economic growth and employment rates before the war. On the other hand, other researchers view recovery as a restoration to the highest level of gross domestic product per capita accomplished during the five years prior to the conflict. Regarding the above definition, a post-conflict government has achieved economic recovery if the country attains a growth rate which is equal to the pre-conflict period.

Some of the countries that experienced war see the recovery as the process of rebuilding physical capital that the war has destroyed during the conflict such as roads, ports and government buildings and they take certain measurements for the recovery. They often compare their accomplishments with the governments before the conflict. These governments view recovery as an economic issue only and that is why they try to get economic welfare before political reconciliation. They strive to create job opportunities, reduce inflation rate and get national output that is equal to pre-conflict period. For post-conflict recovery, the policymakers attempt to lead the country to the normal condition that existed before the eruption of chaos and develop economic policy for getting a self-sustaining approach of the economic system.

On the other hand, many researchers contend that recovery is not only about a return to pre-conflict condition and it is not just related to economic dimensions, but it has a broader concept and definition. It concerns to both politics and socio-economic issues such as reducing the unemployment rate, lowering crime level and combating high Inflation as Ohiorhenuan (2011, p .3) tells that recovery is not confined to the return to pre-conflict economic and institutional framework/arrangements. It relates to socioeconomic transformation and it needs combinations of reforms in legal, institutional and economic policy that enable war-ravaged nations to achieve self- sustaining development. That means establishing a new political-economic system and building back differently and in a better way.

In this study, post-conflict recovery has not considered a return to pre-conflict economic conditions only, but the recovery has a broader definition. It is related to reforming in the security sector, forming inclusive political and economic institutions and achieving sustainable economic growth and development as Mill (2005, p.1) defines post-conflict recovery being a complex process to simultaneously enhance military reinstatement of law and order, political dispensation, economic rehabilitation and development, and social conditions justice and reconciliation. Post-conflict economic rebuilding involves the distribution of relief assistance, rebuilding physical substructure and facilities, reestablishment of social services, creating a good environment for private sector development, and carrying out important structural reforms for macroeconomic stability and sustainable growth. In this study, we used the real gross domestic product as a measurement of economic recovery because the improvement in the key sectors mentioned in the definition of recovery accelerates the economic growth of post-conflict countries and the generally gross domestic product is used as a gauge for the economic performance of countries whether they are at peace or war times.

2.2 Major Reasons for Conflict

In this section, we try to discuss the major factors that cause armed conflicts in Africa, because identifying the reasons for the conflict is important for the peace-building process and achieving sustainable recovery.

2.3 Competition for power and resources.

2.3.1 Competition of Power and Resources

The major reason for conflict in Africa revolves around competition of power and resources among different groups because resources are associated with power, those are in power have the privilege and full access to the public resources. The conflict arises because some individuals want to get more resources at the expense of the majority of the people. The countries of Rwanda and Sierra Leone which the study takes as a case study have experienced severe conflicts that caused the genocide of many peoples and destroyed huge physical capital. In this research work, the root causes of the conflict in those two countries were investigated because it helps us to understand the nature of the conflict and facilitate finding solutions to the problem. Collier (2000, pp.91 & 96) claims that ‘conflicts are considerably more presumably to be induced by economic opportunities than by injustice,’ and ‘injustice-based explanations of civil war are so critically wrong’, In explaining the conflict in Burundi, Hatungimana (2011, p.13) indicates that in Burundi similar to all the poorest countries, the major source of wealth is from power. Everyone thinks losing power means going back to the state of poverty and no one accepts to leave the power but they do whatever possible to remain in the power. Most of them, their personal interest comes before the public interest.

Africa is a continent with sufficient economic resources but there is no equal distribution of resources among the people since only the government officials and foreign companies gain from the natural resources of Africa and the people suffer from poverty, unemployment, and various diseases. The competition for the power and resource is either between the elites or between different ethnic groups and these kinds of competition damaged the economy of Rwanda and Sierra Leone, as Ndikumana (2001, p.2) tells that the ethnic-based conflict in Rwanda has tremendously reduced the economy and worsened the structural situation of the country. The revenue of the government from the taxes has decreased due to the low tax base and management capability of the tax system. These governments diverted many important resources from productive sectors and social development projects to military and security expenditures.

The conflict is not only between ethnic groups but some time it may erupt between various clans within the same ethnic group as the Somalia case, despite they have the same ethnicity but similarly to Burundi; competition of resource and power between clans and sub-clans was one of the major factors caused the conflict as Elmi & Barise (2010, p.33) contend that the clans in Somalia were fighting for resources such as water, livestock and grazing before Somalia get its independence and after the independence they compete for state control to get nation’s resources and recruit civil servants and manage foreign aid and these new resources replaced the regulation of water wells and availability to grazing land in the rural environment. Politics is considered to be one of the most profitable businesses in Africa where many people invest a large amount of money in getting the governmental post to finance their costs and make huge profits from the public resources. The leaders mobilize their ethnic group or clan for involving the political process and promise them that they will get additional benefits

From the government, if they get their support. So there is a constant clashes between the society because of an ending competition like the situation in Somalia since “many Somalis see the government as a tool of accumulation and domination, enriching and empowering those who control it and take advantage of and harassing the rest of the population” (World Bank, 2005, p. 18). Sometimes the same clans face contention for power and resources and the fighting turns to a sub-clan one as they clash over the fortune accumulated from the other clans. So, the main contributing factor for African conflicts is the competition of power and resources between different ethnic groups or between different clans and sub-clans. The extent and possibility of the conflict can be associated with the level of the resources available in specific regions; several African countries have more natural resources while there are insufficient natural resources in some regions of Africa. Some researchers contend that the rate of internal conflict is high in states having fewer natural resources because the people fight over the scarce resources and everyone tries to survive by taking the large share of it. On the other hand, some writers argue that in general, resource-rich countries have a high rate of civil unrest because many behave in a greedy way in accumulating wealth as much as possible.

The different clans fight over resources since the resources are scarce during and after the conflict and competitions to control profitable cash crops caused disputes among clans and sub-clans. For instance, in line with World Bank (2005, p.7) in the valleys of the two rivers of south-central Somalia, some clans displaced others to get land and benefit from the cultivation of high profitable crops particularly bananas and other cash crops. Sometimes, the powerful tribes have forced the people into labor along the rivers. It is normal for the clan or an ethnic group to commit crimes and do every unlawful action in the process of power struggle and resource accumulation, they may attack other clans or organize a coup against legitimate government as Oyeniyi & Media (2011, p.3) assert that many factors cause military coups such as ethnic and personal rivalry (like Idi Amin’s coup in Uganda in 1971). Also, military coups induced by inter-ethnic rivalry among steering army officers and by tribal discontents against the civil head of state. Almost all tribal and ethnic conflicts caused by competition over scarce resources of wealth and power.

African governments and the international community must seek ways to get solutions to the competition of power and resources between various ethnic groups and different clans or sub-clans. Since the countries that have low per capita income and high poverty rate face an internal conflict; so only sharing power and resources equally between various ethnic groups minimize the risk of conflict and contributes to the peace of post-conflict areas. According to Brown & Stewart (2015, p.13), evidence from econometric studies indicates the incidence of the conflict is high in countries with low per capita income, economic growth, and life expectancy. For the ending of the civil war, what matters is sharing all types of resources among the communities. The risk of conflict falls when poverty and underdevelopment are equally shared by the society, but the incidence of the conflict is very high if some groups accumulate a disproportionate share of resources where the majority of the society is poor.

2.3.2 Extractive institutions

Conflict emerges when certain groups rule the country and exploit the public resources at the expense of the majority of the people and many social and economic problems in Africa are attributed to dictatorship in the continent. The people are paying the prices of long-term dictatorship that made Africa the poorest continent in the world. In explaining the causes of conflict in the political history of Burundi, Hatungimana (2011, p.6) notifies that small group mainly Tutsi abused the power and ranked against the majority of Hutu and the remaining groups. The colonizers gave the Tutsi minority superiority over the Hutu and Twa. An ethnic-based conflict happened because of the inequality of opportunities on the standard that was part of the divisive policy of “divide and rule” of the colonizer. The small group has been ruling the country since its independence from 1962 until 1993 for the first time, a president was democratically elected. The extractive institutions or the dictatorship leaders enrich their own ethnic groups or families and they are familiar with such nepotism, for instance, dictatorship president nominates most of the cabinet and high government positions for his relatives to rule the country throughout his life. So those who control the state have many political and economic privileges compared to the majority of

the normal citizens and that is how Tutsi behaved during their rule. According to Golooba Mutebi (2008, p. 3), the monopoly of Tutsi over government institutions offered inequality access to education and training opportunities, as most of the students studying at public and church schools and training institutions were Tutsi. Also, after graduation, Tutsis had high access to job opportunities than their Hutu fellows due to their connections in the government. This widely increased inequality and the sense of injustice among Hutu.

In Africa, some dictators rule their countries for more than two decade and they have done every kind of human violation and accumulation of large resources and wealth from the poor people in their own countries. So, the inequality between the society increased the possibility of violence in Africa because Brown & Stewart (2015, p. 8) found evidence indicates that horizontal inequalities in economic and social issues leads to dissatisfaction among the people and, consequently, increases the possibilities of political mobilization. But political exclusion brings conflict by giving group leaders a powerful motivation for organizing to get support. The extractive institutions benefit from the public and do whatever they can in order to stay in power, but their actions lead to revolution and violence.

Elmi & Barise (2010, p. 36) argue the second major cause of Somali conflict was the repression from the state. Somali people suffered 21 years of an oppressive military government from 1969 up to 1991. The government did not allow the existence of opposition party, not to mention to have a voice in important issues. The military state did not give the people the opportunity to participate in the politics and the opposition groups resorted to violence because the government denied all other means to be part of the regime. The opposition leader attacked Somalia from Ethiopia crossing the border between the two countries and the state’s repression, violence and extreme force against the people were the main justifications for the war.

2.3.3 Colonial legacy

European colonizers devastated Africa in many ways, and they are the root causes of most African conflicts. Africans lived under a colony for a long time and they did not get the opportunity to govern their countries. There are two bad legacies from the colony that drive the clashes and conflicts in Africa, and they are the curse of colonial borders in Africa and introducing ethnic-based conflicts in it. They have drawn controversial borders between Africa and their aim was against the unity of Africa and creating everlasting conflict in the continent. The first colonial legacy is the borders between Africa as Oyeniyi & Media (2011, p. 3) confirms that all most all these borders were hereditary of the colony and are the result of talks and agreements among the Colonial powers, agreed in Europe to form poor maps to Africa while there was little attention from the African people.

