The nexus between institution and stochastic growth in selected Sub-Saharan African countries. Evidence from dynamic panel data analysis

TABLE OF CONTENTS

ACKNOWLEDGEMENTS

LIST OF TABLES

LIST OF ANNEX

LIST OF ABBREVIATIONS AND ACRONYMS

ABSTRACT

CHAPTER ONE: INTRODUCTION
1.1. Background
1.2. Problem Statement
1.3. Objectives
1.4. Research Questions
1.5. Hypothesis
1.6. Justification
1.7. Significance
1.8. Scope and Limitation of the study
1.9. Organization of the paper

CHAPTER TWO: LITERATURE REVIEW
2.1. Theoretical Literature
2.1.1. Definition of Institution
2.1.2. Institutional Theory
2.1.3. Stochastic Growth Theory
2.1.3.1. The Brock-Mir man Stochastic Growth Model
2.1.3.2. Real Business Cycle Model
2.1.4. The Nexus between Institution and Stochastic Growth
2.2. Empirical Literature
2.3. Conceptual Frame work

CHAPTER THREE: METHODOLOGY
3.1. Model Specification
3.2. Nature and Data source
3.2.1. Data Source
3.2.2. Variable Definition
3.3. Estimation Techniques and Method of Analysis
3.3.1. Method of Analysis
3.3.2. Estimation Techniques

CHAPTER FOUR: DISCUSSION AND ANALYSIS
4.1. Data description and Summary statistics
4.2. Econometric Results
4.2.1. Discussion, Interpretation and Analysis
4.2.2. Post Estimation Test
4.2.2.1. Autocorrelation
4.2.2.2. Over identifying Restrictions
4.2.2.3. Heteroscedasticity

CHAPTER FIVE: CONCLUSION AND POLICY IMPLICTIONS

REFERENCE

ANNEX

ACKNOWLEDGEMENTS

First of all I would like to express my limitless gratitude to Almighty of God together with his Virgin mother St. Marry for making possible the once ‘impossible’ dream I had in mind some years ago. When all the possible gates seem closed, this academic achievement in such a short time was not more than a dream if not an illusion at all. Thanks to God and his mother for giving me the endurance, determination and guidance throughout the valleys and mountains of life. With your light, I saw my way!

Next my special thanks go to my instructor and thesis advisor, Dr. Zerayehu Sime for his encouragement, wisdom and generosity in commenting and suggesting throughout this thesis work. He has given me an extensive, constructive and very helpful comment. Further, he has shaped my way of thinking about many issues and hereafter, he will remain to be my inspiration for further research work and certainly in my future career.

I am also very much indebted to my colleagues and friends, who helped me a lot in doing this thesis work. I especially express gratitude to Legesse Debele, Zekarias Minota, Kahsay Berhane and Derejie Mosie for their encouragement and thoughtful suggestions.

Last, but by no means least, my heartfelt gratitude goes to my families who have been on my right hand side since the very beginning of such a long academic journey with a multitude of support for which I lack words to exhaustively list down.

LIST OF TABLES

Table 1: Definition and expected sign of variables used in the analysis

Table 2: Summary statistics for the variables

Table 3: Dynamic panel-data estimation: Arellano-Bond – Difference GMM

Table 4: Dynamic panel-data estimation: Arellano-Bover – System GMM

LIST OF FIGURES

Figure 1: Relationship between institutions and stochastic economic growth

LIST OF ANNEX

Annex: A: Lists of countries included in the study

Annex: B: RGDP per capita and GDP growth rate of SSA, 1996-2014

Annex: C: Regression C1: One-step difference GMM

Regression C2: One-step system GMM

Regression D: One-step difference GMM autocorrelation test

Regression E: One-step system GMM autocorrelation test

LIST OF ABBREVIATIONS AND ACRONYMS

illustration not visible in this excerpt

ABSTRACT

Sub Saharan Africa economic growth shows a stochastic growth performance that is interrelated with faulty and fragile governance problems associated in the region. In view of that, this thesis examines the contribution of formal institution explained by aggregated index for the six governance clusters measured by World Governance Indicator and individual level of these indicators on the stochastic growth behavior of selected SSA countries using data from forty two selected SSA countries over a period of 1996 to 2014. In order to examine the impact of institution and level of good governance, the paper employed Arellano-Bond (1991) and Arellano-Bover (1995) dynamic panel generalized method of moments (GMM) technique of estimation.The estimated result suggested that variables such as foreign aid, public investment, consumption, imported capital good, inflation, control of corruption, rule of law, voice and accountability, political stability, government effectiveness, regulatory quality and the combined effect of governance measures (institution) are significant and positively contribute to stochastic growth behavior of the region across each models. On the other hand, outward trade policy negatively affects region growth performance. In addition, the study surprisingly indicates that though foreign direct investment has no significant contribution in the study period its impact is negative in SSA. A major policy implication arising from the results is that the advancement of institution and level of good governance are fundamental to the realization of sustained economic growth in SSA.

Key Words: - Stochastic growth, Institution, Good governance, GMM, Sub Sahara Africa

CHAPTER ONE: INTRODUCTION

1.1. Background

Sub-Saharan Africa^[1] comprises 50 member countries^[2] in the continent of Africa (UNCTAD, 2014). The region^[3] consists all of African countries that are totally or partially located south of the Sahara desert. It is in abysmal distinction with North Africa who is considered as part of the Middle East. On 2014, the total population of the region was estimated about 974 million with a growth rate of 2.3 percent (WB, 2014). The region has endowed with a wealth of resource, political, social, economic, cultural and structural heterogeneity, and demonstrate the most ethnic and linguistic assortment region in the world (AU, 2014).

Tough, the region is endowed with a large number of population, wealth natural resource, and enormous aid disbursement, it was extremely underdeveloped and mired in with widespread poverty, growing inequalities and instabilities (Schaefer, 2005). The World Bank (2014) report indicates that the region has had scored the lowest GDP for decades and nearly 50 percent of the populations are surviving on less than US $1 per day. It is also a region where the majorities find life awful as it is challenging to satisfy their basic needs such as shelter, food, clothing, and education. Evidence confirms that more than 200 million SSA has no access to proper sanitation and health care service. Similarly, over 47 percent of the population of the region is without access to safe water and non-existent power supply (Marke, 2007). For these different factors are upraised. Economic and political shocks, war, deficiency of hard currency, trade unevenness, debt overhang, religious tension and tribe conflicts, current account deficit, unemployment and low institutional development for the long period of time are some of the common constraints that retards economic growth of the region (Herzer & Grimm, 2011).

