Constraints of initial poverty and inequality on the poverty-effects of economic growth in developing countries : a dynamic panel data analysis

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(2) Constraints of initial poverty and inequality on the Poverty-effects of economic growth in developing countries: A dynamic panel data analysis by. Delphin Kamanda Espoir A dissertation submitted in fulfilment of the degree of Master’s in Commerce of Development Economics at the College of Business and Economics UNIVERSITY OF JOHANNESBURG. Supervisor: Professor Nicholas Ngepah 2018.

(3) ABSTRACT The research motivation of previous studies on the relationship between growth and poverty lies in the interest of discovering the best policy measures to alleviate poverty in a relevant way. This study, among others, subscribes to the same logic. It assesses the role of initial inequality and poverty in predicting the speed at which poverty responds to changes in mean income. We used an annualised panel data (at USD1.9/day) of 112 developing countries segregated into six world regions, for the period 1981-2013. The study follows Bond (2002) in developing an autoregressive growth-poverty model. Over and above the specifications of the well-known growth-poverty identity model, the autoregressive model subjects the change in poverty to its earlier shocks. We first replicated the estimates within the growth-poverty identity model, which supported the previous findings on the critical role played by high initial inequality and high ratio poverty line over mean income in predicting the poverty effects of growth in mean income. However, when changes in poverty were subjected to earlier shocks within the autoregressive framework, the magnitude of both absolute poverty elasticities (income and inequality elasticities), was found to increase with initial inequality and the ratio poverty line over mean income, decreasing only with the initial level of poverty. As such, the results support the dominant role of initial poverty over other initial conditions in predicting the speed at which poverty responds to changes in mean income, as stated in Ravallion (2012). In addition, we found that ignoring the initial level of poverty in modelling the growth-poverty nexus in the identity model, yielded an overestimation of the coefficients of both poverty elasticities. The autoregressive framework suggests that poverty reduction policies should be differentiated according to regional specifics. Growth versus inequality policies as measures of improving poverty reduction efforts cannot be used as a “one-size-fits-all” approach. The cross-regional variations in income and inequality elasticities suggests that redistribution policies could be more fruitful in achieving poverty reduction in Eastern Europe and Central Asia, the Middle East and North Africa, and in East Asia and Pacific. However, for regions such as Sub-Saharan Africa and South Asia, growth-boosting measures must triumph over redistribution for sustainable poverty reduction. Keywords: income elasticity, inequality elasticity, initial poverty, initial inequality, poverty headcount, poverty elasticity.. ii.

(4) DEDICATION This work is dedicated to my dear parents, MUSOBWA NARUKEMBA KAMANDA and ESPERENCE MACHOZI.. iii.

(5) ACKNOWLEGMENTS The achievement of this work greatly benefited from the caring guidance of my supervisor, Professor Nicholas Ngepah, at the University of Johannesburg. I fully appreciate his support, guidance, encouragement and constructive comments. I could not have imagined having a better supervisor and mentor for my dissertation. I must mention my appreciation for the financial support I received from my supervisor, Professor Nicholas Ngepah, through the DPE Project. The achievement of this work would not have been possible without that invaluable financial support. I also extend my thanks to my colleagues Ms. Daffodils Daffs and Mr. Tumiso Maitisa for their encouragement and useful edits of various versions of the draft of this dissertation. I gratefully acknowledge my brothers and sisters who, at any difficult moment, were available with their encouragement through prayers. Particular thanks are addressed to Musore Manasse, Boss Kamanda, Emile Kamanda, Queen Kamanda, Pascal Kamanda, Diallo Rutaha, Benjamin Mudiandambo and Mutuwa Matendo. Finally, for all that has been achieved, the glory goes to God through Jesus Christ, who gives insight, good health, and long life.. iv.

(6) DECLARATION I, Mr. Espoir Kamanda Delphin, declare that: a) The research reported in this minor dissertation, except where otherwise indicated, is my original research. b) This minor dissertation has not been submitted for any degree or examination at any other university. c) This minor dissertation does not contain other person’s data, pictures, graphs or other information, unless acknowledged as being sourced from that person. d) This minor dissertation does not contain other person’s writing. Unless specifically acknowledged as being sourced from other researchers. Where other written sources have been quoted then: i.. Their words have been re-written but the general information attributed to them have been referenced; and. ii.. Where their exact words have been used, their writing have been placed inside quotation and referenced.. e) Where I have reproduced a publication of which I am author, co-author or editor, I have indicated in detail which part of the publication was actually written by myself alone and full referenced such publications. f) This dissertation does not contain text, graphics or tables copied and pasted from the internet, unless specifically acknowledged and the source being detailed in the minor dissertation and in the reference section. Signed at Johannesburg on the 18th day of June, 2018. Delphin Kamanda Espoir Email: [email protected]. v.

(7) NOTICE A version of this minor dissertation has been submitted to a peer review journal for publication.. vi.

(8) TABLE OF CONTENTS ABSTRACT…………………………………………………………………………………….…ii DEDICATION...………………………………………………………………………………....iii ACKNOWLEGMENTS……………………………………………………………………….....iv DECLARATION……....…………………………………………………………………………v NOTICE…………………………………………………………………………………...…….vi CHAPTER 1: INTRODUCTION……………………………………………………………...1 1.1. BACKGROUND AND PROBLEM STATEMENT……………………………………....1 1.2. RESEARCH QUESTION…………………………………………………………………3 1.3. RESEARCHMETHODOLOGY…………………………………………………………..3 1.4. IMPORTANCE OF THE STUDY………………………………………………………...4 1.5. STRUCTURE OF THE STUDY…………………………………………………………..5 CHAPTER 2. THE HISTORICITY, TRENDS AND POVERTY REDUCTION STRATEGIES IN DEVELOPING COUNTRIES…………………………………………....6 2.1. INTRODUCTION………………………………………………………………………...6 2.2. THE HISTORICITY OF POVERTY IN THE DEVELOPING WORLD……………….6 2.2.1. The presence of the past…………………………………………………………………….6 2.2.2. The debt crisis and the effects of structural adjustment programs…………………………………7 2.2.3. Geographical, dependency and structuralism theories…………………………………………....8 2.2.4. Income inequality and poverty effects of globalisation..…………………………………………10 2.3. POVERTY REDUCTION STRATEGIES……………………………………………......12 2.3.1. The IMF and World Bank poverty reductionstrategy.……………………………………........12 2.3.2. The Millennium Development Goals (MDGs) and the Sustainable Development Goals (SDGs).......12 2.4. REGIONAL DIFFERENCES IN MEAN INCOME, INEQUALITY AND POVERTY..13 2.5. CONCLUSION…………………………………………………………………………....16 vii.