In some parts, they formed borders that created disputes between the countries and even led to great wars between the countries in Africa, for example, the 1977 war between Somalia and Ethiopia was due to the border dispute and similarly the hostility between Somalia and Kenya was because of the strategies of colonizers. According to Elmi & Barise (2010, p. 36), the colonial legacy is one of the reasons for the civil war in Somalia. European colonizers namely Britain, Italy, and France divided the majority of Somalia into five parts. British occupied two parts, Italy one and France one. The European powers offered the Somali region of Ogaden to Ethiopia. The aftermath of the division has been haunting the Somali people since and now two Somali territories remain under the control of Ethiopia and Kenya. Also several reasons of the civil war incontinent came from European colony who created opposition groups and supported to continue the war, for instance, Mozambique engulfed by civil war after only a few years of its independence and some European governments were backing the fighting groups in Mozambique and they based in Rhodesia to support Mozambican national resistance group that was struggling to oust the Mozambique liberation front which was the ruling party since its independence.

Europeans have taken the strategy to rule Africa by dividing them into different ethnic groups and clans and took advantage of their difference. They used the policy of “divide and rule” and promoted some ethnic groups over others to create ethnic violence for example in Burundi and Rwanda as Golooba Mutebi (2008, p. 2) says that one of the first measures that the Europeans took in their state-building process was to preclude the Hutu (whom they termed as the less enlightened than the Tutsi and unable to lead the country) from the chieftainship. They nominated Tutsi chiefs in regions where, prior to the colonial role, Hutu chiefs had been ruling.

Also, they had a big role in the Rwandan genocide in 1994 because post-colonial leaders pursued a system similar to the colony and maintained the negative colonial legacy of the ethnic division for all most three decades. Also, they systematically practiced a strategy of exclusion and repression that placed the country’s long-term stability under threat, gradually led to civil war and caused the genocide of 1994.

2.3.4 Poor economic performance

Many African countries faced internal conflicts because of the poor economic performance; the per capita income has fallen; the unemployment rate has risen, and the price of consumer goods has increased, and these factors made the people angry and worry about their lives. Africa is a youthful continent because a high percentage of its population consists of youth between the age of 15-30 and most of them have no opportunity to get education and jobs. So, the youth are likely to prefer war over peace as long as the government does not offer them an alternative means for a better life. Bad economic conditions have led to civil war for most of the countries that experienced conflict in Africa including Rwanda and Sierra Leone as Oyeniyi & Media (2011, p. 4) emphasize that low economic accomplishment brought a more and long-term conflict in many African countries, interfaced with the debt problem, poor flows of private capital and inefficient foreign aid programs.

On the other hand, many researchers label poor economic performance as a contributing factor to the conflict, but they do not consider it as the root cause of the conflict. They have listed many contributing factors that lead to internal conflicts such as the culture that promotes violence, a foreign intervention that intends to create tensions between the people and the rate of youth unemployment that is possible to resort to conflict. Poor economic performance is regarded as one of the root causes of internal conflict in Sub- Saharan African countries and many authors support this view for instance the conflict in Somalia is referred to the bad economic situation that Somalis lives under the dictatorship government of Siyad Bare because “prior to the civil war in 1991, Somalia was one of the poorest countries in the world with a high level of dependence on foreign aid. Its gross national product (GNP) per capita was US$170 and its life expectancy only 47 years” World Bank (2005, p. 23).

2.4 Economic Policy Priorities for Post-Conflict Recovery

In this section, economic policy priorities for post-conflict recovery are discussed since everything seems to have priority in the reconstruction and development process of post-conflict situations. The study examines the role of four factors in the peacebuilding process and in the economic growth and recovery of post-conflict countries. These variables are military expenditures, domestic investment, foreign aid, and FDI.

2.4.1.1 Empirical evidence on foreign aid on foreign direct investment in post-conflict countries

The foreign aid is necessary for post-conflict societies because the war destroys the public and private properties and the life of the people deteriorates after the conflict. Foreign aid is an important financial flow that any post-conflict government in coordination with international donors must set policies to make it effective and efficient for the reconstruction and the development process. The foreign aid mainly comes into two forms which are: humanitarian aid and official development assistance. Although humanitarian aid is required after the wartime to save the lives and alleviate the rate of people suffering from man-made disaster what post-conflict government needs more is official development assistance to restore peace and stability and achieve economic recovery. Donors can support the post-conflict government in restoring law and order, an institutional building and reconstruction of infrastructure. Foreign aid contributed to the economic growth of many post-conflict countries; Mozambique is a prominent example. Mozambique is clearly a success story in terms of growth and poverty reduction since 1992. We have demonstrated that aid has played a determinant role in making this possible. Without sustained aid at a high level there is no way in which Mozambique would have been able to: (i) establish peace so smoothly; (ii) manage the challenge of postwar stabilization; and (iii) carry out widespread reconstruction. As a result, Mozambique is now in a much stronger position than at independence. Based on the growth accounting carried out in this paper, we conclude that aid-financed government investment in public goods, particularly public infrastructure, education, and health; have been fundamental channels through which aid has contributed to development outcomes. Intended outcomes of aid have been largely achieved although its potential contribution to agricultural transformation and development is yet to materialize (Moreira, 2005, p. 1). There is mixed evidence regarding the effect of foreign aid on foreign direct investment in Sub-Saharan African countries. Many researchers advocate the role of foreign aid in promoting foreign direct investment, but others contend that foreign aid has a negative effect on foreign direct investment, and each has reasons to justify. Asiedu (2002, p. 1) examined the relationship of foreign direct investment in developing countries in comparison to Sub-Saharan Africa and non-Sub-Saharan countries. The OLS, cross-sectional and panel regression estimation techniques were used by the researcher to determine the relationship of the period from 1988 to 1997. The findings concluded that infrastructural development and higher returns on investment have a positive effect on foreign direct investment for non-Sub-Saharan countries. However, the insignificant advantage attributable to this was found to be smaller for Sub-Saharan Africa. Asiedu (2002, p. 1) also categorized foreign direct investment into two types: market-seeking and non-market seeking. The former relates to that operating in the local market of the host economy, which is ascertained by the magnitude of the domestic demand alongside the level of income in the domestic economy. Hence non-market seeking foreign direct investment is geared towards exports and local demand is often ignored. In other words, it entails the production of goods domestically with the aim of selling overseas. It was concluded that there are different effects in relation to successfully implement policies in other regions as it may be different in Africa. The comparative analysis between the two regions was definitely an exclusive contribution, but the time frame of the study of the data was quite short and this may have had an effect on the estimation of the results and its accuracy.. Despite the significant research done so far, the empirical evidence of the relationship between foreign aid and foreign direct investment has so far been ambiguous with a different outcome, as most of the studies focused on economic growth. Actually, foreign aid and foreign direct investment are significant derivations for post-conflict countries, and they are very important in the accumulation of human and physical capital as well as the boost of economic development in these economies. In respect to the aforementioned gaps, my motive in this thesis is to examine the short-run and long-run relationship between foreign aid on foreign direct investment.

2.4.2 The empirical evidence on the effects of military spending in reducing the risk of a new conflict

The risk of new conflict is very high in post-conflict situations because when a country emerges from a conflict it is likely to face another conflict because there is great mistrust between the people. The post-conflict government must consider its condition and develop policies to reduce the risk of conflict renewal because “post-conflict societies face an enhanced risk of conflict turnaround. Governments will therefore consequently be bothered, not only with economic recovery as an end in itself but with adopting economic policies that help reduce the risk of conflict” (African-Bank, 2008, p. 46). The governments in post-conflict countries try to develop policies to minimize the risks and avoid anything that can become a reason for provoking violence and conflict but most of the policies of the governments do not work. Also, the role of the international community in helping post-conflict countries to set its policy priority is not effective; developing better policies, the risk of peace collapse after the civil war in Africa can be minimized. As we discussed before one of the main factors that contribute to the conflict are economic ones, so the government must try to achieve inclusive economic growth and reduce the inequality in the distribution of national income.

There are many factors that can cause new conflicts in post-conflict situations, but the two major factors are the risks coming from the rebel groups and unemployed youth. First, we discuss how the post-conflict government can reduce the risk of new conflict through military spending. Second, we talk about the role of youth unemployment in the conflict level. One of the policies that the government can reduce the risk of new conflict is to restore the law and order by increasing military spending but some researchers argue that high military expenditure does not promote peace and recovery but may cause new conflict and they propose reducing the money spent on military because “high military expenditure by the government in post-conflict societies is useless. It significantly and essentially increases the threat of further conflict. We find that an approach of profound cuts would diminish the threat from around 39% to around 24%. It is not theoretical: this was exactly the policy of the post-conflict government of Mozambique. Not just

has Mozambique maintained peace and stability, but there has been swift growth of the economy (Collier, 2006, p. 4).

Several studies indicate that military expenditure crowds out investment in economically productive sectors, thereby lowering economic growth (Rothschild 1973; Smith 1980; Deger and Smith 1983; Leontief and Duchin 1983; Lim 1983; Landau 1985; Mintz and Huang 1990; Ram 1995; Dunne, Nikolaidou, and Smith 2002). Other studies show that military expenditure boosts business confidence in conflicting countries, which facilitates investment and economic growth (Kennedy 1974; Benoit 1978; Whynes 1979; Barro and Sala-i-Martin 2004; Dunne, Smith, and Willenbockel 2005). In retrospect, several studies suggest that military expenditure has a non-linear effect on economic growth, conditional upon exposure to conflict (Frederiksen and Looney 1982; Landau 1996; Cothren 2002; Aizenman and Glick 2006; Aziz and Niaz Asadullah 2017). Economic growth is an outcome of both internal and foreign investment in a country. According to the above literature, in the presence of conflict, positive economic growth is subject to positive growth in military expenditure. This leads to a pertinent question; is FDI inflow also conditional on an increase in military expenditure in the face of armed conflict? Some post-conflict countries had successfully implemented DDR (disarmament, demobilizing and reintegration) programs while others still have so many challenges and difficulties in implementing it. For example, Rwanda has a success story in its DDR program As Lötscher (2014) indicates that Rwanda's approach to DDR and reconciliation including its applied programs are widely praised for their uniqueness and effectiveness. The peacebuilding processes in Rwanda have been arguably the most successful in Sub-Saharan Africa, and Rwandans today live together in peace and harmony without visible tensions. Therefore, Rwanda can be seen as a positive role model for other post-conflict states that develop and manage peacebuilding processes.