Starting from 1990s SSA countries have been undertaking many conflicts and war that damages severely their growth performance (Kidane M, 2011). The costs of war and conflict is mainly high as a result of war being internally struggled and owing to their amalgamation into global economic affairs (Antony, 2012; IPCC, 2007). It diverted potential resources from recurrent expenditure and investment towards the conflict and war. It is regularly supported by inflation since the range for disbursing for a conflict increased wartime employment and productions are trivial (Antony, 2012). Moreover, it interrupted infrastructural development, decreases competition and creates a monopoly rents with adverse consequences for clients (Hailu Abatena, 2009).

Besides, the region has encountered with governance and institutional problems resulted from colonial legacy and domestic governance structure that severely affect their economic growth (Chiriyankandath, 2007). Actually, colonialism contributed to overall socio-economic and political structure of the region through introduction of an infrastructures like roads and railways, introduction of cash crops and commercialization of land (Chiriyankandath, 2007). Yet, it also negatively affected the growth performance of the region with a number of reasons. First, the infrastructure that was delivered by colonialist was used to assist the exploitation of the resources of the colonies rather than promote the economic development of the region (Toyin, 2005). Second, economic growth that was resulted from natural resource exploitation led strong economic disparity within the region (Shillington, 2005). Third, it puts region into an exporter of raw material and an importer of manufactured goods from the metropolitan countries by destroying pre-colonial industries and crafts, disregard industrial development and neglecting the processing of locally produced raw materials (Gifford & Louis, 1982; Shillington, 2005). Fourth, the colonizers were limiting the flow of trade link between and within the region, as well as other part of world through creating political boundary barriers and reorienting the pattern of trade structure towards metropolitan nations (Chiriyankandath, 2007; Gifford & Louis, 1982). Finally, colonialism negatively affected the traditional way of life of the region’s society without giving a real substitute and setting them under western institution's arrangements that are persuaded by a sense of dependency and inferiority among the region (Austin, 2010).

Moreover, the underprivileged economy of the region has been also suffered from the internal governance problems like corruption, absence of rule of law, election related violence and the like (Ikejiaku, 2009). The leaders and government officials are transferring money in billions to their overseas bank accounts each year, which is used to invest in health and education. Furthermore, most leaders have no willingness and autonomous power to correct government failure, thereby building harmony and sustainable development is far from realization in the region (Ikejiaku, 2009). Thus, in the past twenty years, the sum of above factors remains the region to face a fluctuated economic growth and had led most vulnerable, politically unstable, source of terrorism, fragile and socioeconomic disadvantaged area in the continent. Therefore, for the sake of a healthy economy, it needs to improve the performance of these factors by examining their contribution on the stochastic economic growth behavior of the region clearly.

Accordingly, one of such examination needs in area of institution and level of good governance as the study indicated that sustainable growth is extremely moves back and forth, unless it maintained by the right institution (Collier, 2007). Moreover, the quality of institution and level of good governance matters for the stochastic economic growth performance of SSA (Rodrik, 2004). However, which institutions matter? As well as examining its contribution to stochastic economic growth also neglected by a number of economists due to its subjectivity and complexity (Chang & Ha-Joon, 2006).

Therefore, empirically this study examined the contribution of institution and level of good governance for stochastic economic growth behavior of Sub Sahara African countries. The study used an econometric model of dynamic panel data regression system- generalized method of momentum estimation technique as a method of data analysis. To address the above issues, unbalanced panel data set for forty two selected Sub Saharan African countries were used over a period of 1996 to 2014.

1.2. Problem Statement

Africa is the poorest continent in the world. Yet, African countries south of the Sahara are even poorer and confronted with many persistent problems. First, even though there is slight improvement in recent years, the SSA economic growth rates has been characterized with stochastic growth performance. Second, the stochastic growth behavior of the region is interrelated with faulty and fragile institution and governance problems.

When we review the economic growth structure, it shows stagnated and lowest GDP per-capita income. Since 1950s, it moves back and forth, and deteriorated slightly in 1990’s before returning to only 4.1 percent in 2013 (Dulani, R. Mattes, & C. Logan, 2013). Furthermore, the growth process of member countries has been unable to converge to advanced countries. Specifically, only Cameroon, Ghana, Namibia, Niger, Senegal, Botswana, Lesotho, Mauritius and Seychelles are identified as converging countries and others: Ethiopia, Gambia, Tanzania, Cap Verde, Chad, and Uganda are undertaken in a convergence process (King & Ramlogan-Dobson, 2015 ). In line with this, the world Bank (2015a) report estimated that in 2030, regardless of major exertions in the framework of current growth and transformation policies, over 240 million people, which represents 16 percent of SSA’s population will live on less than USD 1.25 a day in 2005 purchasing power parity and caused by stagnant and stochastic growth performance. Moreover, SSA has been identified as a last place in the world in which famine and starvation still persist and millions of their people are struggling with hunger, anxiety, loss of dignity and any sense of efficiency caused by stochastic growth performance (UNDP, 2009b). Therefore, since such level of stochastic growth is sneering and life threatening no country in the region may consider it bearable.

In fact, in the past hundred’s years the world as a general was facing lack of cohesion and stochastic growth in the same way as SSA’s nowadays. Then, following the industrial revolution, most parts of the world countries specially the western regions were significantly deemed stochastic growth problems (Hazlitt, 1996). But, Sub Sahara Africa is trapped in the same status quo where others have thriven in moving. Sala-i-Martin (2002), argued that such failure is a mystery for development actors, economists and governments of the region. Probably, many factors are arisen for such failure. Among these, studies conducted by Acemoglu (2009), Easterly (2006), Fuje N. Habtamu (2005) and Glaeser et al. (2004) concluded that such failure is strongly related to institutional and governance problems exists in the region. in fact, their conclusion seems correct. Because, unlike bad institution, better institution improves growth performance along with the distribution of income in which both of them have significant effects in curtailing growth fluctuation and poverty reduction (Acemoglu, Johnson, & Robinson, 2001). Similarly, empirical evidence from South Korea and Japan has shown that good governance enhances economic growth and general welfare of the nation through stimulating physical and human capital accumulation, enhancing trade pattern, promotes investment and reduces business confidence problem (Brouseau & Glanchant, 2008). Yet, in contrary to the above fact, SSA countries are symbolized by poor, malfunctioning and weak institutional arrangement such as raising ethnic violence, widespread bureaucratic corruption together with administrative inefficiency, institutional ineptitude, etc., (Fosu, 2013b; Rodrik, 2014).

Actually, each year the region invests a huge amount of fund in institutional development indicators such as human development and health structure to reduce the problem and improves their growth performance (Sachs & Warner, 1997). But, they are remaining with weak progress in these indicators. Indeed, in the past twenty years, some improvements have been achieved in human development through investing in education and health (WB, 2014). But, still it is lower than the global average that significantly affects the rising inequality. For instance, in the 1990 human development index for SSA was 0.30 compared to the global average of 0.60 indicating a difference of 39 percent. This level improves to 0.39 percent in 2014, but still stayed 33 percent lower than the global average of 0.70 (UNDP, 2014c). Besides, Inequality-adjusted Human Development Index (IHDI) for the region shows 43.6 percent loss in values after modifications are made for differences in the distribution of income and institution indicators explained above. Moreover, unlike high human development countries in which inequality is related to income distribution, in SSA, the fundamental cause of variation in IHDI values is substantial differences in access to education and health.