(9) CHAPTER 3. LITERATURE REVIEW OF THE RECENT EMPIRICAL EVIDENCE ..17 3.1. INTRODUCTION .............................................................................................................................17 3.2. REVIEW OF THE DEBATE ON THE POVERTY EFFECT OF GROWTH ...................17 3.3. CONCLUSION ...................................................................................................................................20 CHAPTER 4. METHODOLOGY, DATA AND ESTIMATION TECHNIQUES ................21 4.1. INTRODUCTION .............................................................................................................................21 4.2. METHODOLOGICAL APPROACH ............................................................................................21 4.2.1. Model specification .............................................................................................................................21 4.1.2. The algebra of the income and inequality elasticities of poverty ..............................................................26 4.2. ESTIMATION TECHNIQUES.......................................................................................................28 4.3. DATA AND VARIABLES DESCRIPTION ................................................................................30 4.4. CONCLUSION ...................................................................................................................................32 CHAPTER 5. EMPIRICAL RESULTS .................................................................................................33 5.1. INTRODUCTION………………………………………………………………………...33 5.2. DESCRIPTIVE STATISTICS……………………………………………………………..33 5.3. EMPIRICAL RESULTS AND DISCUSSION ..............................................................................34 5.4. PREDICTED INCOME AND INEQUALITY ELASTICITIES OF POVERTY………..38 5.5. EXPLAINING TRENDS IN POVERTY CHANGES BY REGION FROM 1981 TO 2013 ........................................................................................................................................................................43 5.6. CONCLUSION ...................................................................................................................................44 CHAPTER 6. CONCLUSION AND POLICY IMPLICATIONS ................................................45 REFERENCES..………………………………………………………………………………...48 APPENDIX…………………………………………………………………………….…….......52. viii.

(10) LIST OF FIGURES. Figure 1: Poverty effects of trade integration via growth and distributional channels……………...10 Figure 2: Regional trends in mean income (in US dollars)…………………………………………15 Figure 3: Regional trends in income inequality (Gini index)……………………………………….15 Figure 4: Regional trends in poverty rates (headcount rates at $1.9/day)…………………………..16 Figure 5: Plot of income and inequality elasticity against initial Gini rates…………………………40 Figure 6: Cross-country plot of income elasticity against initial poverty rates……………………...41 Figure 7: Cross-country plot of inequality elasticity against log of initial poverty rates…………….41 Figure 8: plot of income and inequality elasticity against initial poverty rates……………………...43. LIST OF TABLES Table 1: Inter-regional mean income, inequality and poverty trends differences…………………... 13 Table 2: Summary statistics………………………………………………………………………..32 Table 3: Estimated income and inequality elasticity of poverty: effect of the initial level of income inequality……………………………………………………………………………………. 36 Table 4: Estimated income and inequality elasticity of poverty: effect of both initial income inequality and initial poverty………………………………………………………………… 38 Table 5: Computed income inequality elasticities of poverty across regions………………………. 39 Table 6: Computed income and inequality elasticities across regions……………………………... 42 Table 7: Income and inequality elasticity of poverty by country (within the autoregressive model).. 52 Table 8 Poverty growth against predicted poverty growth by region at $1.9/day from 1981-2013....43. ix.

(11) LIST OF ACRONYMS/ABBREVIATIONS ECA EAP. Eastern Europe and Central Asia East Asia and Pacific. FGT. Foster, Greer and Thorbecke. GDP. Gross Domestic Product. GMM. Generalised Method of Moment. IMF. International Monetary Fund. HIV/AIDS. Human Immunodeficiency Virus/Acquired Immune Deficiency syndrome. LAC. Latin America and the Caribbean. MDGs. Millennium Development Goals. MENA. Middle East and North Africa. OLS. Ordinary Least Square. PGI. Poverty-Growth-Inequality. PovCalNet. Poverty calculator network. PRSP. Poverty reduction strategy paper. SA. South Asia. SAPs. Structural Adjustment Programs. SDGs. Sustainable Development Goals. SSA. Sub-Saharan Africa. UNDP. United Nations Development Program. UNAIDS. The Joint United Nations Programme on HIV/AIDS. USD. United States Dollars. 2SLS. 2 Stage Least Square. 3SLS. 3 Stage Least Square. x.

(12) CHAPTER 1: INTRODUCTION 1.1.. BACKGROUND AND PROBLEM STATEMENT. The relationship between economic growth and poverty has raised significant research interest in the field of development economics since early 1990. Particular interest has been shown in the quest to understand how to reduce poverty in the best way. The last three decades to 2015 have been characterised by higher economic performance in most developing countries. Economic growth in developing countries taken together remains robust, even with the exclusion of China and India (Fosu, 2017). Growth has been hailed as the key condition for sustainable poverty reduction (Dollar & Kraay, 2002). This assertion has been backed by the Chinese success story in reducing poverty since early 1990, confirming that high growth rates can enhance the level of development and reduce poverty. However, emerging consensus seems to be that economic policies that target growth alone are necessary, but are not enough to alleviate poverty for certain specific countries or regions in the developing world (Besley & Cord, 2007). Rising income inequality trends in some regions such as Latin America and the Caribbean, Eastern Europe and Central Asia, as well as in Sub-Saharan Africa, are currently being blamed for the less than commensurate effects of their growth on poverty (World Bank annual report, 2005). Fosu (2015) for instance, identifies the uneven distribution of the benefit of growth in many countries of the Sub-Saharan Africa region as well as for the other developing regions, as a major cause to the persistence of poverty, despite the annual average GDP growth rates having surpassed the population growth rates. Empirically, a significant number of studies, including that of Datt and Ravallion (1992), have attempted to understand the growth-poverty nexus. They have done so by, among other things, closely investigating the role of income distribution as an important intermediate predicting factor of the responsiveness of poverty to growth in mean income. The existing literature on the role of income distribution is mixed. On the one hand, some results highlight the leading role of the effect of economic growth over the re-distributional effect in reducing poverty. Studies conducted by Ravallion and Chen (1997), and Dollar and Kraay (2002) are the most illustrative. They argue that the effect of income distribution on poverty is minim if it is not zero. One of the reasons advanced for the lack of income distribution effect on poverty is that the income of the poor increases equi-proportionately as those of wealthy people. Romer and Gugerty (1997), Gallup, Radelet and Warner (1998) also demonstrate that, on average, the incomes of poor people tend to increase in the same proportion as the income of the rich people..