On the other hand, the civil war in Sierra Leone lasted for 10 years and the international community has helped the government to develop policies to disarm and reintegrate the ex-combatants. Although Sierra Leone has no high economic transformation like Rwanda, it had successfully implemented the DDR program. Douma & Gasana (2008, p. 6) indicate that the reintegration of ex-combatants started in Sierra Leone Since its inception in 1998, the DDR program has been interrupted twice by the resumption of fighting. NCDDR opened the first demobilization camp for 3,000 ex-combatants in 1998. DDR was suspended when Freetown was attacked in January 1999. After the signing of the Lome Peace Agreement in July 1999, five demobilization camps opened, and 22,500 ex-combatants were disarmed over the period of a year. DDR has halted again when fighting resumed in May 2000 and the RUF kidnapped 500 UN peacekeepers and the DDR program targets about 45,000a combatantthe s, including members of the RUF and pro-government militias, the Civil Defense Forces. The government agency responsible for the DDR program is the National Committee for Disarmament, Demobilization, and Reintegration (NCDDR), primarily funded through the World Bank's Multi-Donor Trust Fund (MDTF). NCDDR has numerous partners who implement the program activities. The UN peacekeeping force (UNAMSIL) is responsible for the disarmament phase of the program, and various local and international NGOs implement the bulk of the reintegration programs. The ex-combatants had five options that were to 1) return to their former jobs; 2) go back to formal education school; 3) engage in vocational training; 4) receive support to start a new business and 5) receive income-generating activities and support. The vast majority of the ex-combatants reintegrated receiving income-generating activities.

So, the DDR program is very important for every country coming from years of internal conflict and intends to achieve recovery and sustained development. It is necessary for restoring peace and stability after the conflict and the government must give great considerations in the early times. The failure in this program may cause reversion into new conflict because the ex-combatants must be directed and get livelihood projects that enable them to go back to their normal lives. For example, in Mozambique, the DDR contributed to the peacebuilding process since “programs provided demobilized soldiers with 18 months of subsidies in the form of cash disbursements and provided reasonable assurance of financial support for an extended period. During this 18-month period, it was hoped that the former combatants would find employment and integrate into the local community. The RSS program also provided vocational kits that consisted oa f agricultural tools, seeds, and food rations for up to three mo innths” (Edloe, 2007, p. 20).

The second factor that represents a threat to the peaca e-building process of post-conflict countries is the high youth unemployment rate because the percentage of youth in Africa is very high and over 50% of Rwandan population is under 20 years old. Most of the youth are unemployed ones who have no job opportunities. In general youth unemployment is associated with the conflict level because the unemployed youth can be easily recruited by the rebels in the war during post-conflict situations. According to Azeng et al (2013, p. 4) youth unemployment is significantly associated with an increase of the risk of political instability. They suggest that exceptionally large youth unemployment rate, associated with socioeconomic inequalities and corruption, make countries more susceptible to political instability and national insecurity.

The international donors and the government should set a strategy to create employment opportunities for the youth and all the classes of the society because when more jobs are created, the expectations of the people will change dramatically. More strategies to surmount youth unemployment are necessary because if unskilled young men can be employed, the rebels do not get the opportunity to recruit them into violence. Indeed, economic growth brings down the risks by offering ja ob opportunities to young men and women. On the other hand, some scholars contend that youth unemployment is not the reason for the conflict and that there are other factors induce the youth to the violence. Amarasuriya et al (2009, p. 6) reject the concept that youth unemployment caused armed conflict and they argue that such concept cannot reflect many factors increasing young people’s frustrations and grievances in conflict contexts; and the multiple barriers young people face in entering the job market. It also ignores the fact that youth is a highly heterogeneous group with a different class, gender, political and geographic lines. Many emphases are needed on the country-specific study of the links between youth unemployment and other socio-economic and political factors that contribute to marginalization and discrimination that cause conflict and violence at a more structural level.

2.4.3 The effects of domestic investment on foreign direct investment

There is not much empirical evidence on domestic investment flow on foreign direct investment most of the previous research focused on the flow of domestic investment on economic growth. A research paper in 1999 by McMillan was evidently the first that clearly focuses on this issue.

According to McMillan, there is a negative relationship between domestic investment and FDI. McMillan concluded that domestic investment does not lead FDI: The question was asked “Does domestic investment promote FDI? The answer in relation to the above question appeared to be no. The answer no to the question is in relation to both developing countries and the OECD countries.” This conclusion is in relation to the inconsistency that when local firms choose to invest more, foreign companies choose to invest less - results directly from the method chosen to measure domestic investment: domestic investment = gross fixed capital formation (GFCF) minus FDI. But FDI is a balance of payment data, not a national account one. FDI does not interpret nor instantaneously either consistently systematically into the real capital formation in the host country. For example, the acquisition of a local company by a foreign investor is a transfer of assets. It will result in a capital inflow, noticed in the balance of payment, but it will not increase capital formation in the country. Furthermore, FDI flows are far more volatile than GFCF. As a result, FDI variation will largely determine the change of the proxy used to measure domestic investment (-FDI+GFCF), and there will always be a negative relationship between these two variables. Ndikumana and Verick (2008, p.1) research was done on Sub-Saharan Africa, examined whether domestic investment promotes FDI and is in turn affected by FDI. Their research covers 38 African countries from 1970 to 2005, and they divided private domestic investment and public domestic investment, thanks to a World Bank database on Africa. They conclude in the opposite way. Their results indicate that the relationship between FDI and domestic investment run both ways. But the positive impact of domestic investment on FDI, especially in the case of private investment, is more enhanced and more robust than the reverse relation. Public domestic investment also has a positive influence on FDI inflows.

The government of Rwanda implemented infrastructure and rehabilitation projects especially in water supply, electricity supply, and transport infrastructure. In the year 2000, a small percentage of Rwandans could find clean water, but the government allocated a large portion of its budget in water supply development projects. The number of people who have access to safe water increased because of government efforts, along with donor support and in 2015 more than 70% of the population had access to water and in 2017, the government plans to increase the percentage to 100%. Also, the government spent a large amount of money on sanitation since the roads and public places were full of garbage. In Rwanda, electricity supply was generated from power stations on lakes until the early 2000s. The electricity supply from power stations decreased because the two lakes’ water level has fallen in 2004 and this came when the demand for electricity was increasing as the economy started to grow and the business and industry sector was very in need for high electricity supply. The government established diesel generators that increased the supply of electricity, but the diesel generators were very costly.

Also, the government rehabilitated certain power stations on lakes to solve the problem of electricity. In 2009, an estimated 28% of the people had access to electricity but in 2017 the government targets 70% of households to get electricity, likewise in 2002 Sierra Leone develop the Bumbuna hydro-power station but till date it only supplying the capital city Freetown through rotational policy, though the past government initiated the idea of working with the Turkish based power plant Kara- Deniz, and it is still not enough to supply the whole country. The government of Rwanda implemented transport infrastructure projects getting development assistance from donors. It rehabilitated the roads between the capital and other major cities and also built new roads in the country. Rwanda is a landlocked country that is a member of the East African Community and it is linked by road to these countries.

The most important trade route is the road to Mombasa via Kampala and Nairobi and most imported goods come through this road. Also, the government implemented the reconstruction of an international airport at Kigali. One of the early jobs of policymakers is to reduce capital outflows because those resources are essential for the contribution of the economy and “capital flight is a blight that has seriously undermined growth and development in the sub-Saharan region. Reduction of capital flight is essential to increase the resources available in sub- Saharan countries for both consumption and investment, public and private” (Weeks, 2012, p. 14). Reforms in policy and business regulations are needed for minimizing the capital flight as well as attracting more capitals. So, the priority of the government must be the repatriation of capitals. The government must try to prepare the necessary institutional and physical infrastructure to rebuild the financial systems, reduce capital flight and increase capital repatriation, and develop policies that encourage the international community to give and maintain large amounts of aid which is the main source of funding of the reconstruction process in the short to medium term following a civil war. Also, the African Diaspora can contribute more to the peace-building process in their countries if the government and the donors help them participate in the reconstruction and development process. This is absolutely necessary if the objective is to mobilize the financial resources and the human capabilities of the sizeable number of African Diaspora living in the western countries for peace promotion and stabilizing the countries they came from. The government can also increase capital inflows by creating a business-friendly environment and encourage people to invest in the country. The private sector investment is very essential for the recovery of a post-conflict country. According to Mills & Fan (2006, p. 10), although creating a good climate for investment is important in any developing country, it has special importance in post-conflict times for three reasons. First, the private sector generates sustainable employment because job opportunities are very necessary for demobilized ex-combatants, giving them a stake in the peacebuilding process.

Second, the private sector takes a major role in filling the gap left by the reduced capacity of governments to offer public goods and services in the post-conflict period. Third, these three factors are essential for solving some of the principal ‘greed’ and ‘grievance’ issues which increase the probability of reversion to a new conflict. Sources of domestic investment in both Rwanda and Sierra Leone are domestic saving, remittances and government revenues from taxes and foreign aid. Domestic savings are small in Sierra Leone since it is a largely agriculture-based country where most people work on subsistence farming and there is no developed banking system that can give credit to the small farmers, but the saving performance has been improving since the peace agreement was signed in 2002. Also, remittance contributes to the domestic investment because a large number of Sierra Leonean and Rwandan Diaspora send money back to their families for consumption and investment in small private enterprises and the remittance is one of the main financial flows that these countries finance their trade deficit. The small and vulnerable economy as that of Sierra Leone, remittances represents a very significant part of foreign exchange earnings and it is ranked as the second financial factor for development after official development assistance. Rwandan government-initiated programs encouraging the people to change the saving culture and invested more in financial systems including the banking and capital market system. The people started to save their money in the banks rather than their homes and the banking sector is expanding throughout the country. The people who live in urban areas save more than those who live in rural areas and domestic savings is expected to reach 20% in 2020 while now the rate of saving is about 11%.