Sub-Sahara Africa growth performance is also suffered from institutional problem measured by countries’ good governance indicators. In view of that, corruption and illegal capital flight are a serious challenge in the region. Empirical evidence confirmed that out of world most corrupted ten countries, six^[4] of them are found in the region and only Botswana, Cape Verde, Seychelles, Rwanda and Mauritius scores above fifty (Chene, 2014; D. Kauffmann, 2005). Moreover, illicit real capital flight drastically high in SSA. For example, illegal capital flight from the region is estimated to about $814 billion dollars from 1970 to 2010, which is significantly exceeding the amount of aid ($659 billion) and foreign direct investment ($306 billion) inflow to the region for the same period (James & Ndikumana, 2012).

Similarly, another measure of government quality is also below average in SSA. Specifically, on average the value of the rule of law indicates (-0.53), regulatory quality (-0.48), government effectiveness (-0.53), political stability (-0.48), voice and accountability (-0.52) from 1996 to 2014 (WB, 2014). On the other hand, not only uncertainty, but also authoritarianism is higher and civil liberties are collateral victims in the regions than anywhere else in the world. For instance in the 2014, without border press freedom, a 2014 report showed that Eretria, Somalia and Ethiopia ranked second, third and fourth world’s biggest prison for journalists, respectively, while Mali, Central Africa, Sudan, Chad, Kenya, Burundi and Djibouti is acknowledged by impotent to hear the voice of those without a voice. In addition, lack of strong institutions and the level of good governance are factors for technology, trade and government spending shocks in the region.

Therefore, the sum of these and other factors set the region under stochastic economic growth and turned it as a world least developed^[5] area. If the problem persists with this phase and cannot solve in a short period, it inherently slows down SSA overall economic, social and political growth structure, impairing citizens' welfare and put the region under the vicious circle of poverty.

Actually, many scholars such as Aixala and Fabro (2008), Basu (2008), Augustin (2008), Easterly (2006), Acemoglu, Johnson, and Robinson (2005), Durham (2004), Assane and Grammy (2003), Aron ( 2000), and Chong and Calderon (2000), had investigated the contribution of institution and good governance on economic growth in context of developing country and Africa as a whole. Specifically, Hakeem and Kamil (2014), Gani ( 2011), Djankov et al. (2010) and Pillay ( 2004 ) were empirically examined on context of SSA. However, the previous study conducted in the region is limited to, the following aspect that provides a room for undertaking this research to fill the gap.

1. The previous study used primary data predominantly taken from the Polity dataset to investigate the contribution of institution and level of good governance on economic growth. However, the governance indicators used by the primary studies have used people’s perceptions of governance in various countries derived from polls, surveys or expert opinions that leads subjective decision and lack objective analysis in addition to leading to a large margin of error (Gani, 2011).
2. Most of the previous studies conducted in SSA lack the indirect effects of institution and level of good governance on economic growth. Nonetheless, governance indicators can affect economic growth indirectly through upsetting technology, trade, consumption and fiscal policy amongst many other factors. This shows a clear scope for inclusion of indirect effects of level of good governance and institution on stochastic economic growth in the region.
3. The past studies used static model (with the exception of Fuje N. Habtamu (2005) who employed dynamic model to investigate role and the possible transmission channels through which governance affects growth using data from 35 SSA countries from 1996 to 2005) and focused on either one or more governance measures to explore their contribution. Thus, they provided a mixed result that inherently affects policy decision in the region.
4. Empirical studies on measures of governance indicator and stochastic economic growth are relatively few in the case of SSA as opposed to studies on other determinants of growth.

1.3. Objectives

The general objective of this research is to examine the relationship of institution and level of good governance with the stochastic economic growth in the selected SSA countries.

The specific objectives are:

1. To explore the performance and practices of institutions and their level of good governance in selected SSA countries.
2. To describe and analyze the effect of institution and level of good governance on stochastic economic growth in selected SSA countries.
3. To explore the transmission channel through which institution and level of good governance cause stochastic economic growth in selected SSA countries.

1.4. Research Question

- What are the performance and practice of institutions and their level of good governance in selected SSA countries?
- What is the relationship of institution and level of good governance with stochastic economic growth in selected SSA countries?
- Do institution and level of good governance affect stochastic economic growth behavior of selected sub-Saharan African countries?
- What are the transmission channel through which institution and level of good governance cause stochastic economic growth in selected SSA countries?

1.5. Hypothesis

Based on problems specified in aforementioned sections and the related literature to the objectives, hypotheses are settled for further analysis. The first hypothesis is that the nexus of institution and level of good governance with the stochastic economic growth positive in SSA countries. Second, the performance of institution and level of good governance is low in SSA. Third, institution and level of good governance plays a significant role in explaining stochastic growth performance in SSA. Fourth, in addition to direct effect, institution and level of good governance indirectly contribute to the stochastic growth of the region by upsetting other macroeconomic variable. It is believed that the real explanation for the problem of unstable economic growth is an inappropriate growth strategy in the region, which is caused by weak institution and the resulting uncertainty and lack of public confidence. Therefore, subsequent lack of sustainable growth over the years elucidates SSA underdevelopment.

1.6. Justification

The main justification of this study is associated with the cruelty of the problem followed by unstable economic growth that harms and put millions people of the SSA countries under absolute poverty. This study has also been expected to give insight to development actors, policy makers and the result will be expected to improve economic growth performance and then the general welfare of society through identifying institutional factors that contribute to stochastic growth performance under study area. The specific justification to conduct the study was as follows:

A. The existence of uncertain economic growth: In the last twenty years, the majority of the SSA countries faced stagnant and uncertain economic growth performance caused by growth barriers like institution (WB, 2014). Due to this reason the majority of resident’s survives under abysmal poverty, lack social cohesion and income inequality. On average, nearly 45 to 85 million people of the SSA countries are under famine and starvation each year (FAO, 2011). Surprisingly, each year people live below poverty line increase drastically. For instance, in 1996 out of the total population of the SSA countries on average nearly 27 percent are under the poverty line while in 2014 the population below the poverty line on average increased to 35 percent. This is mainly due to stochastic economic growth aggravated by poor institution and governance quality of the region.
B. Existence of socio- economic insatiably and political shock: Sustainable growth depends on institutional factors such as rule of law, voice and accountability, property right, government effectiveness, political stability and like. Yet, SSA countries face stochastic and unstable economic growth performance resulted from poor institutional quality indicator which is in turn caused by socioeconomic instability and political shock. They faced nearly 45 internal and 19 to 28 inter- sate conflict and war from a period of 1960 to 2011 (Kidane M, 2011). According to Africa Union 2014 report, out of war and conflict upraised in the region in last twenty years, about 80 percent of them are associated with institution and governance problems. Furthermore, a number of growing, active labor force international migrations and brain drained happened in SSA has been highly related to weak institution performance that in turn directly underwrites to the stochastic economic growth behavior of the region.