(13) On the other hand, other studies argue that income distribution is an important mediating factor in the effect of growth in mean income on poverty. Thorbecke (2013) notes that income inequality is one of the most important filters between growth and poverty. In this respect, evidence has been shown that the poverty effect of growth is high when inequality is low. For example, Fosu (2010) assesses the constraining effects of income inequality on Africa’s poverty reduction efforts. Using the so-called standard growth-poverty model, he finds that the poverty effect of a change in mean income is a decreasing function of inequality. He concludes that high inequality is extremely harmful to the speed at which growth is impacting poverty. Moreover, Ravallion (2005) argues that intuitively, the higher the initial level of inequality in a country, the lower the poor people will benefit from growth unless the growth effect is accompanied by significant distribution changes to lower inequality. Another growing conjecture, advanced by Ravallion (2012)1 is that the effect of income inequality and/or initial inequality on the responsiveness of poverty to changes in mean income is only part of the story of what is now known as binding constraints of growth to poverty. Ravallion (2012) emphasises the additional and critical role that initial levels of poverty can play as a binding constraint to the povertyreducing effects of growth. His thesis relies on the neoclassical growth-convergence theory (Solow, 1956; Barro & Xavier Sala-i-Martin, 1992). According to the convergence theory, the economy of a country that starts with low mean income may enjoy rapid income growth compared to high-income countries, with both converging to a long-run steady state mean income level. Furthermore, for lower mean income countries, poverty reduction would seem an inevitable result of economic growth. Such developments may never transpire for most of them, due to their high initial level of poverty posing a drag on the pace at which growth translates into poverty reduction. Empirically, Ravallion (2012) displays this claim on a sample of 90 developing countries. He calculates an average elasticity of the initial level of poverty with respect to the changes in mean income as equal to 2, while an absolute mean income elasticity is shown as equal to −2.5.2 However, the main concern with his methodological approach is that it fails to include the initial inequality and the initial poverty, both interacted respectively with the change in mean income and the change in inequality. This omission of the interactions terms can possibly introduce a significant bias in the estimate of poverty Ravallion, M. (2012) published the most recent empirical evidence that used a panel data for 100 developing countries and assessed the issue of why we don’t see poverty convergence between poor countries reach countries as predicted by the neoclassical growth theories. He revealed that the higher initial level of poverty was the main stylised fact that constrained the speed at which growth should be effective to poverty, and hence the lack of poverty convergence in poverty reduction. 2 The corresponding average elasticity of the initial level of poverty is obtained through average values of both OLS and GMM estimated coefficients in Ravallion (2012). 1. 2.

(14) responsiveness to changes in mean income. Although his efforts to show that initial poverty poses a significant drag to current poverty reduction efforts, if his coefficient is estimated with bias, it can lead to misleading policy prescriptions. There is therefore a need for a framework that eliminate this bias. This work seeks, among other things, to close this gap by taking into account those interactions terms. This amplification of the model is important, firstly, to test whether inequality still matters in the poverty effects of growth once initial poverty is controlled and secondly, to identify the relevant strategy between the growth-enhancing and inequality-reducing policies in order to alleviate poverty or rather, to eradicate it. 1.2. RESEARCH QUESTION This study aims to empirically reassess the responsiveness of poverty to changes in mean income across various developing regions of the world, after controlling for both initial inequality and poverty. In doing so, it answers three key questions: (1) Are the initial levels of inequality and poverty muffling the speed at which growth is effective in reducing poverty? (2) Are both the initial levels of inequality and poverty equally binding constraints to the effects of economic growth on poverty reduction? (3) Are there cross-regional differences in the trends of poverty reduction since early 1981 to date, and to some what extent can the cross-regional differences be explained (by only the initial distributional effect; the initial poverty effect, or both)? 1.3.. RESEARCH METHODOLOGY. Numerous studies, including that of Janvry and Sadoulet, (2002), Dollar and Kraay, (2002) used the so-called standard growth-poverty model to assess the relationship between growth and poverty across countries and time periods. This model is based on multiple linear regression, where the change in poverty is explained by the change in mean income, and a host of other explanatory variables. Bourguignon (2003) criticises the use of such a functional specification due to the fact that it ignores one of the key assumption: the identity-related link between the change in mean income and the change in poverty. Under the identity assumption, the stated growth-poverty relationship is determined in the context of where the distribution of income between individuals is assumed as holding constant. This framework provides a comprehensive functional specification (an interaction model) which allows for assessment of the extent to which the change in mean income is effective in 3.

(15) predicting the change in poverty. It also allows for correction of the lack of precision when measuring the contribution of the distributional component included in the growth-poverty equation. This study built on the well-known growth-poverty identity model by Bourguignon (2003), while taking the conjectures of Ravallion (2012) into account. However, the original formulation of the growthpoverty identity framework was revisited in order to account for the initial level of poverty. The development of the augmented framework closely follows the reasoning of Bond (2002). The resulting framework is a dynamic growth-poverty model that can be termed an autoregressive growth-poverty model. This work represents the only attempt to date to estimate the growth-poverty nexus controlling for the initial level of poverty and its interactions with both changes in mean income and changes in income inequality. The work utilised panel data from 112 developing countries from the World Bank PovCalNet dataset, spanning 1981 to 2013. The choice of this time interval was pragmatic and was justified by the availability of the time series data of the variables included in the regression equations. The estimation process used the headcount poverty measure as the dependent variable. Our approach first replicated the estimates in which the role of growth in mean income and that of inequality were examined to determine both income and inequality elasticities of poverty, as in Kalwij and Verschoor (2007) and Fosu (2017). All the estimates were obtained through the two-step system Generalised Method of Moment (GMM). The choice of such estimators was due to their ability to overcome problems of bias induced by the double causality between growth and income inequality with poverty (Kalwij & Verschoor, 2007;3 Fosu, 2017), and for their gain of allowing extra moment conditions compared to the Anderson Hsiao estimators on a differentiated dynamic model (Bond, 2002). 1.3. IMPORTANCE OF THE STUDY Recently, Bourguignon (2003), Besley and Burgess (2003) and Fosu (2017) stressed the role of initial inequality in predicting the speed at which poverty responds to a change in mean income. Among other things, they demonstrate that a higher initial inequality index muffles the developing countries’ poverty effect of growth in mean income. However, to date the role of the initial level of poverty is still under- investigated. The only known work focusing on the role of initial poverty to the. 3. Kalwij and Verschoor (2007) used the same method in assessing the growth, inequality and poverty equation and controlled for bias in the estimates using a set of instruments such as population growth, GDP growth and several interaction terms between earlier shocks of mean income and the Gini coefficient.. 4.

(16) relationship of interest is provided by Ravallion (2012). In emphasising the role of growth on poverty reduction, Ravallion (2012) suggests that if the element of initial poverty is not considered in the examination process, the outcomes might be misleading and therefore lead to a wrong policy prescription. He also demonstrates that once the initial poverty is considered, the effect of income inequality becomes no longer significant to explain countries’ differences in the poverty effect of growth in mean income. In this respect, the significance of this work resides in it providing a new empirical assessment on the roles of initial inequality and poverty (both coupled in a unique specified equation) to the effects of growth on poverty. The work attempts to shed more light in a global context by providing new empirical evidence that will enrich or enlarge the existing literature. This empirical evidence emphasises the importance of having less people living below the poverty line as an advantage of amplifying policies that seek to alleviate poverty or eradicate it. However, the focus on both initial conditions (initial inequality and poverty) appears to be interesting from the policy prescription point of view. This is due to the fact that it allows one to precisely determine whether the growth-boosting or inequality-reducing policy is most necessary, and which should be prioritised. Finally, it allows for determining whether there is a need for applying both policy prescriptions concomitantly. Moreover, in respect of policy perspectives, this study allows one to identify the appropriate regional poverty reduction policy – either initial inequality or poverty – and which appears to be the most binding constraint on the effects of growth in poverty reduction. 1.4. STRUCTURE OF THE STUDY The rest of the study is structured as follows: Chapter 2 provides the historicity, trends and poverty reduction strategies in developing countries. Its interest resides in understanding how the current extreme poverty figures were generated, and why they tend to persist. The chapter also presents the regional trends differences in mean income, inequality and poverty since early 1981 to 2013. Chapter 3 presents a literature review of the recent empirical evidence. It seeks to understand different outcomes on the growth-poverty nexus from these previous works. Chapter 4 describes the methodological approaches (the identity and the autoregressive model) and the data sources used in the empirical test. Chapter 5 presents and discusses the empirical results of both identity and the autoregressive model, and finally, Chapter 6 concludes by providing some policy implications from the findings. 5.