2.4.4 The effect of gross domestic product on foreign direct investment

There is little empirical evidence on the effect of gross domestic product on foreign direct investment as many scholars focus on the effect of foreign direct investment on growth but few empirical evidence are available namely (Noorbakhsh et al. 2001, p. 25), infrastructure (Wheeler and Mody 1992, p. 35), a profound atmosphere for international investors such as political stability (Schneider and Frey 1985, p. 40), trade openness (Albuquerque et al. 2005, p. 35; Gastanaga et al. 1998, p. 45), relative costs such as labor cost (Lucas 1993, p. 1), taxes and tariffs (Gastanaga et al. 1998, p. 46; Wei 2000, p.20), and access to natural resources (Agosin and Machado 2007, p. 1).

Several research concluded on the effects that economic growth is an incentive for FDI inflows (e.g. Al Nasser 2010, p. 1; Jiménez 2011, p. 14; Kandil 2011, p. 17; Mohamed and Sidiropoulos 2010, p. 20). There are various justification for why foreign investors would rather invest in faster-growing markets. For instance, the cost level of production and the realization of economies of scale and scope in production are extensively correlated with market size (Wang and Swain 1995, p. 20). All things being the same, an expanding market can be appealing to foreign direct investment due to the fact the probability that a larger market will enable a more efficient scale of production through the attainment of economies of scale (Agosin and Machado, 2007, p. 1; Carstensen and Toubal, 2004, p. 14). That is, growth is a benchmark and indicator of market demand and market demand attracts FDI. Torrisi (1985, p. 1) notes that while considering FDI venue the decree hinge on only on recent or past earnings, they rely also on the potential and expected profitability of the specific investment project in a particular location. The possibilities for market growth would need to be positive to ensure a long-term commitment by the foreign investor. Lim (1983, p. 35) and Zhang (2001, p.1) argue that a higher economic growth rate, other things being equal, leads to a higher level of aggregate demand, leading to greater opportunities for making profits and, hence, increasing the incentive to invest. These incentives attract FDI to growing regions. Torrisi (1985, p. 20) notes that while FDI location decisions depend only on recent or past earnings, they rely also on the potential and expected profitability of the specific investment project in a particular location. The prospects for market growth would need to be favorable to ensure a long-term commitment by the foreign investor. Several research studies report negative effects of economic growth on FDI. For instance, Buchanan et al. (2012, p. 26), Jensen (2003, p. 50), all find considerably negative effects of economic growth in attracting FDI in developing countries. Albuquerque et al. 2005, p. 25; Asiedu 2002, p. 26; Reece and Sam, 2012, p. 1 find out that developing countries seek to attract international investors by offering new and relatively unexploited markets, access to natural resources and relatively cheap labor, locational advantages, and direct and indirect incentives. Hence, it is an empirical issue whether economic growth attracts has no effects on at all on foreign direct investment as it is entirely possible that growth has a positive effect on FDI in some aspects, while it has a negative or even no effect in other

3. Research Methodology

3.1 The Model Specification

The model has five variables which hypothesize that foreign direct investment is a function of the real gross domestic product, domestic investment, foreign aid, and military expenditure.

FDI_t
= F(GDP_t
DI_t, Aid_t, MX_t) (3.1)

FDI_t
stands for foreign direct investment that refers to direct investment equity flows in the reporting economy. It is the sum of equity capital, reinvestment of earnings, and other capitals. Data are in current U.S. dollars. GDP_t
stands for the total monetary value of all goods and services produced within a country’s borders in a specific period of time. Data are in constant 2010 U.S. dollars which means the study considers the data of real GDP. Also, DI_t
stands for domestic investment that is the amount of public and private capital which is invested in domestic production either through the purchase of fixed property or inventory. Data are in constant 2010 U.S. dollars

Aid_t
stands for foreign aid that is the international transfer of capital, goods, or services in the form of loans or grants from a country or international organization to promote economic development and welfare of the recipient country. Data are in constant U.S. Dollars. MX_t
stands for military expenditure that is the total amount of money spent on the military by the government or donors. The data are in constant 2014 U.S. dollars.

The sample consists of 148 observations of quarterly time series data from 1980 up to 2016. We have considered this time period because it enables us to examine the post-conflict economic conditions of both Rwanda and Sierra Leone; since the genocide and civil war in both countries had happened in 1994 and 1991respectively. The data of domestic investment, foreign aid, and foreign direct investment was taken from the indexmundi Indicators (World Bank). The data on military spending was taken from the Stockholm International Peace Research Institute (SIPR).

3.2 Stationarity Test

“In short, if a time series is stationary, its mean, variance, and autocovariance (at various lags) remain the same no matter at what point we measure them; that is they are time-invariant” (Gujarati & Porter, 2003, p. 798). Testing the stationary of time series data is necessary because it may affect its behavior. If the series of variables are non- stationary, we can study its behavior only for the time period under consideration. It is not possible to generalize it to other time periods. Therefore, for the purpose of forecasting, such (non-stationary) time series may be of little practical value.

If we estimate x and y series that are a non-stationary random process, it will generate a spurious regression.

Y_t
= a+bX_t+u_t
(3.2)

Spurious regression provides misleading statistical evidence of a linear relationship between independent non-stationary variables.

There are three conditions for stationarity:

E[X_t] = μ (3.3)

Var [X_t] = σ² (3.4)

Cov (X_t, X_t+h) = f(h) (3.5)

So time series is stationary when its mean and variance are constant over time. We take the difference in the series to make it stationary. Differencing the series generates a new set of observations such as the first-differenced variables, the second-differenced variables and so on.

X level X_t
(3.6)

X 1^st-differenced value X_t-X_t-1
(3.7)

X 2^nd- difference value X_t-1-X_t-2
(3.8)

A series that is stationary at a level without differencing it is termed I (0) or integrated of order zero (0). Also, a series that is stationary after taking the first difference is designated I (1) or integrated of order one (1.). And a series that became stationary after taking the second difference is known I (2) or integrated of order two (2).

Different methods are used to test the stationarity of the variables but the Augmented Dickey-Fuller test is used in this study.

3.2.1 Augmented Dickey-Fuller test

Augmented Dickey-Fuller test (ADF) is used to test the null hypothesis of a unit root presence in a time series sample. The alternative hypothesis is that the series is stationary.

The null hypothesis H₀
= δ = 0 (3.9)

The alternative hypothesis H1 = δ

The ADF test is composed of estimating the following regression:

i=1 i

ΔY_t
= β₁+ β_2t+δY_t-1+ Σ^m
α ΔY_t-i+u_t
(3.11)

Where i_t
is a pure white noise error term and where

ΔY_t-1
= (Y_t-1- Y_t-2), ΔY_t-2
= (Y_t-12- ΔY_t-3) (3.12)

So, if a time series has a unit root, the first difference of such time series is stationary. Therefore, the solution here is to take the first difference of the time series.

3.3 Testing of Cointegration

Cointegration test is needed because standard regression analysis fails when dealing with non-stationary variables and leads to spurious regression which suggests relationship even where there is no relationship. In non-stationary variables, it is often found high R-squared and low p-values when the OLS method is used even though there is no relationship between the non-stationary variables.

In principle, testing for cointegration is similar to testing the linear regression residuals (u_t) for stationarity. So, to establish a cointegration relationship, you would run first an OLS regression model for your variables and test the residuals for stationarity.

3.3.1 Johansen cointegration test

The Johansen test deals with testing a cointegration by examining the number of independent linear combination (k) for an M time series variables set that produces a stationary process. There are two forms of Johansen test: the trace test and the Maximum Eigenvalue test. Both tests address the Cointegration presence hypothesis, but each asks very different questions.

3.3.1.1 Trace test

The trace test examines the number of linear combinations (i.e. K) to be equal to a given value (K₀), and the alternative hypothesis for K to be greater than K0

H₀: K = K₀
H₀: K > K₀
(3.13)

To test for the existence of Cointegration using the trace test, we set K0= 0 (no cointegration), and examine whether the null hypothesis can be rejected. If we reject the null hypothesis, then it means there is at least one cointegration relationship, so we need to reject the null hypothesis to establish the presence of Cointegration between variables.

3.3.1.2 Maximum Eigen-value test

With the Maximum Eigen Value test, as Trace test, the same central question is asked but the difference comes from the alternative hypothesis:

H₀: K = K₀
H₀
: K = K₀₊₁
(3.14)

So, starting with K0 = 0 and rejecting the null hypothesis implies that there is only one possible combination of the non-stationary variables to produce a stationary process.

A special case for using the Maximum Eigen Value test is when K0 = m-1, where rejecting the null hypothesis implies the existence of m possible linear combinations. This is impossible unless all input time series variables are stationary (I (0)) to start with.

3.4 Vector Error Correction Model (VECM)

Vector error correction model (VECM) is used in multiple time series when the variables under consideration are cointegrated. The model is important for estimating both short-term and long-term effects of a one-time series on another. The error term estimates the speed at which a dependent variable returns to equilibrium after a change in other variables.

When all the variables are stationary at first difference and cointegration between them is found that means the existence of a long-term equilibrium relationship between the series. In this case, VECM is used to examine the short and long-run relationship between the variables. The regression equation for our VECM will be as follows:

ΔY_t
= δ₀+ Σ^p
_i=0
δ₁ΔX_t-1+ Σ^k
_j=1
β₁ΔY_t-1-λ(Y_t-1- α₁- β₁
X_t-1)+u_t
(3.15)

In this model the cointegration rank shows the number of cointegrating variables. For example, the rank of four indicates that four linearly independent combinations of the non-stationary variables will become stationary. A negative and significant coefficient of the equation means that any short-term fluctuations between the dependent variable and explanatory variables will cause to a stable long-run equilibrium relationship between the variables

4. ANALYSIS

4.1 Graphical Analysis

First, we do a graphical analysis to examine the trends in our variables and try to discuss the reasons behind the trends in the series of the variables in Rwanda and Sierra Leone. Also, graphical analysis enables us to compare the economic performance of both countries.

Figure

4
.
1. Foreign direct investments (FDI) of Rwanda

Figure

4
.
2
.
Foreign direct investments (FDI) of Sierra Leone

In Sierra Leone, foreign direct investment was a positive from 1980 to 1987 and has been low since 1991 mainly because of the civil war then and reaches it recorded minimum level in 2016 as the country could not attract more foreign capitals because of its long-term internal conflict and poor governance system but the FDI had risen in the period between 2011 to 2015. We see 99% increase in FDI in 2011 but in 2012 FDI recorded 29% decrease and the fall in FDI is attributed to the halt of the mining sector as the country fail to retain investor in the mining sector.

For Rwanda, foreign direct investment was close to zero from 1994 up to 2005 but FDI has risen after 2005 where FDI has increased 14% which was a high percentage in 2009. In 2010 FDI again decreased to 6% but after that, it has been increasing significantly.