1.7. Significance

It has been very long time as the notorious honor of the stochastic economic growth area in the world has been given to Sub Sahara Africa. Amid of several reasons that are most often ascribed to an institution and the level of good governance structure that the region has followed in the past. It was said to be triggering factor for the lack of progress of the region‘s economic growth. The outcome of this study is used to examine the contribution of institution and level of good governance on the stochastic growth performance of selected Sub Saharan African countries from as many angles as possible. The main significance of this study was:-

First, the finding of this study provided inherent clue to government, policy designers, and decision makers on the indigenous relationship between institutions and the level of good governance with stochastic economic growth in the current context of SSA countries. It also provided insight to them on seizing the comprehensive role and potential of good governance indicator to promote sustainable economic development in the region. Moreover, it helped them to understand the progresses regarding achieving the sustainable economic development, to know where and what shall be their focus, and to pass reliable decision in prioritizing policies and strategies of implementation. Second, the study gives some insight into economic science theory of growth by contributing some empirical fact to existing economic growth theory. Finally, the outcome of this research can be used as a springboard for researchers and practitioners to study further on the nexus between the institution and stochastic growth.

1.8. Scope and Limitation of the study

The study is specifically focused on examining the contribution of institution and level of good governance on stochastic economic growth in selected Sub Saharan African countries. It also explored the transmission channel, performance and practices of institutions and level of good governance in the region. Though, the topic also worries other Sub- Saharan African countries, this study is limited to only 42 countries of the region. This is due to the problem of availability of data on the variables used in the study and the time period covered. As data for governance measure is not available for many of the countries under study before the year 1996, this study is limited to the period from 1996 - 2014. Thus, the major limitations of the study among others, was a problem of getting data for a longer period of time and for more countries in the region under consideration

1.9. Organization of the paper

Following introduction part indicated in chapter one, the rest of the paper was organized as follows. Chapter two provided the theoretical and empirical related literature to this study. Chapter three focused on model specification, data sources and methodology. The data analysis part is conducted in chapter four. Finally, chapter five offered conclusions and some policy implications.

CHAPTER TWO: LITERATURE REVIEW

2.1. Theoretical Literature

2.1.1. Definition of Institution

One of the problem with institution school of thought is that, it's somewhat difficult to define the word “institution” because institution refers to many different things that academic literature is sometimes not clear about its definition (Acemoglu et al., 2005).

North (1990), defines institution “Institutions are the rules of the game in a society or, more formally, are the humanly devised constraints that shape human interaction." According to his definition institution captures three important elements that make up the institution. First, they are “humanly devised” meaning institution is a human made factors that are under the control of the human being. It is about the effect of society own choice on their own economic chances. Second, it is placing constraint on individual behavior. This indicates that policy, regulation and laws that punish certain types of behavior while rewarding others will naturally have an effect on behavior. Finally, institutional constraints placed on individual will shape human interaction and affect incentives.

Acemoglu et al. (2005), defined institutions as a combination of three interrelated concepts: Economic institutions-these are factors that influence the structure of economic incentives in society such as incentives of economic actors to invest, make transactions, distribution of resources and etc. It includes the structure of property right, functioning of the market and contractual opportunity available to the society. Political power- it clarifies the relative political power of different groups of society with conflicting interests that governs their capacity to decide the administration of resources and implement policies. Political institutions- these are institution that allocates political power across groups and related to the features of the government and the scheme of the constitution such as power distribution, decision-making and like.

This research paper takes the definition of institutions, following the work of Kauffman, Kraay, and Mastruzzi (2005) that they defined as a governance measure in which one country’s authority is exercised for mutual benefit. According them institution contains six governance clusters. These are: -

1. Government effectiveness: - measured the quality of public services, the quality and degree of independence from political pressures of the civil service, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies.
2. Regulatory quality: - Measured the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector in to development.
3. Rule of law: - Measured the extent to which agents have confidence in and abide by the rules of society, in particular the quality of contract enforcement, the police, and the courts, as well as the likelihood of crime and violence.
4. Control of corruption: - measured the extent to which public power is exercised for private gain, including petty and grand forms of corruption, as well as “capture” of the state by elites and private interests), which shows the respect of citizens and the state for the institutions that govern economic and social interactions among them and the political dimension.
5. Voice and accountability: - Measured the opinions of the extent to which a country's citizens are able to participate in selecting their government and freedom of expression.
6. Political stability and absence of violence: -measured the perceptions of the likelihood that the government will be destabilized or overthrown by unconstitutional or violent means, including domestic violence or terrorism.

2.1.2. Institutional Theory

In real world countries have different economic performance and classified as advanced countries, developing countries and underdeveloped countries. This classification is based on the economic growth of the state. For the differences in the economic performance of world countries, economists provide different justifications. But, most of them emphasized on the quality institution that each country adopted. Contextually, it indicates that economic growth is related with domestic institution i.e.‘’good institution’’ correlated with high economic growth and ‘’bad institution’’ generates low economic performance. Papers like Collier (2006), IMF (2003), Rodrick and Subramanian ( 2003) and Acemoglu et al. (2001) provides economic institutions are the fundamental causes of the divergence of the economy between low income countries and advanced countries. On the other round scholars like Acemoglu et al. (2005) and Glaeser et al. (2004) gives attention for the role of political institutions that leads disparity across a countries.

The importance of institution in theory of economic growth is first explained by the works of D. North in 1981. Based on the kind of institutions; strong and weak institution, he proposed two institutional theories, a ‘’contract theory’’ of the state and a ‘’predatory theory’’ of the state. The former states that the state and its institution has the role to protect property right by setting legal framework that can encourage private investors and hence, it facilitate the economy. While the second theory states that bad institutions like corruption (rent seeking activity) and political instability affects negatively the economic performance of the state (North, 1981).

Following the work of North, and lack of empirical evidence for convergence of the neoclassical growth model developed by Solow (1956) that predicted economies move toward their steady state growth path, Romer (1986) and Lucas (1988 ) introduced new growth theory called the new endogenous growth theory. Unlike Solow, their growth theory a growth is conditioned with an institution or it states that, ‘’knowledge spillover’’ brings economic growth in less advanced countries. This implies that countries with quality institution can catch up new technology and can narrow the economic gaps between low income countries and advanced countries. This theory also indicates that technology is exogenous; hence, technological change has been significantly depended on the existing institutions through their effect on incentives and transaction costs (D. C. North & Thomas, 1973).