(17) CHAPTER 2. THE HISTORICITY, TRENDS AND POVERTY REDUCTION STRATEGIES IN DEVELOPING COUNTRIES 2.1. INTRODUCTION The interest of this chapter is on reviewing the historicity of poverty in developing countries. In doing so, we sought to understand how the current extreme poverty figures were generated and why they tend to persist. We also sought to understand the fundamentals of different poverty strategies adopted and proposed to the developing world by the Breton Woods institutions (the IMF and the World Bank). This chapter also aims to understand the global and the specific regional poverty rates trends. This understanding is for the purpose of identifying and appreciating the poverty reduction progress achieved regionally and globally since 1981 to date. 2.2. THE HISTORICITY OF POVERTY IN THE DEVELOPING WORLD According to Branwen (2007), the simple empirical exercise of defining, measuring and explaining the nature and extent of poverty and income inequality as observed over these past three decades, does not in itself provide a relevant understanding of their existence and persistence. In this regard, Branwen (2007) suggests that one should be concerned by apprehending the causally efficacious, the intransitive, and the historical connotations of the socio-political context in which conditions of poverty, income disparities and impoverishment processes are generated over time. This section provides a summary of some of the well-documented causes that produce poverty and wealth inequality in most countries of the developing regions. Four main causes are maintained to be the most illustrative of how absolute poverty and inequality occurred and how it tends to persist in the developing world. These four causes are: the presence of the past (which includes slavery, colonialism and the primitive accumulation of wealth in the developed world); the debt crisis and the effects of structural adjustment programs (SAPs); geographic location and natural resources dependence; and the effects of globalisation on income inequality and poverty.. 2.2.1. The presence of the past Figures on individual wealth up to 2015, a year linked to the late millennium development goals (MDGs) of halving the extreme world poverty from their 1990 levels, indicate how much global effort is still required in reducing absolute poverty. Extreme poverty has decreased in most regions of the world, as shown by the World Bank PovCalNet dataset, which demonstrates that extreme poverty (at USD1.9 per day) globally decreased (from 51.70% in 1981 to 12.71% in 2013). The regional figures for the Sub-Saharan Africa region indicate a slight decrease (from 55.13% in 1990 to 42.29% in 2013), 6.

(18) compared to East Asia and Pacific (from 80.85% in 1981 to 3.64% in 2013). However, income inequality generally shows increasing trends in most regions of the world. The most used indicator for income inequality, the Gini index, ranges from just above 0.55 in Africa, Latin America and the Caribbean countries, to below 0.30 in Eastern Europe, Central Asia and the Western European countries. The persistence of absolute poverty and inequality is currently well studied and documented in the literature (see Deininger & Squire, 1996); Li, Squire & Zou, 1998). Several theories and evidence indicate that the persistence of absolute poverty and inequality correlates to credit market imperfections, economic and political problems and the intergenerational transmission of socioeconomic status (see for instance, Becker & Tomes, 1986; Fernandez & Rogerson, 2001; Galor, 2009). Some other studies including those of Engerman and Sokoloff (1997, 2005) reveal the historical use of slavery during colonial periods as one of the significant underlying determinants of cross-regional differences in levels of poverty and inequality. Among other things, they proposed that a country’s or a region’s socio-economic wealth may be explained or justified by their history. In their understanding, several colonies (most of them if not all belonging to the developing world) were seen as potentials for growing certain crops due to their climate and natural conditions, and were therefore used to generate rental for their colonisers (Western European countries). As long as these conditions were met, rentals were established and human exploitation through the extensive use of slavery was observed. This past reality may explain the persistence of poverty and income inequality in regions such as Sub-Saharan Africa, South Asia, Latin America and in the Caribbean. Empirically, among other studies, the work by Soares, Assunção and Goulart (2012) is indicative. The work assesses whether levels of income inequality correlate with the historical use of slavery. The findings suggest that in a situation where no form of slavery existed, the actual income inequality level would lessen by 10 Gini points. However, in such a reasoning, one should conclude that the persistence of inequality and extreme poverty may be partly due to the historical exploitation of slavery by western countries during the colonial period.. 2.2.2. The debt crisis and the effects of structural adjustment programs With reference to the question of why absolute poverty and inequality tend to have persisted, other studies such as that of Easterly (2003), advance the reason of the third world’s debt crisis. Easterly (2003) emphasises the event of the structural adjustment programs as defined by the Bretton Woods institutions (IMF and the World Bank) as one of the major causes. One of the most influential and leading development theories and models of the 20th century is given by Rostow (1960). The model is known as the Rostow’s Stages of Economic Growth. This model suggests that poor countries may 7.

(19) reach high levels of development through the “catching up” process. In Rostow’s understanding, the catching-up process includes the third-worlds’ economic industrialisation, which may later produce high economic growth and increase the standard of living levels. Poor countries (specifically those of Latin America and Africa), most of which gained independence in 1950-1960, adopted the former model to overcome their low level of industrialisation. Most of them, if is not all, decided to finance their industries through foreign debt. However, the collapse of commodity prices in 1972-1976, the increase of the lending interest rates, portfolio mismanagement as well as other economic and political factors, exacerbated their domestic fiscal situations, and the fiscal deterioration created spillover effects on their balance of payments. Moreover, Easterly (2003) notices that an important fraction of the contracted loans was affected by unproductive white elephant investments such as militarisation. Overall, this situation constrained poor countries from refinancing their maturing debt with new loans, which later created a vicious circle debt crisis, even though the IMF and the World Bank had established some key conditions for the refinancing of debt. These included the liberalisation of the economy, minimisation of the role of the state in the economy, economic privatisation measures, while reduced protection of local industry were encouraged. Several other macro-economic measures such as increased interest rates, currency devaluation, labour market flexibility and reduced regulation standards were also adopted as part of the conditions. The debts crisis erupted from exponential increases in external debt compared to the countries’ debt servicing capacities. The crisis occurred at end 1970 early 1980, when countries like Mexico and Argentina refused to guarantee their debt servicing. According to the IMF and the World Bank, the structural adjustment programs (SAPs), also known as the “Washington Consensus”, appeared in 1986 to be the “royal” therapy for the debt crisis. The outcomes of its application were unfortunately devastating. This process is often blamed for the entrenched and persistent poverty levels that followed these programs.. 2.2.3. Geographic, dependency and structuralism theories Sachs et al., (2004) explains how Sub-Saharan Africa regions are caught in the poverty trap. Geographical location is advanced as one of the causes. Sachs et al., (2004) demonstrates by advancing five reasons that make Sub-Saharan Africa the most vulnerable region in terms of the persistence of extreme poverty. The first reason is that the region has a high disease burden. This view relies on some prominent statistics that indicate how Africa’s disease burden is unique in its harshness compared to other world regions. According to the 2017 data from the Joint United Nation Program 8.