Figure

4
.
3
.
Gross domestic product (GDP) Rwanda

Figure

4
.
4. Gross domestic product (GDP) Sierra Leone

According to figure 4.2. Sierra Leone the real gross domestic product declined sharply in 1985, this was as a result of severe macroeconomic instability including per capital incomes, high inflation and low domestic revenue, and experience a rise again until 1991, when the civil war broke out in March 1991 led by the Revolutionary United Front (RUF), and was fluctuating and fall sharply due to the intervention of the RUF (Revolutionary United Front) in the capital city, Freetown, social and physical infrastructures was destroyed, as we as mining was halted, farms abandoned, manufacturing and related sectors disrupted, while in 2000, the effect of the signing of the peace agreement in Lomé on July 7, 1999, which ended the most devastating phase of the civil war in Sierra Leone, started to yield results, until 2015 after the decline of mining in the country, while Rwanda was experiencing growth but experienced its lowest growth rate in 1994 which is the year of genocide. In Sierra Leone, the real GDP started to rise infinitely after 2002 when the newly installed President Ahmad Tejan Kabbah declared the Sierra Leone Civil War had finally ended, while Rwanda the GDP also started to rise mainly because of the end of the civil war ended with the victory of the RPF (Rwanda Patriotic Front) party led by the current president Paul Kagame and after political reconciliations; they developed policy reforms for economic transformation. After two decades, Rwanda achieved high economic growth because in 1995 the growth rate was 3.5% but in 2010 the growth became 7%.

In Sierra Leone, since 2002 the real GDP has been increasing but at decreasing rate until 2010 because of the main challenges of restoring and sustaining macroeconomic stability, improve public service delivery, improve economic/sector governance (PFM), support drivers of growth, facilitate full potential for creating jobs, reducing poverty and improving living standards. After 2010, the growth rate started to increase extensively because the country maintained relative political stability but again growth rate has fallen in 2016 because of the halt of mining in the country.

Figure

4
.
5. Domestic investment (DI) of Rwanda

Figure

4
.
6
.
Domestic investment (DI) of Sierra Leone

For Sierra Leone, domestic investment has been fluctuating since 1980, and fall sharply in 1999 due to the intervention of the Rebels in the capital city. From the years 2000 to 2010, domestic investment rate was low, but it began to increase after the year 2010 reaching its maximum level in 2012. After the peace agreement in 2002, the government and the donors implemented useful development projects such as infrastructure rehabilitation and institutional building. In 2010 the rate of domestic investment increased, and it can be associated with the boom of the mining sector which greatly has an impact on the economy. Also, after 2012, domestic investment started to fall because of the halt of mining in the country.

In Rwanda, in 1994 domestic investment recorded its lowest rate because of severe conflict and genocide in that year but after this year the country maintained high political stability and domestic investment has been increasing extensively.

Figure

4
.
7
.
Foreign aid to Rwanda

Figure

4
.
8
.
Foreign aid to Sierra Leone

The figure shows that foreign aid was fluctuating since 1980 but rise sharply after the start of the civil war, but start to fall in 1995 after discussion was in place for a table talk for the conflict and that resulted to recorded low rate in 2000 and then a large amount of aid was given to Sierra Leone and mostly the foreign aid in Sierra Leone was in the form of humanitarian, after the end of the war in 2002 it declined sharply in 2013 but rise sharply till 2015, and till then falling after aid organization declared Sierra Leone as in a stable state. In Rwanda, the figure shows fluctuations in the amounts of foreign aid, in 1994 the amount of foreign aid has reached its maximum level because at this year the civil war ended, and donors started to give more humanitarian aid and development assistance to Rwanda.

Figure

4
.
9
.
Military expenditure of Rwanda

Figure

4
.
10
.
Military expenditure of Sierra Leone

The figure 4.5 shows that there was a high military expenditure in Rwanda between the years of 1994 because Rwanda experienced its civil war during that time period and the military variable has been fluctuating from 1994 to 2016 with decreasing rate and then military expenditure has a low steady-state level. In Sierra Leone, despite the military expenditure variable has been fluctuating all over the time, the figure shows that the government increased its military spending between 1980 up to 1985 and rise sharply from 1991 to 994 because the civil war period lasted from 1991 up to 2002. So, the government allocated a large amount of money to military expenditures but after that, the level of military expenditure has been reduced.

4.2 Stationarity Test Results

The stationarity of the variables is checked to know if the series has the same mean and variance over time. Several tests are used for checking the stationarity of the time series but in this study, ADF (Augmented Dickey-Fuller) test is used for unit root test.

4.2.1 Augmented dickey-fuller test

Table 4.1 The results below shows that at Level and Intercept with lag of (0), the results for the ADF test show that FDI, GDP, DI, AID, MS are nonstationary at a significant level of 5 %, that is we fail to reject the null hypothesis for unit root, that means the series contained unit root processes and thus it’s nonstationary, and at first difference with lag of (Uysal et al.) and at a significant level of 5% the results for ADF test show that FDI, GDP, DI, AID, MS are stationery that is we successful reject the null hypothesis for unit root. That means the series at first difference (1) is stationary.

Table 4.2.1 Unit Root Test for the series of Rwanda based on Augmented Dickey-Fuller test and Lag Length Base on the Schwartz Bayesian Information Criterion.

Table 4.2.1 The results below shows that at Level with lag of (0), the results for ADF test show that FDI, GDP, DI, AID, MS are nonstationary at a significant level of 5% ,that is we fail to reject the null hypothesis for unit root, that means the series contained unit root processes and thus it’s nonstationary, and at first difference with lag of (Uysal et al.) and at a significant level of 5% the results for ADF test show that FDI, GDP, DI, AID, MS are stationery that is we successful reject the null hypothesis for unit root. That means the series at first difference (1) is stationary.

Table

4
.
1
.
Unit Root Test for the series of Rwanda based on Augmented Dickey-Fuller test and Lag Length Base on the Schwartz Bayesian Information Criterion

Variables	Level Intercept ADF t-Statistic	First Differences Intercept ADF t-Statistic
FDI GDP DI AID MS	0.178979 (0) 3.364755(0) 7.254572(0) -0.011868 (0) 2.196228 (0)	-6.607492 (1) -4.529724(1) -4.327149(1) -5.771671 (1) -4.724517 (1)

Table

4
.
2
.
Unit Root Test for the series of Sierra Leone based on Augmented Dickey-Fuller test and Lag Length Base on the Schwartz Bayesian Information Criterion

Variables	Level Intercept ADF t-Statistic	First Differences Intercept ADF t-Statistic
FDI GDP DI AID MS	0.230219 (0) 0.727122 (0) -0.060902 (0) -0.957296 (0) -1.433169 (0	-4.691248 (1) -3.476385(1) -4.038191 (1) -4.304777 (1) -5.002099 (1)

4.3 Lag Length Determination of The Model

A Var lag order selection criterion is used to determine optimal lags in the Vector Error Correction Model (VECM). Var lag order selection criteria show the maximum lags by comparing different criteria such as Akaike information criteria and Schwarz information criterion. The table shows that two lag is optimal for the Vector Error Correction model since four criterions selected two lag. So, the study uses two lag for the Vector Error Correction Model.

4.3.1 VAR lag order selection criteria (Rwanda)

Table

4
.
3
.
VAR Lag Order Selection Criteria (Rwanda)

Included observations: 144
Lag	LogL	LR	FPE	AIC	SC	HQ
0	-12363.30	NA	2.76e+68	171.7820	171.8851	171.8239
1	-11134.90	2354.449	1.52e+61	155.0680	155.6867	155.3194
2	-10990.64	266.4647*	2.91e+60*	153.4117*	154.5460*	153.8726*
3	-10976.08	25.89793	3.38e+60	153.5566	155.2065	154.2270
4	-10968.66	12.66783	4.34e+60	153.8008	155.9663	154.6808

4.3.2 VAR Lag order selection criteria (Sierra Leone) VAR lag order selection criteria (Sierra Leone)

Table

4
.
4
.
VAR Lag order selection criteria (Sierra Leone) VAR lag order selection criteria (Sierra Leone)

Lag	LogL	LR	FPE	AIC	SC
0	-12339.98	NA	2.00e+68	171.4580	171.5611
1	-11246.64	2095.567	7.19e+61	156.6199	157.2387
2	-11074.23	318.4715	9.30e+60*	154.5726*	155.7070*
3	-11052.75	38.19419*	9.79e+60	154.6215	156.2714
4	-11045.61	12.19385	1.26e+61	154.8696	157.0351
* indicates lag order selected by the criterion
LR: sequential modified LR test statistic (each test at 5% level)
FPE: Final prediction error
AIC: Akaike information criterion
SC: Schwarz information criterion
HQ: Hannan-Quinn information criterion

4.3.3 Cointegration Testing

Cointegration test is conducted to examine the long-term equilibrium relationship between the variables.

4.3.4 Johansen cointegration (Rwanda)

This study adopted Johansen Cointegration test and as in table 4.3, both Trace and Maximum Eigen Value test indicate the null hypothesis that there is no long-term relationship among variables can be rejected since the P value is less 5%. In contrast, both Trace and maximum Eigen Value test show that at most four variables are cointegrated since their P value are greater than 5%. So, all the variables are cointegrated and have equilibrium relationship in the long run.

Table

4
.
5
.
Johansen Cointegration test for the series of Rwanda

Unrestricted Cointegration Rank Test (Trace)
Hypothesized		Trace	0.05
No. of CE(s)	Eigenvalue	Statistic	Critical Value	Prob.**
None *	0.335855	106.1218	69.81889	0.0000
At most 1	0.161169	46.77981	47.85613	0.0629
At most 2	0.074262	21.29655	29.79707	0.3394
At most 3	0.049314	10.10783	15.49471	0.2725
At most 4	0.018956	2.774978	3.841466	0.0957
Unrestricted Cointegration Rank Test (Maximum Eigenvalue)
Hypothesized		Max-Eigen	0.05
No. of CE(s)	Eigenvalue	Statistic	Critical Value	Prob.**
None *	0.335855	59.34202	33.87687	0.0000
At most 1	0.161169	25.48325	27.58434	0.0907
At most 2	0.074262	11.18873	21.13162	0.6284
At most 3	0.049314	7.332847	14.26460	0.4505
At most 4	0.018956	2.774978	3.841466	0.0957

4.3.5 Johansen cointegration (Sierra Leone)

Cointegration test is conducted to examine if the variables have a longterm equilibrium relationship. As the table 4.4 shows this study adopted Johansen test and according to the trace and Maximum Eigen Value test, we can reject the null hypothesis that there is no long-term relationship among variables since the P value is less 5%. In contrast, we found that at most two variables are cointegrated since the P-value is greater than 5% in both trace and maximum Eigen-value test. So, all the variables are cointegrated and have long term equilibrium relationship.