Rodrik institutional theory discussed that, even though it is challenging to round about that which institutions matter, democracy is the most effective way to improve better institutions. Consistent with his theory, an enormous literature is there to find a correlation between democracy and autocracy in determining growth but ambiguity between the variables is still there. Autocracies show low growth rates as compared to democracy since democracy is organized and operated under formal institutions such as whether it has strong or weak political parties, puts a long or a short time limit in terms of legislators and presidents as well as presidential or parliamentary system. These complications are making hard to measure which institution mater and lend it to cross country comparisons (Rodrik, 2004).

Rodrik also claimed that institution, international trade and geography are deep determinants of income that causes income differences between developed and developing countries. Moreover, he argues that to advance the economic growth of developing country the institution of that country might be organized under market stabilizing, regulating and legitimizing system (Rodrik, 2004).

Richard and Talbott (2001), theory of institution states that both formal institutions (property rights, legal system, rule of law, constitution, etc.) and informal institution is vital in determining the economic growth path. According to their theory in developing countries, informal institutions like culture, customs, taboos, physiology, belief and norms play a significant role.

By supporting Rodrik theory of institution, Acemoglu suggested that the fundamental cause of growth difference between rich and poor countries is due to geographical advantage and institution. His theory of institution concludes that geographic factors are not the main reason for difference in prosperity between developed and developing country since correlation does not prove any causation between the variables. However, institutional factors plays a significant role for variation in prosperities of the countries around the world (Acemoglu et al., 2001).

Through classifying institution into economic institution, political institution and political power, Acemoglu & Robinson developed institution theory that played a significant role in economic growth (Acemoglu & Robinson, 2008). According to them, economic institutions determine economic growth through affecting the key productive factors in the economy. In specific terms, investments in human and physical capital as well as the technological advancement are factored out by economic institutions. Their institutional theory correspondingly enlightened that, economic institution considers the distribution of resources in the society. This implies that resources are distributed either an individual’s base or social groups. In this case problems might arise because all individuals and social groups may not prefer the same set of economic institution. This leads to conflict of interest among the various individuals and groups which needs a political power intervene to give the solution for this problem. However, Political power is also an endogenous source of growth and it distinguished as; de jure and de facto (Acemoglu & Robinson, 2006a). They explain that de jure political power originates from the political institution like the democracy versus an autocracy form of government in the society and significantly determines growth performance of a country. While de facto political power influences the economic growth through revolting the crisis, using arms, making a coup’s data and undertaking a protest. Individuals take such action with the aim to possess political power and to benefit the society i.e., de facto political power originates to solve its economic and political problems taken by the powerful groups and individuals (Acemoglu & Robinson, 2008).

2.1.3. Stochastic Growth Theory

Stochastic growth is the study of maximum inter-temporal allocation of production resource and consumption in an economy where production is subject to random shock (Acemoglu, 2009). Its influence has been greater by research that shows how the pointed stochastic growth model can be distributed to characterize the behavior of firms and consumers in a dynamic and competitive market equilibrium (Acemoglu, 2009; Brock & Mirman, 1972). It is useful in the development of positive theories of how the economy works. As a consequence, the theory has emerged as one of the central paradigms of dynamic economics. In the classical framework, it has three fundamental components:, the production possibilities frontier which determines the set of optimal allocation consumption, investment, output, an indeterminate environment shock relating to unsystematic productivity shock, and a sudden utility function that represents the choice of the economic agents (Acemoglu, 2009).

2.1.3.1. The Brock-Mir man Stochastic Growth Model

Brock and Mir man (1972), Provided the first systematic analysis of economic growth with unpredictable shocks. It is a theory of an optimal growth problem and solved for social planer maximization problems with aggregate production shocks (Acemoglu, 2009). It is a generalization of the neoclassical growth model that includes complete market system in which households and firms can trade in Arrow-Debru commodity. The model assumes with the presence of uncertainty that is caused by aggregate shock, full set of contingent claims is traded competitively, which implies that consumers can fully insure against idiosyncratic risks. It also assumes individual consumption and saving decisions are made after observing stochastic aggregate productivity term (Acemoglu, 2009).

The contribution Brock and Mir man stochastic growth model, where it shows how a productive factors of a given combination of labor and capital that used final good of the economy has been affected by aggregate productive shock and importance of contingent claims in the basic neoclassical model under uncertainty (Acemoglu, 2009; Mirman, 1971). This model is not only an important generalization of the baseline neoclassical growth theory only, but also provides the starting point of the influential Real Business Cycle models, which have been used widely to study a range of short- and medium-run macroeconomics questions (Acemoglu, 2009).

The major weakens of Brock and Mir man stochastic growth theory has, it does not hold environment and other productive shocks into representative household assumption under stochastic situation since it reliance only sufficiency trading in contingent claims. However, trading in contingent claims has necessary, but not only a sufficient condition for a typical household with ambiguity (Acemoglu, 2009).

2.1.3.2. Real Business Cycle Model

Real Business cycles are normally labeled as direct consequences of the actions of individual rational units or agents. This model acknowledged that the stronger is the desire to understand economic variation as something logical, the more likely is this micro economic methodology is recognized (Jeffrey, 2010 ). We claim that microeconomic agent differs across sectors and their arrangements change macroeconomic situation and then, results new and diverse micro economic variation.

The theory of existence of growth fluctuation in economic activities is recognized by economists before the foundation of modern economic theory that cites with a reference to something corresponding to a business cycle in biblical (Jeffrey, 2010 ). Starting the second half of the 19thcentury, researchers began to investigate the causes of frequent movement of the advanced country economic growth in which each “business cycle” bring to mind the others in many respects. The first comprehensive general business-cycle theory was published by Wesley Clair Mitchell in 1913 (Mankiw, 1989). Following his empirical observation, Dennis Robertson and A.C. Pigou were developed economic theories that help them try to explain sources of business cycles in the pre-depression period (Stadler, 1994).

Through investigating the role of deficient demand in spawning and elongating cyclical downturns, John Maynard Keynes renovated the inquiry of cyclical fluctuation in 1936 with his General Theory of Employment, Interest and Money. According to his argument, investment was the main causes for business cycle fluctuation of operating its effect on aggregate demand (Stadler, 1994).