(20) on HIV/AIDS (UNAIDS), 25.5 million people in Africa (excluding North Africa) are living with HIV/AIDS. This number is compared to 2.1 million infected people in West and Central Europe and North America, and the 2.1 million infected people in Latin America and the Caribbean. However, an additional element is that many African countries have tropical climates. This exposes them to various endemic tropical diseases such as malaria. According to the 2016 World Health Organisation Report, although the number of malaria deaths had decreased for all regions, Africa remains the highest region in terms of death caused by malaria. The number of deaths in 2015 is estimated to 395 000 against 500 for the Americas and 3 200 for the Western Pacific region. Sachs et al., (2004) concludes that Africa’s malaria crisis and other disease burdens are evidence of its poverty and the poor quality of its institutions, rather than being the profound cause. The second reason is identified as high transport costs and small market size. Sachs et al., (2004) demonstrates that the transport costs of moving goods from their place of production to main markets is often high in Africa. This is due to the fact that most Africans live in landlocked rural areas. However, this issue of isolation is often linked to small market size, where countries with less access to global trade are found to grow slowly compared to countries with larger markets. The third reason is the poor productivity of the agricultural sector. Excessive rainfall and high temperatures in some countries subject the land to high rates of evapotranspiration. This, and the high transport costs constrain African farmers from being able to afford enough fertilizer to enhance crop productivity. In addition to these three reasons, the argument of adverse geopolitics is also given. Despite the historical past as mentioned previously, African countries have suffered the dominance of the European power for almost five centuries, and that of Arab powers for more than a century. Actual poverty levels are also seen as the legacy of poor infrastructure and low education levels which prevail in postcolonial Africa compared to the postcolonial levels in Asia. The last reason is the support of dictatorships after independence by the west. It is evident that actual poverty in Africa is also exacerbated by corruption and authoritarian rule implemented by those dictatorial systems. In the other hand, the natural resources dependence theories are cited to explain why poverty and inequality in the developing world tend to persist. The former theory builds on the idea that oil and mineral abundances creates growth-restricting forms of government intervention. The government interventions lead to large degree of rent-seeking, portfolio mismanagement and corruption, which are generally found to negatively correlate with the developmental outcomes they produce. Such a phenomenon is known as “Dutch disease”, in reference to observations made in the United Kingdom 9.

(21) and the Netherlands relating to the negative effects of the North Sea oil exploitation on deindustrialisation and employment. In addition, structuralism theories as supported by the PrebischSinger hypothesis, which advocates the deterioration of terms of trade in developing countries as major reason for low levels of development in the developing world. Prebisch (1950) demonstrates the deterioration of terms of trade in the developing world by cutting down the relative prices of raw commodities compared to manufactures. As a solution, he then suggests the adoption of importsubstitution policies to break the cycle of low economic performance and thus achieve extreme poverty reduction in developing countries.. 2.2.4. Income inequality and poverty effects of globalisation Recent research conducted on the benefit of trade integrations across countries or regions demonstrates that, despite its positive impact on economic growth, trade integration has exacerbated income disparities and poverty in several developing countries. Thorbecke (2013) borrowed the socalled Bourguignon (2004) poverty-growth-inequality (PGI) triangle to explain the mechanisms through which trade integration directly or indirectly impacts poverty. Thorbecke (2013) demonstrates that in such a process, the most significant impact of those mechanisms transits through the growthinequality channels. Figure 1 schematically reproduces the causation links between trade integration and poverty, starting from trade integration (globalisation) to poverty.. Economic growth Globalisation. Trade openness Capital, Labour, Technology. Trade integration. Poverty. Income inequality. Technology Figure 1: Poverty effects of trade integration via growth and distributional channels Source: Thorbecke (2013).. Figure 1 shows two channels through which trade openness mechanisms affect poverty. The first transits via the economic growth channel. This is, for instance, the positive impact of globalisation in enhancing economic growth. It is noted that the double causation links between trade openness and 10.

(22) economic growth are still under debate. However, a consensual view seems to be emerging, indicating a unidirectional causation running from trade openness to economic growth. In such a context however, the growth-boosting impacts of trade openness rely on the way and the extent to which a region or a country is integrated into the global market. The second channel is by way of the income distribution channel. A large body of research on the growth impacts of trade openness shows how international trade and globalisation mechanisms exacerbate income inequality in less developed countries. This research includes that of Asadullah and Savoia (2018). Atkinson, Piketty and Saez (2011) show how technological innovations generated global markets for the top 1 per cent income earners in the USA during the 1980s. In this respect, the Heckcher (1919) and Ohlin (1933) models are often used to explain the effects of trade on wage disparities. Their original versions explain trade relations between countries that have different relative factors endowment such as relative endowments of less educated and educated workers. By considering two countries with two factors of productions (capital and labour) and two tradable goods, the Heckcher and Ohlin models suggest that countries with skilled labour should specialise in producing tradable goods that requires educated labour. In contrast, countries with unskilled labour should specialise in tradable goods that use lesseducated labour. According to Pavcnick (2011), such a trade model increases the wage gap among workers (unskilled and skilled workers). This is due to the fact that in countries with abundant moderately skilled labour (such as the United States), there will be an increase in the call for skilled labour. This situation leads to wage-inequality linked to what is known as “skills premia demand”. On the other hand, in countries with less-educated labour, there will be a relative demand for less-educated labour, which induces a reduction of the wage gap between workers. Another observable link indicated in Figure 1 is the dual causation between economic growth and income inequality. Two main contradictory theoretical opinions are documented (Thorbecke, 2013). First, the classical (traditional) opinion which stresses the growth-boosting impacts of income inequality via the saving-boosting effects as well as the existence of incentives effects and investment opportunities, (Aghion & Bolton, 1997). The second is the opinion of the modern development theories, which relate greater income inequality to reduced economic growth via several constraints. These include: lower investment and greater uncertainty due to social and political instability; activities related to unproductive rent-seeking; increasing insecurity of private property rights; and increasing transaction costs, (Thorbecke, 2013). 11.