Table

4
.
6
.
Johansen Cointegration test for the series of Sierra Leone

Unrestricted Cointegration Rank Test (Trace)
Hypothesized		Trace	0.05
No. of CE(s)	Eigenvalue	Statistic	Critical Value	Prob.**
None *	0.304061	139.6215	69.81889	0.0000
At most 1 *	0.282779	87.05998	47.85613	0.0000
At most 2 *	0.194064	38.86614	29.79707	0.0035
At most 3	0.050869	7.582289	15.49471	0.5111
At most 4	8.31E-05	0.012046	3.841466	0.9124
Unrestricted Cointegration Rank Test (Maximum Eigenvalue)
Hypothesized		Max-Eigen	0.05
No. of CE(s)	Eigenvalue	Statistic	Critical Value	Prob.**
None *	0.304061	52.56149	33.87687	0.0001
At most 1 *	0.282779	48.19384	27.58434	0.0000
At most 2 *	0.194064	31.28385	21.13162	0.0013
At most 3	0.050869	7.570243	14.26460	0.4241
At most 4	8.31E-05	0.012046	3.841466	0.9124

4.4 Vector Error Correction Model (VECM)

Since the variables are integrated at order I (1) and all the series are cointegrated; a Vector Error Correction model is used to look at the short run and short-run relationship between the variables.

4.4.1 VECM (Vector Error Correction Model) for Rwanda

VECM equation composes of two parts: the first part deals with the long run causality while the second part is about the short run causality and the C(1) is the error correction term, also it is known as the speed of adjustment towards equilibrium and it is the coefficient of the cointegrating model.

The coefficient of the cointegrating model C(1) is negative and statistically significant because the p-value is less than 5 percent (5%) and this means that there is a long-run causality running from the gross domestic product, domestic investment, foreign aid and military expenditure to foreign direct investment. According to the short run relationship: the table 4.6 shows that the coefficients of gross product, direct investment, and foreign aid have no significant positive effect on foreign direct investment, and we can say that there is no short-run causality running from those four variables to foreign direct investment. They have no significant effect because their p values are greater than 5% which is the critical value for rejecting the null hypothesis.

Table

4
.
7
.
Vector Error Correction Model for Rwanda

	Coefficient	Std. Error	t-Statistic	Prob.
C(1)	-0.384144	0.049184	-7.810405	0.0000
C(2)	0.457512	0.090749	5.041538	0.0000
C(3)	0.246073	0.100687	2.443926	0.0158
C(4)	-0.010193	0.018697	-0.545147	0.5866
C(5)	-0.014873	0.018404	-0.808129	0.4205
C(6)	0.005841	0.062481	0.093480	0.9257
C(7)	-0.048122	0.062102	-0.774881	0.4398
C(8)	-0.002667	0.040403	-0.066012	0.9475
C(9)	-0.029503	0.040253	-0.732952	0.4649
C(10)	-138416.2	637196.4	-0.217227	0.8284
C(11)	308027.1	646633.4	0.476355	0.6346
C(12)	2787549.	1432337.	1.946154	0.0537
R-squared	0.418396	Mean dependent var		1896711.
Adjusted R-squared	0.370293	S.D. dependent var		17722059
S.E. of regression	14063171	Akaike info criterion		35.83515
Sum squared resid	2.63E+16	Schwarz criterion		36.08150
Log-likelihood	-2586.048	Hannan-Quinn criteria.		35.93525
F-statistic	8.697997	Durbin-Watson stat		2.098926
Prob(F-statistic)	0.000000

4.4.2 VECM (Vector error correction model) Sierra Leone

There is a long-run causality running gross domestic product, direct investment, foreign aid and military expenditure to foreign direct investment since the coefficient of the cointegrating model is negative and significant.

For the short run relationship: there is no short-run causality running from the gross domestic product, direct investment, foreign aid and military expenditure to foreign direct investment since their coefficient is statistically insignificant.

Table

4
.
8
.
Vector Error Correction Model for Sierra Leone

	Coefficient	Std. Error	t-Statistic	Prob.
C(1)	-0.296723	0.050610	-5.862981	0.0000
C(2)	0.505424	0.090195	5.603658	0.0000
C(3)	0.247371	0.100673	2.457185	0.0153
C(4)	-0.036475	0.050785	-0.718212	0.4739
C(5)	0.020524	0.050941	0.402889	0.6877
C(6)	-0.006394	0.122790	-0.052071	0.9586
C(7)	-0.092787	0.123376	-0.752062	0.4533
C(8)	0.160883	0.122982	1.308188	0.1931
C(9)	0.121448	0.123774	0.981207	0.3283
C(10)	-1630149.	2053195.	-0.793957	0.4286
C(11)	-348613.3	2037121.	-0.171130	0.8644
C(12)	-2366456.	3214218.	-0.736246	0.4629
R-squared	0.533162	Mean dependent var		-4910354.
Adjusted R-squared	0.494551	S.D. dependent var		52555108
S.E. of regression	37364018	Akaike info criterion		37.78945
Sum squared resid	1.86E+17	Schwarz criterion		38.03580
Log-likelihood	-2727.735	Hannan-Quinn criteria.		37.88955
F-statistic	13.80866	Durbin-Watson stat		2.059701
Prob(F-statistic)	0.000000

4.5 Granger Causality Test

Granger Causality test is used to know the direction of the causality because Vector Error Correction model does not show the direction of the effect. Granger Causality test gives the direction of the effect and whether there is a unidirectional or bidirectional effect.

4.5.1 Granger causality test for Rwanda series

According to Granger causality test in Rwanda: Domestic investment Granger causes real GDP at 5% significance level and there is unidirectional causality coming foreign aid to real gross domestic product in Rwanda. Also, there is a unidirectional effect coming from real GDP to foreign aid and foreign direct investment. For explanatory variables, domestic investment Granger causes foreign aid and foreign direct investment.

Table

4
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9
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Granger causality for Rwanda

Null Hypothesis:	Obs	F-Statistic	Prob.
GDP does not Granger Cause FDI	146	20.0762	2.E-08
FDI does not Granger Cause GDP		0.31306	0.7317
DI does not Granger Cause FDI	146	15.8223	6.E-07
FDI does not Granger Cause DI		0.44871	0.6394
AID does not Granger Cause FDI	146	7.22526	0.0010
FDI does not Granger Cause AID		9.63249	0.0001
MS does not Granger Cause FDI	146	2.84445	0.0615
FDI does not Granger Cause MS		3.39188	0.0364
DI does not Granger Cause GDP	146	0.53595	0.5863
GDP does not Granger Cause DI		0.34123	0.7115
AID does not Granger Cause GDP	146	5.63732	0.0044
GDP does not Granger Cause AID		3.67564	0.0278
MS does not Granger Cause GDP	146	2.97104	0.0545
GDP does not Granger Cause MS		4.86665	0.0090
AID does not Granger Cause DI	146	2.60683	0.0773
DI does not Granger Cause AID		3.53604	0.0317
MS does not Granger Cause DI	146	0.26931	0.7643
DI does not Granger Cause MS		4.44062	0.0135
MS does not Granger Cause AID	146	2.91046	0.0577
AID does not Granger Cause MS		4.50950	0.0126

4.5.2 Granger causality test for Sierra Leone series

The table shows that GDP Granger causes foreign direct investment and military expenditure. Domestic investment Granger causes real gross domestic product and military expenditure since their p-values are less than 5% level.

Also, foreign aid granger causes military expenditure and its p-value is less than 5% critical level. On the other variables, all other variables do not Granger Cause the remaining ones since their p-values are greater than 5% level so we cannot reject the null hypothesis.

Table

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10
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Granger causality for the series of Sierra Leone

Null Hypothesis:	Obs	F-Statistic	Prob.
GDP does not Granger Cause FDI	146	3.96824	0.0211
FDI does not Granger Cause GDP		10.9102	4.E-05
DI does not Granger Cause FDI	146	20.6024	1.E-08
FDI does not Granger Cause DI		2.51237	0.0847
AID does not Granger Cause FDI	146	4.87744	0.0089
FDI does not Granger Cause AID		2.45423	0.0896
MS does not Granger Cause FDI	146	0.16324	0.8495
FDI does not Granger Cause MS		0.20625	0.8139
DI does not Granger Cause GDP	146	9.58193	0.0001
GDP does not Granger Cause DI		3.96892	0.0210
AID does not Granger Cause GDP	146	0.36594	0.6942
GDP does not Granger Cause AID		10.7167	5.E-05
MS does not Granger Cause GDP	146	0.23420	0.7915
GDP does not Granger Cause MS		0.48012	0.6197
AID does not Granger Cause DI	146	2.25742	0.1084
DI does not Granger Cause AID		2.10605	0.1255
MS does not Granger Cause DI	146	0.10900	0.8968
DI does not Granger Cause MS		0.14378	0.8662
MS does not Granger Cause AID	146	0.67415	0.5112
AID does not Granger Cause MS		0.46281	0.6305

4.6 Checking Serial Correlation

Serial correlation is detected to examine the relationship between the independent variables and the stated hypothesis that there is no serial correlation between the explanatory variables.

4.7 Serial correlation detection for Rwanda

Serial correlation is checked using the Breusch-Godfrey Serial Correlation LM Test to look if there is a serial correlation between the variables and we cannot reject the null hypothesis that there is no serial correlation between variable.

Table

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11
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Breusch-Godfrey serial correlation LM test for the variables of Rwanda

Breusch-Godfrey Serial Correlation LM Test:
F-statistic	203.3134	Prob. F(2,141)		0.0000
Obs*R-squared	109.8938	Prob. Chi-Square(2)		0.0000

4.7.1 Serial correlation detection for Sierra Leone

Serial correlation is also checked by using Breusch-Godfrey Serial Correlation LM Test to look if there is a serial correlation between the variables and the table shows that the null hypothesis cannot be rejected which means there is no serial correlation between the variables.