In 1970s the supremacy of Keynes’s theory stared to vanish following by inflation and the oil price shock which brought stagnation in production activities and then, the stagflation that not fit with his traditional ideas (Long & Charles, 1983). Stagflation interrupted the empirical state of affairs of macroeconomics factors and gave a birth to recognize the importance of the microeconomic foundations of macro theory which generated new theoretical ideology. Based on this new theory economists tried to investigate the new events through constructing models of the business cycle based on carefully specified arrangements of macroeconomic assumptions (Stadler, 1994). For example, macro economist Robert Lucas established a model with imperfect information and market clearing that gives the impression to explain the characteristics of business-cycle features of the time (Jeffrey, 2010 ). Following the work of Robert Lucas, a neoclassical economist like Finn Kydland and Edward Prescott were developed the real-business-cycle model in the 1980s (Kydland, Finn, & Edward, 1982). The basic idea of this model is to introduce no imperfect information assumption to the perfectively competitive market system which is different from an imperfect competitive model developed by Sargent, Neil Wallace, and others in the early 1970s. It is also a stochastic growth model as it incorporates full-employment growth models that allows for random fluctuations in the rate of growth of output. Conversely, New Keynesian economist responded the problem through identifying and providing theoretical justifications grounded on sticky wages (Jeffrey, 2010 ). Later new Keynesians School stressed the existence of coordination failures and institutional problems that lead to inefficiencies in aggregate equilibrium growth (Nelson, Charles R., & Charles, 1982).

Therefore, from the above explanation we can understand that a numerous theories of real business cycle models are available. However, no consensus is achieved among economists to identify and explain the nature of real business cycle theory. For this, different reasons are factored out. The first basic reason is that many models are observationally comparable. This means that related results are consistent with several models, so noticing these results cannot be used to scrap one model in approval of the others. It does not mean, however, that the two models are necessarily equivalent. Even theories that have very different implications for the optimal design of economic policy may share many of the same predictions about observable relationships among variables. Second, empirical evidence that developed by different authors is bound by dissimilar methods of measurement and explanation. Thus, the macroeconomic argument over the feature and sources of real business cycles shock is debatable and looks continue near future.

2.1.4. The Nexus between Institution and Stochastic Growth

Stochastic economic growth theory hypothesizes that economic growth is affected by a number of factors of production such as government spending and levels of technology in a country (Stadler, 1994). In this process, the stochastic growth is associated with the ability of the nation to augment its level of technology along with development of factor of production such as land, labor and capital. This indicates that the institution has a role in explaining growth performance of a nation. However, its role has been ignored in the ordinary growth models. For example, The Solow model depends on several assumptions, one of them is that property rights are protected. Thus, the main drawback of this model from the viewpoint of institution is that it does not take into account any shortcomings in the quality of the institution, assuming that they do not exist (North, 1990). In addition, the Solow growth model does not explain why in some countries, individuals spend more on innovation, human and physical capital than in some other countries. Moreover, the neoclassical models of growth theory has still do not provide essential justification for the role of the institution (Acemoglu et. al., 2004).

Contrariwise the above theory, the current new growth theory explains fluctuation in real GDP and associated per capita growth characteristics among countries is related to institutional factors (see, North, 1990; Acemoglu et. al., 2001; and Rodrik et. al., 2004). For instance Acemoglu and Robinson (2010), state that:

“The differences in human capital, physical capital, and technology are only proximate causes in the sense that they pose the next question of why some countries have less human capital, physical capital, and technology and make wise use of their factors and opportunities. To develop more satisfactory answer to the question of why some countries are much richer than others and why some countries grow much faster than others, we need to look for potential fundamental causes, which may be underlying these proximate differences across countries”

They argue that institutional factors are the primary causes of the long run economic growth as well as growth fluctuation across the countries. North (1990), argued that institution plays a significant role for the stochastic growth performance through affecting the incentive structure in the society that may increase or hamper the economic activities. He identified that poor institutions may contribute to low output growth through a number of factors. First, it may increase uncertainty and transaction costs, accordingly shaking government spending, technological advancement and trade efficiency, and discouraging specialization investment in innovation, physical and human capital. Indeed, it contributes to building up and carrying out laws that facilitate the government to become the main agent in corruption which reduce consumption. Second, it leads fluctuations in productivity. When property rights are not secured, the owners of capital are less likely to invest, all other things being equal. If it is not easy to trade, get recognition, and grasp a sound share of the profits and to insure against risks, investment is again discouraged. On the other hand, sustainable economic growth needs that individuals choose to save some of their portion income so that investments in physical and human capital occur. In addition the amount of research devoted to the creation of new technology and application of new ideas is determined by human decision. The decision whether to devote regarding to save rather than consume, to risk invested in new project, or to take the time to devise a new way of undertaking something are prejudiced by a country institution. Third, it condenses incentive for individuals to work hard and save some portion of their income, for government unable to provide public goods and planned cost effective program to achieve well defined goals. Finally, malfunctioning institutions reduce productivity by deeming wealth to be immoral, by discriminating, and precluding some people from scrutinizing certain activities and by glowering people who have new ideas, then economic growth is suffering and subjected to stochastic performance (North, 1990).

By supporting North argument Murphy et al, (1991, explained that institutional problems may hamper output growth activities by providing possibility to economic decision maker to remain busy in redistributive politics with lower economic profits rather than growth encouraging economic activities.

On the other hand, strong institutions may encourage incentive structure in the society and leads to higher output growth through reducing uncertainty and promoting efficiency. Moreover, factors of production such as labor that can used for productive activities and not wasted in rent seeking actions can only work under incorrupt, efficient and strong institutions and leads to sustainable output growth (North, 1990). Strong institutions also improve the capacity of a nation in adopting new technologies invented in the form import, foreign aid and foreign direct investment somewhere else. This adoption may contribute a significant role in upgrading the overall growth of the nation in the world (Bernard & Jones, 1996). In general factors of production that used in productivity of a country are driven by the quality of its institutions (Hall & Jones, 1999).

2.2. Empirical Literature

The recent dispute of economists, governments, non-governmental organization and other development actors regarding the understanding of sustainable growth, strong enough to reduce inequality and absolute poverty is becoming increasingly forced to address the several growth problems of developing country like SSA. The argument is basically based on the query of what are the sources of sustainable economic growth in the region? Many scholars have studied the problem and have come up with the conclusion that persistent economic growth could be augmented by the significance of institutions in general and good governance indicators in particular through realizing the concrete policies (Easterly, 2006). Following this argument, this section explores the nature and techniques of interactions between institutions and stochastic growth behavior in SSA by designating the empirical investigation that has been conducted on economic growth. However, limited and fragmented empirical studies exist in the region.

The attentiveness offered in current periods with regard to whether the performance of institution determines the stochastic economic growth behavior of developing countries have been motivated by the works of Douglass North. North (1981), studied that unclear property rights my lead investment fluctuation and ineffective resource allocations and then stochastic economic growth. Following North, Elisa and Sara (2011), investigated that accumulation of knowledge drifts into production directly affects economic growth through examining the relationship between human capitals; foreign aid, foreign direct investment, output and public spending defined as the set of policies and institutions set by the administration that governs the economic situation in which representatives improves specialization and experiences. Their finding indicated that states with malfunctioning institutions fail to perform as states with stronger institutions.

Alonso (2010) studied the impact of political stability and no violence, government effectiveness, regulatory quality, voice and accountability, rule of law and control of corruption on economic growth in 154 countries using two-stage least square estimation technique from a period of 2006 to 2007. He found that all the indicated variables are result positive and significant effect.