(23) Overall, the conclusion made on the impact of globalisation on poverty is that globalisation mechanisms through growth may be in favour of the poor. However, the poverty effect of such an impact may depend on how the fruits of the growth are distributed between individuals, as income inequality appears to be an important filter between growth and poverty reduction (Thorbecke, 2013). 2.3. POVERTY REDUCTION STRATEGIES. 2.3.1. The IMF and World Bank poverty reduction strategies The failure of the SAPs to provide suitable solutions to the poverty reduction agendas in developing countries raised several criticisms against the Bretton Woods institutions’ policies. One of the criticisms formulated in the SAPS is that the former programs were defined as a common way through which every country had to agree to maintain macroeconomic equilibrium and hence, poverty reduction. The SAPs were found to be ignoring countries’ specificities through undermining national capabilities by generating parallel systems. These parallel systems render country-ownership weak by imposing conditionalities to the provision of foreign aid. This situation produced a negative result on poverty reduction goals. In 1999, the IMF decided to launch a poverty reduction strategy paper (PRSP) as a responsive initiative to the growing voice of criticism and challenge. The PRSP is a strategic country-specific document which analyses the causes of poverty and key specific country strategies towards its reduction. This new strategic approach to reducing poverty is a national initiative piloted by governments. It involves national stakeholders as well as international development partners. The PRSP became increasingly important to bi- and multilateral donors of aid, since the document was found to be a means of improving the efficacy as well as the efficiency of development assistance. Unfortunately, most of the PRSP targets were judged by stakeholders to be too broad, specifically in terms of the time frameworks which were supposed to be achieved.. 2.3.2. The Millennium Development Goals and the Sustainable Development Goals The event of the Millennium Development Goals (MDGs) in early 2000 was saluted by several stakeholders around the world due to the core of its ambitious targeting. This is confirmed by the following statement: "I’ve read through dozens of PRSPs and often the targets are much less ambitious than the MDGs" (Jeffrey Sachs, The Earth Institute, Washington DC, May 2003). As mentioned in the late Human Development Report of the United Nations Development Program (UNDP) in 2003, the MDGs were considered more ambitious than the PRSP. Stakeholders’ appreciation of the PRSP targets was due to the fact that, PRSP targets achievements were prescribed by a precise time framework: the late 2015s. On a set of seven goals, three were devoted to halving the 1990 level of poverty by late 2015. However, those goals were generally not achieved, although several poverty 12.

(24) reduction efforts were registered. The universal will of continuing to reduce poverty as expressed by the United Nations Development Program (UNDP), is currently represented by their 2030 agenda on poverty reduction. The 2030 agenda on extreme poverty eradication is known as the UNDP Sustainable Development Goals (SDGs). They build on the MDG achievements, and contain a set of seventeen goals. After reintegrating the former MDG targets, the SDGs’ particularities and innovations reside specifically in the fact that they include new spheres such as peace and justice, sustainable consumption, economic disparities (income and gender inequality), and climate change. 2.4. REGIONAL DIFFERENCES IN MEAN INCOME, INEQUALITY AND POVERTY As demonstrated in Table 1, there was a great deal of regional variation in mean income, inequality, and poverty from 1981 to 2013. Table 1 provides the changes in mean income (in GDP per capita) growth, changes in inequality and poverty for Sub Saharan Africa (SSA); South Asia (SA); the Middle East and North Africa (MENA); Latin America and the Caribbean (LAC); Eastern Europe and Central Asia (ECA); and East Asia and Pacific (EAP). The sample is divided into three periods, the decades of 1981 to 1990; 1991 to 2000, and 2000 to 2013. Table 1: Inter-regional mean income, inequality and poverty trends differences Region SSA SA MENA LAC ECA EAP All regions. Mean income (GDP per capita growth) (1981-1990) (1991-2000) (2001-2013) 0.21 0.29 2.33 3.38 3.40 4.35 0.61 1.50 2.41 −0.36 2.02 2.31 1.50 −0.08 4.91 2.34 2.89 3.60 0.91 1.11 3.27. Inequality (Gini index) (1981-1990) (1991-2000) (2001-2013) 0.05 −0.27 −0.35 0.76 0.39 −0.47 −0.28 −0.26 −0.28 0.05 0.30 −0.79 0.65 1.39 −0.11 0.17 0.06 −0.31 0.24 0.35 −0.37. Poverty (Headcount, $1.9/day) (1981-1990) (1991-2000) (2001-2013) −0.09 −1.36 −2.58 −3.64 −3.64 −15.96 −0.26 −1.74 −11.67 2.41 −2.30 −7.42 2.60 8.19 −14.47 −3.29 −4.85 −12.12 0.48 0.38 −8.97. Notes: The table displays the calculated regional average in mean income (in GDP per capita), Gini index and Headcount rate, (in percentages changes). Source: Computed by the author using data from the World Bank PovCalNet dataset.. According to the results of Table 1, the developing world regions as a whole experienced considerable income growth during the sub-period 2001-2013, with a modest decline in inequality and a significant fall in poverty compared to the sub-periods 1981-1990 and 1991-2000. Region-specific trends are as follows: a) Sub-Saharan Africa’s per capita income rose by 2.33 during 2001-2013 compared to 0.21 and 0.29 in 1981-1990 and 1991-2000 respectively. The latter period corresponds with a slight fall in inequality and considerable poverty reduction of about 22.7 times more in 2001-2013 compared to its 1981-1990 levels. However, compared to other regions, SSA has lower levels of poverty reduction. b) South Asia (SA) registered considerable per capita income growth during all three periods. Though the period corresponds with a relatively mild reduction in inequality, the ensued growth translated into 13.

(25) a significantly high reduction in poverty level. Its poverty reduction figures are the highest among all the regions. The sample does not include India. The figures rates may slow somewhat with the inclusion of India, however, progress will still remain impressive. c) The Middle East and North Africa (MENA) experienced some economic growth during the period 2001-2013. The region also registered a modest inequality reduction and a higher poverty reducing trend in the same period compared to 1981-1990 and 1991-2000. d) Growth in the Latin America and the Caribbean (LAC) region for the period 2001-2013 was on par with SSA, however, because of a very high reduction in inequality, poverty fell by up to 7.42 points compared to only 2.58 in SSA, with similar levels of economic growth. e) Eastern Europe and Central Asia (ECA) experienced the highest growth relative to all the other regions in the period 2001-2013, with a modest inequality reduction. This high growth resulted in the second-highest fall in poverty, of 14.47 points. f) Finally, East Asia and Pacific recorded a relatively high-income growth, with proportionate inequality reduction during the last time interval compared to both first sub-periods. This growth brought about a significantly high and increasingly consistent poverty reduction for all the sub-periods. This trends in all the three variables for the region, and can be explained by the Chinese success story, due to its influence in the region. Overall, we can classify the regions into low growth, modest inequality reduction, and low poverty reduction (SSA); low growth, low inequality reduction, but high poverty reduction (MENA); low growth, high inequality reduction and high poverty reduction (LAC); high growth, low inequality reduction, but high poverty reduction (ECA); high growth, high inequality reduction, and high poverty reduction (SA) and modest growth, modest inequality reduction, and high poverty reduction (EAP). With such diversity, it is necessary to robustly assess the correct poverty elasticity of the growth in an appropriate framework for regionally customised policy measures. Figures 2, 3 and 4 below present each region’s trend in mean income, Gini index, and poverty rates for the entire time period (1981-2013).. 14.

(26) 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013. GINI INDEX. 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013. MEAN INCOME (IN USD). 450. ECA. 400. 350. 300. 250. LAC. 150. 50. 45. 40. 35. MENA ALL REGIONS. 200. EAP. 100. SSA. SA. Figure 2: Regional trends in mean income (in US Dollars). 55. 50. LAC SSA. ALL REGIONS EAP. SA MENA. 30. ECA. 25. 20. Figure 3: Regional trends in income inequality (Gini index). 15.