Table

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12
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Breusch-Godfrey serial correlation LM test for the variables of Rwanda

Breusch-Godfrey Serial Correlation LM Test:
F-statistic	236.5644	Prob. F(2,141)		0.0000
Obs*R-squared	114.0202	Prob. Chi-Square(2)		0.0000

4.8 Checking Heteroskedasticity

4.8.1 Checking heteroskedasticity for Rwanda

Heteroskedasticity (which means different variance) is checked using Heteroskedasticity Test: Breusch-Pagan-Godfrey. The null hypothesis is that there is no heteroscedasticity and the alternative hypothesis is that at least one variable has heteroskedasticity problem. The table shows that the null hypothesis cannot be rejected since the probability value is greater than the 5% level. So the Vector Error Correction Model used in this study has no heteroskedasticity problem.

Table

4
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13
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Heteroskedasticity test: Breusch-Pagan-Godfrey for Rwanda

Heteroskedasticity Test: Breusch-Pagan-Godfrey
F-statistic	27.90181	Prob. F(5,142)		0.0000
Obs*R-squared	73.34521	Prob. Chi-Square(5)		0.0000
Scaled explained SS	152.1067	Prob. Chi-Square(5)		0.0000

4.8.2 Checking heteroskedasticity for Sierra Leone

Table

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14
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Heteroskedasticity test: Breusch-Pagan-Godfrey for Sierra Leone

Heteroskedasticity Test: Breusch-Pagan-Godfrey
F-statistic	19.17196	Prob. F(5,142)		0.0000
Obs*R-squared	59.64544	Prob. Chi-Square(5)		0.0000
Scaled explained SS	163.3518	Prob. Chi-Square(5)		0.0000

Also, for the time series of Sierra Leone, heteroskedasticity is detected using Heteroskedasticity Test: Breusch-Pagan-Godfrey. The null hypothesis cannot be rejected since the probability value of the chi-square is greater than 5% level. So, the VECM model used in this study has the same variance over time and there is no heteroscedasticity problem.

4.9 Cusum Test

The stability of the model is checked using the Cusum test and as the figure shows the model is stable since the blue line which represents the dependent variable is between the two red-lines.

Figure

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11
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Checking the stability of the model using the Cusum test (Rwanda)

Figure

4
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12
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Checking the stability of the model using the Cusum test (Sierra Leone)

4.10 Impulse Response

Impulse Response is used to know the change in the dependent variables when one standard shock is given to one of the explanatory variables.

4.10.1 The results of the impulse response for the series of Rwanda

Figure

4
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13. Impulse response of FDI to changes in the gross domestic product in Rwanda

The response of real FDI to shock in Gross Domestic Product (GDP) is positive at first and falls down to the sixth year but it starts to rise gradually till it becomes zero and after that, the effect of the foreign direct investment on real GDP in Rwanda increases significantly

Figure

4
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14
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The impulse response of FDI to changes in domestic investment in Rwanda

If we look the response of foreign direct investment to direct investment in Rwanda, where there is a shock is given, the effect of direct investment to real FDI extends to the future up to 10 years. At first, real GDP was low but rises and at the tenth year reaches the maximum level.

Figure

4
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15. The impulse response of FDI to one standard shock in foreign aid in Rwanda

The impulse response of real FDI to foreign aid: figure 4.9 shows the response of foreign direct investment product to change in foreign aid when one standard deviation shock is given. Foreign aid is negative but at the sixth year, the effect of foreign aid on foreign direct investment increases while it reaches its maximum level at the seventh year then starts to fall for the following years indicating a negative effect.

Figure

4
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16
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The impulse response of FDI to changes in military expenditures in Rwanda

If we look the response of foreign direct investment to military expenditure in Rwanda, where there is a shock is given, the effect of military expenditure to real FDI extends to the future up to 10 years. At first military expenditure was high but falls and at the tenth year reaches the minimum level.

4.10.2 The results of the impulse response for the series of Sierra Leone

Figure

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17
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The impulse response of Foreign Direct Investment to changes in the Gross domestic product in Sierra Leone

If we look the response of foreign direct investment to gross domestic product in Sierra Leone, where there is a shock is given, the effect of gross domestic product to real FDI extends to the future up to 10 years. At first real GDP was negative and continue to be negative low at the tenth year reaches the maximum level.

Figure

4
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18
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The impulse response of Foreign Direct Investment to change in Direct Investment in Sierra Leone

The response of real Foreign direct Investment to shock in foreign direct investment (FDI) is negative and falls up to the fifth year but it starts to rise gradually till it becomes zero and after that, the effect of the foreign direct investment on real direct Investment in Sierra Leone increases significantly.

Figure

4
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19
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The impulse response of Foreign Direct Investment to one standard shock in Foreign Aid in Sierra Leone

The impulse response of real foreign direct Investment to foreign aid: figure 4.13 shows the response of real gross domestic product to change in foreign aid when one standard deviation shock is given. Foreign aid affects real Foreign direct investment in the future and initially, the response of foreign direct investment to foreign aid is positive but falls until zero at the ninth year the effect of foreign aid on foreign direct investment decreases until it reaches it maximum then starts to fall for the following years indicating a negative effect.

Figure

4
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20
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The impulse response of foreign direct investment to changes in Military expenditures in Sierra Leone

In Sierra Leone, when we look at the response of foreign direct investment to military expenditure, after one standard deviation shock is given to military expenditure, military expenditure is affecting foreign direct investment in the future starting from zero up to 10 years period. The reaction in foreign direct investment to the change in military expenditure is from zero at the beginning and continues below zero levels indicating negative effect throughout the time period.

5. Overall Summary of the Empirical Results, Policy, and Conclusion

5.1 Overall Summary of the Empirical Results

The stationarity of the variables are checked for Rwanda using Augmented Dickey-Fuller test and all the series became stationary after taking the first difference which means that variables are integrated at order one or I (Uysal et al.), similarly the stationarity of the series is tested for Sierra Leone and all the variables became stationary after taking their first differences I (Uysal et al.). Also, the cointegration of the variables is checked using the Johansen cointegration test for the series of Rwanda and Sierra Leone to look at the long-term relationship between the variables. It is found that at most four variables are cointegrated since the null-hypothesis cannot be rejected, and as expected in the long-run gross domestic product, domestic investment and foreign aid have positive effects on foreign direct investment and are statistically significant at 5% while military expenditure has negative effect on foreign direct investment and statistically insignificant at 5% for Rwanda and it is was found at most two variables are cointegrated and there are long-run for gross domestic product, domestic investment, foreign aid and military expenditure on foreign direct investment and there are positive effects of foreign aid on foreign direct investment and statistically insignificant at 5% while there are negative effects of gross domestic products, domestic investment and military expenditure on foreign direct investment and they are all insignificant at 5|% for Sierra Leone. This result is inconsistent across specification.

Vector Error Correction Model was used to examine the long run and short-run relationship between the variables since the series are stationary at I (Uysal et al.) and they are all cointegrated. According to the results of the VECM model, in Rwanda, it is found that there is a long term relationship from gross domestic products, domestic investment, foreign aid and military expenditure to foreign direct investment, but there is no short-run relationship coming from gross domestic products, domestic investment, foreign aid and military expenditure to foreign direct investment since their coefficients were statistically insignificant , that is their p values were greater than 5% level for Rwanda. The statistically and positive effects of foreign aid on foreign direct investment indicates a significant effect of foreign aid on post-conflict countries though Bhavan et al. (2011), have also found physical capital aid of having a crowding-in effect on foreign direct investment in the case of South Asian economies, this thesis look at foreign aid in general as a whole. The negative effect of military expenditure on foreign direct investment result as the end of the war since 1994 the government of Rwanda took the policy of reducing military expenditure and lowering the unemployment level as Collier (2006) indicates that hia gh military expenditure is related to low social services and underinvestment in public infrastructure and he suggests reduction in military expenditure since the resources released by decreasing military spending can be used to increase growth and in turn growth will reduce the risk of internal conflict, and the economic stability the attracts foreign direct investments. The positive result of gross domestic product on foreign direct investment confirmed with the an earlier studies (Noorbakhsh et al. 2001), infrastructure (Wheeler and Mody 1992), a sound climate for international investors such as political stability (Schneider and Frey 1985), trade openness (Albuquerque et al. 2005; Gastanaga et al. 1998), comparative costs such as labor cost (Lucas 1993), taxes and tariffs (Gastanaga et al. 1998; Wei 2000), and access to natural resources (Agosin and Machado 2007).The positive result of gross domestic products on foreign direct investment occurred as Rwanda maintained political stability and developed policies for capital accumulation and successfully created a business-friendly environment. The positive relationship between domestic investment and foreign direct investment is in line with Ndikumana and Verick (2008, p.1) investigate whether domestic investment promotes FDI and is in turn affected by FDI. Their study covers 38 African countries from 1970 to 2005, and they separate private domestic investment and public domestic investment, their results indicate that the relationship between FDI and domestic investment run both ways. But the positive impact of domestic investment on FDI, especially in the case of private investment, is stronger and more robust than the reverse relation. The positive relationship of domestic investment on foreign direct investment results as a result of robust infrastructure comply with the booming tourist industry in Rwanda.

In Sierra Leone, there is a long-term relationship between foreign direct investment and the explanatory variables namely gross domestic products, domestic investment, foreign aid, and military expenditure. Also, there is no short-run relationship coming from gross domestic products, domestic investment, foreign aid and military expenditure to foreign direct investment. Though the results show statistically insignificant but positive effects of foreign aid on foreign direct investment emphasize the importance of foreign aid on post-conflict countries. The negative effects of military expenditure on foreign direct investment show an amount of stability as it takes time for military expenditure to affect foreign direct investment, thus a country with higher military expenditure faces higher armed conflicts than a country with lower armed conflict. The negative effect of gross domestic products on foreign direct investment on a country with large access of natural resources is not always possible, in a country with limited human capital and low growth economy with a cheap underemployed abundant supply of labor as foreign investors may always exploit such opportunities for profit. The negative relationship also occurred as a result of physical capital and technology problems, as well as quality institutions and political-economic instability. The negative relationship of the negative effect of the domestic investment on foreign direct investment is not as surprising as Sierra Leone cannot afford sustainable electricity complies with other rehabilitation projects on water and transportation. There is bi-directional Granger causality relationship from gross domestic product to foreign direct investment, there is also a uni-directional causality relationship from domestic investment to foreign direct investment, while also foreign aid granger causes foreign direct investment. There is also two-way causality relationship for the explanatory variables domestic investment Granger cause foreign direct investment vice versa, while gross domestic product granger causes foreign aid for Sierra Leone. Furthermore, there is unidirectional Granger causality relationship of gross domestic products to foreign direct investment, while also one- way Granger causality between domestic investment and foreign direct investment, and there is bi-directional granger relationship of foreign aid to foreign direct investment vice versa, while also exists uni-directional relationship coming from foreign direct investment to military expenditure and for the explanatory variables a bi-directional granger relationship between foreign aid and gross domestic product vice versa, and one-way Granger causality relationship for the following gross domestic product granger military expenditure, domestic investment Granger cause foreign aid, domestic investment Granger cause military expenditure and finally foreign aid granger cause military expenditure.