Mobolaji and Omoteso ( 2009), examined the impact of corruption and other institutional factors indicated by governance index on economic growth in some selected developing country for the period of 1990-2004 by using data drown from International Country Risk Guide (ICRG). He concluded that corruption has negative impact on economic growth of these countries.

The impact of voice and accountability on economic growth is explained by its effect on corruption. Empirically, Buehn and Schneider (2009), investigated that decreasing voice and accountability can increase the possibility for corruption. Similarly, Aidt, Dutta, and Sena (2008), examine the consequence of political accountability on the spread of corruption and they conclude that the ability to grasp political leaders accountable could be a foundation of non-linearity in relating corruption and growth. This implies that accountability affects corruption, which in turn affects economic growth. Similarly, using a rule of law countries-specific data collected from the PRSG, Busse and Groizard (2008), examined the impact of rule of law and foreign direct investment on growth of 84 Countries using GMM estimation technique of estimation from 1994 to 2003 and found significant result.

Gyimah-Brempong and Gyimah-Brempong (2006), studied the regional differences impact of corruption on economic growth and income distribution using panel data approach collected from 61 country from 987-2006. The result indicated that the impact of corruption is very high in Africa compared to Asian, OECD and Latin America countries.

Lane (2003b), assessed the impact of institution on growth fluctuation across countries over the period of 1960-98 using panel data drawn from developing countries. He found that the fluctuation of output growth across countries varies significantly and associated with the literature of greediness effect power dispersion.

Williamson (2000), investigated empirically the effect of institution on growth of developing county by using cross-countries difference on productivity. He concludes that nations with insecure institution make business firms to act under uncertain environment.

Gupta, Davoodi, and Tiongson (2000), studied the impact of corruption and government effectiveness in developing country and found that it shrinks availability of the resources uses in health and education via increasing the operating cost of government. Similarly, Johnson, Kaufmann, and Zoido-Lobaton (1999), found the binding power of corruption and rule of law on human capital through tax evasion system, which reduces drastically the availability of resource and tax income to finance public provision of services such as education and health.

Generally, both theoretical and empirical literature review provides that institution and level of good governance are the fundamental determinants of countries’ stochastic growth performance. However, the earlier study focused on long term effect of institution on economic growth. In addition, the methodology they used to explore the nexus between them is linear and not uniform. Moreover, depending on the time period of study, variables taken in study and study area; their analysis and conclusion is different. Therefore, by considering the finding of past researchers and their limitation, we used important variables indicated in the literature review to examine their contribution on the stochastic economic growth behavior of Sub- Sahara Africa

2.3. Conceptual Framework

The conceptual framework developed in figure 1 was designed from both theoretical, empirical literature reviews discussed above. It is designed and developed by modifying Dunning (2000 ), eclectic growth model, which is the leading analytical frame work that take into account different factors of institution and their relationship with economic growth. Accordingly, a weak institution that explained in the literature is determined by six interdependent governance variables such as corruption, low level of voice and accountability, rule of law problem, political instability and violence, government ineffectiveness and weak regulatory quality. Furthermore, as aforementioned in the literature part, we define institutions as combinations of these interrelated factors. Therefore, the paper assumed that weak institutional development of SSA is directly affected by these interrelated factors. Moreover, the literature review point out that stochastic economic growth of the country is the result of individual and collective action of these interrelated factors. These means stochastic growth is directly affected by weak institution and governance variables explained above. In addition to direct effect, the literature review also indicates that weak institution and bad governance could cause stochastic growth through spawning uncertainty and lack of public confidence in the SSA. On the other hand, uncertainty and lack of public confidence always caused by informal networking, high bureaucracy and long licensing process. Hence, it affects growth performance through three channels. These are; first, it severely affects technological advancement through creating political instability, reducing the level of knowledge, gleaming human capital and creating scarcity of investment in R&D. It also affects technological advancement through limiting private investment opportunity for imported capital goods.

Second, it causes fiscal policy shock through affecting government expenditure and capital inflow in the form of foreign aid and foreign direct investment. Similarly, it affects government expenditure through developing tax evasion and an exemption system for corrupted investors, creating instability in government revenue and facilitating complex fiscal management. It also reduces business confidence and societies trust in the state's development agenda. Reduction in government expenditure affects public investment and consumption as it curtail investment in health, education, infrastructure development and then, leads to output growth fluctuation.

Correspondingly reduction in public confidence and uncertainty reduce the flow of foreign direct investment and aid inflow from donors and NGOs which used to finance fiscal gap of the region. This is due to the fact that foreign direct investment and aid are external source of finance, which inflows based on the socioeconomic and political conditions of the receipt countries. In addition, if one countries, institutional systems is poor foreign aid damages investment growth of that countries through stimulating corruption and rent seeking activities of the government (Economides, Kalyvitis, & Philippopoulos, 2008). Similarly Kim, Ki, and Seo (2003), supports the ineffectiveness of aid to improve private investment under poor institution. They found that instead of encouraging domestic investment it creates foreign exchange appreciation that interrupts the growth performance and competitiveness of developing country at global market.

Finally, it affects the trade structure of the region through creating terms of trade shock, which leads export fluctuation in the region as uncertainty reduces the export of primary product in relative to import product. Therefore, through this trigger factor we developed a figure that represents our stochastic growth model to examine the effect of institution and level of good governance on the stochastic growth behavior of the region.

illustration not visible in this excerpt

Figure 1: Relationship between institution and stochastic economic growth.

Source: Author, 2016

CHAPTER THREE: METHODOLOGY

3.1. Model Specification

To estimate the contribution of institution and level of good governance on stochastic economic growth across countries, the paper used growth model in the form of neoclassical production function;

illustration not visible in this excerpt

Where gyi= refers to annual growth rate of GDP, V= represents other controlled variables that determine economic growth and Zi= denotes institutional variables explained with government quality index (Kaufmann, Kraay, & Mastruzzi, 2007).