(27) 60. SSA 50. POVERTY RATE. EAP 40. SA. 30. 20. 10. ALL REGIONS. LAC MENA. ECA. 0. Figure 4 Regional trends in poverty rates (Headcount rates at $1.9/day) Source: Author’s computation using PovCalNet data. 2.5. CONCLUSION. the debt crisis and the effect of the structural adjustment programs; the geographical location of most of the developing countries; the Dutch disease and the deterioration of the terms of the trade; and the income disparities created by the globalisation mechanisms were shown as the most important historical factors that explain why extreme poverty tends to persist. Secondly, the chapter reviewed different key development strategies that were defined by the Bretton Woods institutions (the IMF and the World Bank) and the UNDP, in order to achieve the common goals of extreme poverty eradication. Thirdly, the global and regional specific trends of poverty starting to the 1981 to 2013 were provided. The results of the regional trends indicated regional diversity. As such, this study aims to identify factors that may explain this regional diversity inherent in the trends of poverty, and thus seeks to interpret it.. 16.

(28) CHAPTER 3. LITERATURE REVIEW OF THE RECENT EMPIRICAL EVIDENCE 3.1. INTRODUCTION This chapter reviews the existing literature on the growth-poverty nexus. It starts by going through the empirical work that emphasises the importance of economic growth in reducing poverty with zero effect of the distributional changes. The following sequence is devoted to other studies that emphasise the role of distributional changes as a filter for the effects of growth on poverty. The chapter ends by reviewing studies that emphasise the constraining effect of higher initial poverty rates in predicting how growth is effective in reducing poverty. 3.2. REVIEW OF THE DEBATE ON THE POVERTY EFFECT OF GROWTH The quest for understanding the growth-poverty nexus has generated considerable interest since early 1990s. Despite the interest, the role played by income inequality and higher poverty rates in predicting the responsiveness of current poverty rates to growth in mean income are still ambiguous and controversial. The existing literature demarcates two different viewpoints that have emerged over the years. The first, exemplified by Dollar and Kraay (2002) demonstrates that growth is good for the poor. This view upholds the conclusion that inter-country or inter-regional differences in poverty reduction experiences may be largely, if not totally, attributed to differences in changes in mean income, with little or no role for distributional changes. The Dollar and Kraay (2002) approach to the analysis of the growth-poverty nexus is based on linear models, where the change in poverty is subject to the change in mean income, and a host of other explanatory variables. The focus is on determining whether there is a connection between the average income and the income of the poorest quintile. The results obtained failed to reject the null hypothesis that changes in mean income explain almost all changes in the incomes of poor people. In the same vein, Ravallion and Chen (1997) tested the relationship using the panel data of 67 developing countries covering the period 1981-1994, with a pooled OLS technique on the standard growth-poverty model. The findings suggested that changes in income inequality are uncorrelated with changes in poverty. Some criticism has been raised against the above conclusion. For instance, Ravallion (2005) suggests that the lack of distributional influence on poverty may be due to insufficient variability in inequality and might be based on two factors. One is the limitation of data availability, and the other relates to the measurement of inequality in previous literature, as using relative rather than absolute measures of inequality may yield different outcomes. This is obvious, as the latter measure is more closely linked 17.

(29) to people living under the poverty line than the former. Moreover, Ravallion (2003) sheds more light on the measurement issue of inequality as often used empirically. He shows that in developing countries, growth in mean income tends to be accompanied by consistent absolute disparities within socioeconomic groups. Arguably, absolute changes in inequality should be more efficient than relative changes in predicting poverty changes. The second viewpoint is based on more recent studies with better data. This view supports the significant role of inequality on poverty responsiveness to growth in mean income. Key studies of this view include Ravallion, and Huppi (1991), Kakwani (1993), Easterly (2000), Epaulard and Pommeret (2003), Bourguignon (2003), Adams (2004), Kalwij and Verschoor (2007) and Fosu (2010, 2015, 2017). The methodological procedure used by most of these researchers shares common features such as the use of interaction models that allow for the assessment of the roles of both mean income and inequality on poverty. For instance, Easterly (2000) assessed the effect of the Bretton Woods institution agendas on poverty reduction by specifying an econometric model in which growth is interacted with inequality. He found that the effect of the agendas was boosted by a lower level of inequality. Similarly, Bourguignon (2003) looks at the same relationship at regional level using nationally representative household surveys for 50 countries, covering 1981-1998. Within the popular growth-poverty identity model, he applied a two-step GMM technique and found that a higher initial level of inequality and a higher ratio poverty line over mean income (both known in the literature as distributional effects) were dampening the effects of growth on poverty. Bourguignon (2003) argues that countries or regions with higher initial inequality and initial mean income closer to the poverty line, experience lower responsiveness of poverty to changes in mean income. Bourguignon’s evidence has been supported, first by Besley and Burgess (2003), later by Kalwij and Verschoor (2007), and more recently by Fosu (2017). Their findings show that both absolute income and inequality elasticities of poverty decrease with the initial inequality and the ratio of poverty line over mean income. They suggest that it is crucial to consider these two elements together to best understand the growth-poverty nexus. Another relatively insignificant strand of literature consists of those who consider the role of initial poverty rates in addition to the effect of inequality. This aspect was first anticipated by Easterly (2009). With specific reference to the Sub-Saharan Africa region, he argues that for their higher poverty rates, higher and sustained growth rates are required to reach the same equivalent rate of poverty alleviation (when referring to the late MDGs of halving the proportion of the 1990 poverty rate in 2015). 18.

(30) Unfortunately, his thinking never evolved into any empirical evidence until Ravallion (2012) provided a supportive illustration. Ravallion (2012) suggests that a higher initial level of poverty might be the most binding constraint of the poverty effect of growth in mean income than other initial conditions such as initial mean income or initial inequality levels. He supports his claim by relying on the predictions of convergence, which, when applied to poverty, conclude that poorer countries should tend to grow faster than developed countries and that in the long run, such economic development will translate into significant poverty reduction. By testing the role of the initial level of poverty in an interacted model, he identifies higher initial poverty rates as the main constraint to the process. His elasticity with respect to the initial level of poverty is 2, while an absolute mean income elasticity is -2.5. However, a key gap in his methodological approach is the fact that it fails to accommodate initial inequality and initial poverty, which both interacted respectively with the change in mean income and the change in inequality. These terms are important in distinguishing the residual role of inequality once initial poverty is controlled for. Asadullah and Savoia (2018) used a panel data of 89 developing countries and applied ordinary and iteratively reweighted least square techniques to assess whether adoption of global MDGs by lowincome countries facilitates and explains convergence in reducing poverty. Contrary to Ravallion (2012), their findings showed that countries with higher initial poverty rates tended to experience faster poverty reduction. They argue that the trend differences in poverty reduction across countries is explained by the state’s capacity or ability to manage their territory. Once again, their methodology considers the initial mean income and initial poverty level but fails to control for initial inequality as one of the key initial conditions that may also explain countries’ diversity in reducing poverty. We argue that all these must be controlled in a single framework in order to identify the truly binding constraints and correctly isolate the true elasticities. Following the above discussion, this study stands halfway between the two last viewpoints and methodological approaches. It originality resides in it capabilities to provide a new comprehensive methodology that is less challenging in explaining the regional trend differences in reducing poverty. This new methodology relies on the premise of the functional approximations of the identity model as developed by Bourguignon (2003), such as the income or consumption expenditure that is lognormally distributed.. 19.