5.2 Policy and Recommendation

Policies to reduce foreign aid dependency and increase internal revenue are needed to achieve sustainable recovery and development. The economies of Rwanda and Sierra Leone are highly vulnerable to changes in foreign aid since most of the government expenditures are financed from the development assistance of donor. The governments must try to find internal financial sources that contribute to the economic growth because foreign aid flows are not reliable in the long run and also post-conflict countries do not get the aid on a timely basis since international community requires certain criteria to be fulfilled to get financial support such as loans and grants. One of the ways to increase internal revenue is reforming the tax system. For instance, the government can increase the revenue from taxes by increasing the tax rate, expanding the tax base and levying new taxes.

To reduce the risk of conflict renewal the study recommends policymakers to reduce military expenditure in Rwanda and Sierra Leone and increase investments in human capital especially in education and skills training programs since investment in human capital will increase the labor supply and enhance the productivity. Instead of high military expenditure, investments in both physical and human capitals are necessary for increasing exports particularly tea and coffee exports because high military expenditures cause underinvestment in productive sectors and low domestic product. Also, in order to reduce the risk of new conflict, the study recommends creating job opportunities for youth because a high percentage of the population is youth under 20 years old and youth unemployment is very high in both countries. The unemployed youth can be recruited for violence and new conflict.

The governments should develop policies to increase domestic investment because it is the only way to create sustainable economic growth and development. Public investments like building new roads, power generators, dam constructions etc. are necessary for encouraging domestic investment and stimulating economic growth. The business-friendly environment must be created for private sector development and laws and regulations protecting the property rights must be enacted. Saving culture must be promoted because the saving rate is very low in both countries since the majority of the people generate their incomes from subsistence agriculture. Domestic savings contribute more to the domestic investment if the people deposit their money in bank accounts instead of traditional saving methods. Depositing in banking accounts provide credit to private business and increase domestic investment. Also, the government (using its own macroeconomic policies) must protect local business from foreign companies with monopoly power and also give subsidies to the farmers. Also, the governments in coordination with donors must develop policies to offer free education to the people because illiteracy is part of the problem since uneducated people prefer war over peace and peace and development come when many people get the opportunity for education. Rwanda. So, the governments of Rwanda and Sierra Leone must set policies that encourage foreign investors such as:

Reducing risks related to foreign direct investment such as security risk in Sierra Leone.

Rwandan government in coordination with donors set its policy priorities for post-conflict recovery and foreign aid represented the engine for economic growth and development in Rwanda. Foreign aid mainly was in the form of development assistance. The government urged huge investment in important sectors such as infrastructure rehabilitation, institutional building, and budget support. After a decade, high growth rate, improved gross domestic product per capita and fall in the unemployment rate were the results of large foreign aid offered to the fragile government of Rwanda. In another hand, Sierra Leone was offered a large amount of foreign aid that relatively contributed to the economic growth and it facilitated the improvement in the livelihood of many people but compared to Rwanda aid didn’t increase the growth rate significantly. The reoccurrence of another conflict should be priorities in policy implementation of both Rwanda and Sierra Leone, as it negatively affects foreign direct investment, thus the need to address the root cause of the conflict should be address and efficient legal framework should be functional in order to attract a foreign investment. Policies on how post-conflict government can reduce the risk of new conflict as there is are many types of research about the effect of military spending on the economic recovery in post-conflict situations. Many scholars advocate high military expenditure after the conflict period because of the high possibility of a new conflict. They suggest that the government should increase the amount of the budget for the military in order to disarm the rebel groups and restore law and order all over the country. In contrast, many researchers found that military spending negatively affects the economic growth in post-conflict situations because the government diverts a large amount of money to the military instead of using these public resources for promoting growth and recovery. The study found that military expenditure has a significant long-run relationship with the foreign direct investment in Rwanda and from the impulse response, foreign direct investment negatively responds to changes in military expenditure. Since 1994 the government of Rwanda took the policy of reducing military expenditure and lowering the unemployment level.

Collier (2006) indicates that high military expenditure is related to low social services and underinvestment in public infrastructure and he suggests a reduction in military expenditure since the resources released by decreasing military spending can be used to increase growth and in turn growth will reduce the risk of internal conflict. Also, African-Bank (2008) supports the negative relationship between military expenditure and recovery since their research work revealed that there is a trade-off between policies that promote growth and those that promote peace.

Domestic investment positively affects foreign direct investment and it significantly contributes to attracting foreign direct investment in Rwanda. After the civil war, the government has done macroeconomic reforms including improving public infrastructure and developing the private sector. The construction of new roads, improvement in electricity and water and better telecommunication services promoted the business activities across the country. Also, the government created a business-friendly environment through its regulations and tax system.

In the beginning, in Rwanda, foreign direct investment had little effect on economic growth because the government could not attract more foreign direct investment due to the political instability and uncertainty of the volatile environment. The government has announced that the country is open for investment by reforming its business laws and giving incentives to the foreign investors such as low taxes and low business registration fees and after these reforms, more foreign investors started to invest in the agriculture and the industry sector and then more foreign direct investment came to country increasing export level. In Sierra Leone, the foreign direct investment flow is low compared to Rwanda because of many factors including corruption, poor institutions and governance, and ineffective economic policies.

5.3 Conclusion

This study tried to investigate the economic policies for post-conflict recovery by comparing the relationship of foreign aid on foreign direct investment and the effect of policy reforms made by the governments of Rwanda and Sierra Leone to end the conflict and enhance the economic growth and development. A sample of 37-time series observations from 1980 up to 2016 was taken to examine the performance of the economy before and after the genocide, and the civil war which happened in the two countries. The primary objectives of the research were the relationship of foreign aid on foreign direct investment and the effect of military expenditure in reducing the risk of new conflict and promoting the economic growth and examine the contribution of internal and external financial flows to the economic recovery of the two countries.

The result from the Vector Error Correction Model indicates that gross domestic products, domestic investment, foreign aid, and military expenditure have long run significant effect on foreign direct investment of Sierra Leone and Rwanda. There is no short run on all the explanatory variables on foreign direct investment for both Rwanda and Sierra Leone. Also, Granger causality test is used to know the direction of the effect (whether the effect is unidirectional or bidirectional one) since the VECM model does not show the direction of the effect of the variables. For Sierra Leone, it is there is bidirectional Granger of gross domestic product and FDI and domestic investment Granger cause FDI, and AID Granger cause FDI. There is also bi-directional Granger between the explanatory variable’s domestic investment and gross domestic product. Also, there is a unidirectional effect coming from gross domestic product to AID. On the other hand, for Rwanda gross domestic product Granger causes FDI and there is unidirectional causality coming domestic investment foreign direct investment in Rwanda. Also, there is a unidirectional effect coming from foreign direct investment to military expenditure, and it is bi-directional from foreign aid to foreign direct investment and from foreign direct investment to foreign aid. For explanatory variables, domestic investment Granger causes foreign aid and military expenditure.

5.4 Recommendations for Further Study

The study suggests the following topics to be investigated in detail:

Signals of foreign direct investment in post-conflict countries.

How inclusive political and economic institutions can be established in post-conflict situations?

How a domestic product can be increased in post-conflict countries?

Good governance and economic recovery in post-conflict country

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African Development Bank (2001). Economic Recovery for Post-conflict Recovery www.econstor.eu.

CV

Profile

Ahmed an already professional retailer in the banking sector who is keen to apply those experiences in another market with additional qualification in economics, with very good knowledge in both quantitative and qualitative Research, with very good knowledge on Microsoft packages, Stata and Eviews. Having the ability to work accurately, with excellent Communication skills, and a very good team player.

Ahmed Kemoh

Zincirlikuyu Mahallesi, 26200 Tepebaşı/Eskişehir Province, Turkey

[email protected]/
[email protected]

+905396765365

Education

Master of Economics-major, Anadolu University- Turkey

September 2017- To Date

Thesis Topic: Economic Policies For Post-Conflict Recovery: Comparative Study Between Rwanda And Sierra Leone

Research Related Course:

Research in Area of Specialization

Ethics of Science and Research Techniques

Term Paper Presentations

A Vector Autoregression (VAR) Analysis of the Monetary Transmission Mechanism in Sierra Leone (Econometric Technique)

State of the Business Cycle (Macro Economics)

Bachelor Honours in Applied Accounting-major, Institute of Public Administration and Management University of Sierra Leone

Marketing Related Course at Undergraduate:

Marketing and Communications

Global Advertising Industry

Global Sport Industry

Global Media Industry

Dissertation Topic: Evaluating the Effectiveness of Financial Performance of Financial Institutions – (Sierra Leone Commercial Bank and Standard Chartered Bank & DHL and Sierra Leone Postal Services).

September 2008-December 2012

West Africa Senior Secondary Certificate Examination, Albert Academy-Sierra Leone

2002-2008

Work experience

Executive Training: Guaranty Trust Bank Sierra Leone Limited, February 2013 –September 2015, Sierra Leone

Ensuring the smooth running of basic banking transactions.

Marketing new financial products or services.

Handling customer queries face to face, over the phone or via correspondence.

developing a network of local business contacts

managing budgets and meeting targets

Develop a portfolio of retail clients with a strong emphasis on a high-quality portfolio and effective risk management

Finance/Logistic Officer:
Sierra Leone Social- Aid Volunteer June 2012-January 2013, Sierra Leone

Ensure income and expenditure forecast.

Ensure effective cash management, disbursement, and office safe, control of checkbooks and petty cash and relevant transaction with outsiders.

Ensure monthly payroll processing and staff commitment.

Ensure effective and efficient documentation and reporting of vouchers, cash and bank reconciliation, income and expenditure summary.

Ensures financial document are in proper filing systems.

Language skills

Speaks six Languages

Fluent in English, Turkish and 4 four African Languages

Traveling

Great experiences and high familiarity with different religions and culture of Europe, Africa, and Asia.