The theoretical and empirical evidence that is summarized in literature part reveals that various macro-economic insecurity, including weak institution and bad governance (the interest varies for this paper) cause stochastic growth. Regardless of these factors, studies suggested that technological shock and fiscal policy uncertainty caused by poor institution and bad governance that causes uncertainty and lack of public confidence are treated as the most determinant factors of stochastic growth (Jeffrey, 2010 ). Therefore, in order to examine our stochastic growth model, this study incorporated the above factors into the equation (1) and specified as follows:

illustration not visible in this excerpt

Researchers such as Nicholas (2014), Ranis (2011), Grossmann and Steger (2007) and Findly (1978) conducted research on, what determine or influence the level of technology in different countries and thereby their growth performance. According to these researchers, the level of technology that influences growth performance and create economic disparity among countries is affected by three different technological factors. These are technology diffusion, technology transfer and technology spillover. Furthermore, research conducted by Hussain (2011) and Grossman and Helpman (1991), indicated that from the three technological factors, in developing countries like SSA, technology spillover effect play more significant role in generating technological variation and then, growth instability. Suppose, by capturing the effect of technological shock via technology spillover effect, equation (2) can be rewritten as follows:

illustration not visible in this excerpt

Additionally, research conducted by Zerayehu (2013), Cameron, Proudman, and Redding (2005) and Griliches (1992) revealed that expenditure on R&D uses as a proxy variable for technology. However, due to limited budget accessibility, the growth effect of investment on research and development in developing countries, particularly in the SSA is insignificant (WB, 2014). Instead of this researcher argued that developing countries that uses technology in production activity is peroxide by importing capital goods which depends on the countries technology transfer obstacles such as institutional factors, and the like (Siebert, 2007; Zerayehu, 2013). Accordingly, this argument point out that, imported capital goods was used as a proxy variable to capture the effect of technological shock on stochastic economic growth. Therefore, equation (3) can be rewritten as follows:

illustration not visible in this excerpt

On top of the above argument, Yichen and Boxin (2012) and Griliches (1992) stated that technology imported in the form of capital good affects economic growth performance through affecting labor productivity. Similarly, research conducted by Yichen and Boxin (2012) and Carmen, Sara, and Jaime S. (2008) concluded that through altering the quantity and quality of capital technological spillover can affect labor productivity. On the other hand, researchers like Mavannoor (2009), Javorcik (2004) and Grossman and Helpman (1991), indicated that labor productivity is affected by imported capital goods which in turn depends on the terms of trade shock. This implies that trade fluctuations are an important factors that affect the labor productivity and then, growth performance in the region. Therefore, through taking into account the effect of trade shock, equation (4) is extended as follows:

illustration not visible in this excerpt

An empirical finding of Theo (2006) suggested that the economic growth effect of terms of trade shocks has not only limited to direct effects on growth, but also the resulting changes in volatility of output. Correspondingly, research conducted by Tsai (2010) and Harberger (1950) also projected that decline in the terms of trade would decrease real income by deeming current account balance. In addition, Baxter and Kouparitsas (2000) indicated that terms-of-trade instabilities are double as large in emerging countries as in advanced countries due to the substantial dependence of developing countries on exported goods, whose prices are more unstable than those of manufactured goods. On the other hand, economic theory proposed that the efficiency with which countries cope with changes in their terms-of-trade shocks depends primarily on the nature of their exchange rate regime (Christian & Cédric, 2003). Thus, the above arguments indicated that the economic effect terms of trade shock can be captured with countries trade openness towards a global economy. Therefore, by taking terms of trades shock effect through countries openness to trade, equation (5) is rewritten as follows;

illustration not visible in this excerpt

Moreover, stochastic growth is not only explained by the above economic variable factors alone. It is also being affected by institutional uncertainty related to fiscal policy, investment, consumption pattern and flow of capital into the nations (R. Lensink, Hong, & Elmer, 1995).Weak institutional policy affects capital inflow through curtailing and creating uncertainty on revenue generated from aid (Lensink&Morrissey, 1999). On the other hand, researches like Franco-Rodriguez et al, (1998) indicated that due to incorporating aid into physical planning, many of developing country government policy particular fiscal policy: government expenditure has affected with aid revenue. On a similar theme, studies conducted by Lensink and Morrissey (1999) address the effects of aid as a source of government revenue that will affect investment decisions. According to these researchers if aid revenues are unstable, it is probably that expenditures will be changed and investment is often the easiest expenditure heading to cut in the short-term. This indicated that aid revenue instability that leads government revenue and expenditure instability directly curtail growth performance. Research conducted by Aizenman and Marion (1993) also shown that institutional problems that affects economic growth through distressing public investment. Therefore, by capturing the effect of aid fluctuation, foreign direct investment and public investment expenditure as a measure of fiscal policy shock, equation (6) is extended into the following form:

Similarly, economists argued that in addition to investment channel institutional uncertainty can dampen economic growth through affecting the consumption decision, increasing cost of finance, lower asset prices (Bernanke, 1983) and creating inflationary uncertainty (R. Lensink et al., 1995). It affects consumption decision extremely since the cost of reverting consumption is very high and not early revert (e.g. Due to fixed and adjustment costs). These means institutional uncertainty gives a consumer an incentive either to cancel or postpone their decision until ambiguity is determined and more information is offered, thus glooming economic growth performance. As a result, as variation in consumption makes producers to be not confident about the economy, it adversely affects economic growth. Therefore, by incorporating consumption expenditure and inflation variables in the stochastic growth model, equation (7) is extended as follows:

illustration not visible in this excerpt

On top of the above argument, Bardhan (2005), Glaeser et al. (2004), Rodrick and Subramanian ( 2003) and North (1990) analyzed the effect of institutions on growth. However, as explained in the introduction and literature review part measuring the effect of institution on economic growth is very difficult and challenging issue. The main justification is, first, there is no well properly indicated and quantified institutional variables are available. Second, the methodology used to analyze its effect is varying as they are commissioned by dissimilar organizations like the World Bank and as the IMF. Therefore, institutional measures are different as they rely on the organizations’ attention of the inquiry. Though, these are the limiting factors, currently; researchers, institutional economists and international organizations have mostly used world governance index developed by the World Bank to examine the cross country effect of institution and level of good governance on economic growth (Geoffrey, 2006).

[...]

---

^[1] Sub-Saharan Africa is geographically the area in the continent of Africa that lies south of the Sahara Desert.

^[2] Angola, Benin, Botswana , Burkina Faso, Burundi, Cameroon ,Cape Verde, Central African Republic, Chad, Comoros, Congo (Brazzaville),Congo DRC (Zaire), Cote d'Ivoire, Djibouti ,Equatorial Guinea, Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissaau, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mauritius ,Mozambique, Namibia, Niger, Nigeria, Reunion, Rwanda ,Sao Tome and Principe ,Senegal ,Seychelles ,Sierra Leone, Somalia, South Sudan, South Africa, Sudan, Swaziland, Tanzania, Togo, Uganda, Zambia ,Zimbabwe.

^[3] The term region refers the African countries covered in this study. Thus, throughout this paper the terms Sub-Saharan Africa, SSA and region are interchangeably used.

^[4] Specifically Chad, Somalia, Sudan, Burundi and Equatorial Guinea are the most corrupt countries

^[5] The region’s GDP, Djibouti excluded, was only USD 167 billion and the average per capital GDP was USD 1045 in 2014. Comparably, in the same year the GDP of Canada, OECD and East Asia & Pacific was $32489, $6465, $1238 billion, respectively and its average per capital GDP Latin America was $6124, OECD $32489 and East Asia & Pacific $6465 respectively.