(31) 3.3. CONCLUSION The literature on the growth-poverty nexus is not exhaustive. The existing literature demarcates two different viewpoints that have emerged over the years. The first, represented by Dollar and Kraay (2002) supports the argument and the conclusion that inter-country or inter-regional differences in poverty alleviation achievement may be largely, if not totally, attributed to differences in changes in mean income only, with little or no role for distributional changes. The second view supports the significant role of inequality on poverty responsiveness to growth in mean income and concludes that the level of inequality determines the speed at which poverty responds to changes in mean income and therefore regional differences. We also reviewed another relatively insignificant strand of the literature that relates to those who consider the role of initial poverty rates in addition to the effect of inequality. This up-to-date literature is centred on Ravallion’s (2012) work, which concludes that a higher initial level of poverty might be the most binding constraint of the poverty effect of growth in mean income than other initial conditions, and explains why countries with lower poverty rates are most successful in reducing absolute poverty.. 20.

(32) CHAPTER 4. METHODOLOGY, DATA AND ESTIMATION TECHNIQUES 4.1. INTRODUCTION This chapter provides the methodological frameworks on which the analysis of the growth-poverty nexus relates. The first section presents the model specifications. These include the standard growthpoverty model, the growth-poverty identity model, and the autoregressive growth-poverty model, which was developed by this work. Section 2 discusses different estimation techniques that can be used to estimate such kinds of specifications (with specific reference to the autoregressive model). It also discusses the choice of the use of the two-step system GMM estimators over other econometric techniques, such as the difference GMM and the 2SLS estimators. Finally, section 3 presents and discusses the data employed in this study. It also presents the variables maintained in the analysis. 4.2. METHODOLOGICAL APPROACH. 4.2.1. Model specification The starting point in modelling the growth-poverty nexus was adopted from Bourguignon (2003). In the fundamental framework, the logarithm of poverty is a function of the logarithm of the growth in mean income taken as a proxy for economic growth, and the logarithm of the Gini coefficient taken as a proxy for the income distribution. This can be formalised as follows: 𝑙𝑛𝑝𝑖𝑡 = 𝐶𝑡 + 𝑏1 𝑙𝑛𝑚𝑖𝑛𝑐𝑖𝑡 + 𝑏2 𝑙𝑛𝐺𝑖𝑛𝑖𝑖𝑡 + 𝜔𝑖 + 𝜀𝑖𝑡. (1). Where 𝑙𝑛𝑝𝑖𝑡 is the logarithm of any Forster-Greer and Thorbecke (1984) family of poverty measures, 𝐶𝑡 is the time-constant region-specific trend, 𝑙𝑛𝑚𝑖𝑛𝑐𝑖𝑡 is the logarithm of the mean income, 𝑙𝑛𝐺𝑖𝑡 is the logarithm of the inequality index, 𝜔𝑖 is the region’s unobserved heterogeneous fixed effect, the 𝑏𝑗 are parameters to be estimated and 𝜀𝑖𝑡 is the idiosyncratic error term. As written, Equation (1) is expressed in natural logarithms in order to minimise the outliers and facilitate easy interpretations to straightforward elasticities. By differentiating the equation (1) to eliminate the region’s individual fixed effect bias and by allowing the time-constant region-specific trend, we get the following standard growth-poverty model: ∆𝑙𝑛𝑝𝑖𝑡 = 𝐶𝑡 + 𝑏1 ∆𝑙𝑛𝑚𝑖𝑛𝑐𝑖𝑡 + 𝑏2 ∆𝑙𝑛𝐺𝑖𝑛𝑖𝑖𝑡 + ∆𝜀𝑖𝑡. (2). Where ∆𝑙𝑛𝑝 is the poverty growth rate, ∆𝑙𝑛𝑚𝑖𝑛𝑐𝑖𝑡 is the mean income growth rate, ∆𝑙𝑛𝐺𝑖𝑛𝑖𝑖𝑡 is the inequality growth rate, the 𝑏𝑗 are the absolute growth and inequality elasticities of poverty and ∆𝜀𝑖𝑡 is 21.

(33) the idiosyncratic error term. However, the impact of growth in mean income on poverty can be assessed using Equation (2) following Besley and Burgess (2003), and Kalwij and Verschoor (2007), with and/or without including the income distribution component. In doing so, the estimates will only be considered as empirical poverty elasticities, which are linked to the actual changes in the Lorenzo curve, rather than being the true poverty elasticities. From Equation (2), the income and inequality elasticity of poverty can be determined as follows: . Income elasticity of poverty 𝜕∆𝑙𝑛𝑝. 𝑖𝑡 𝜀𝑚𝑖𝑛𝑐 = 𝜕∆𝑙𝑛𝑚𝑖𝑛𝑐 = 𝑏1 𝑖𝑡. . (2a). Inequality elasticity of poverty. 𝜀𝑔𝑖𝑛𝑖 =. 𝜕∆𝑙𝑛𝑝𝑖𝑡 𝜕∆𝑙𝑛𝑔𝑖𝑛𝑖𝑖𝑡. = 𝑏2. (2b). Furthermore, most recent evidence, including that of Fosu (2015, 2017), prefer the growth-poverty identity model instead of the standard growth-poverty model. The reason behind such preference is its ability to include the initial level of inequality (𝐺𝑖𝑛𝑖𝑖𝑡−1) and the ratio poverty line over the mean income (𝑍/𝑚𝑖𝑛𝑐𝑖𝑡 ) as the extent to which the change in mean income and the change in inequality are effective in reducing poverty. Ravallion (1997) also supports the importance of this inclusion in modelling the growth-poverty nexus. He argues that a high inequality level muffles the impact of growth on poverty. Equation (2) is extended to incorporate this consideration and also includes different interaction terms involving growth and inequality respectively, with the initial inequality and the ratio poverty line over the mean income. This extension gives the empirical evidence used by Bourguignon (2003), Kalwij and Verschoor (2007) and Fosu (2015, 2017) as follows: ∆𝑙𝑛𝑝𝑖𝑡 = 𝐶𝑡 +𝑏1 ∆𝑙𝑛𝑚𝑖𝑛𝑐𝑖𝑡 +𝑏2 ∆𝑙𝑛𝑚𝑖𝑛𝑐𝑖𝑡 𝐺𝑖𝑛𝑖𝑖𝑡−1 +𝑏3 ∆𝑙𝑛𝑚𝑖𝑛𝑐𝑖𝑡 ln𝑍/𝑚𝑖𝑛𝑐𝑖𝑡 )+𝑏4 ∆𝑙𝑛𝐺𝑖𝑛𝑖𝑖𝑡 +𝑏5 ∆𝑙𝑛𝐺𝑖𝑛𝑖𝑖𝑡 𝐺𝑖𝑡−1 + 𝑏6 ∆𝑙𝑛𝐺𝑖𝑛𝑖𝑖𝑡 ln𝑍/𝑚𝑖𝑛𝑐𝑖𝑡 )+𝐺𝑖𝑡−1 + ln𝑍/𝑚𝑖𝑛𝑐𝑖𝑡 +∆𝜀𝑖𝑡. (3). From this equation (3), the growth and inequality elasticities of poverty can be computed as follows: . Income elasticity of poverty 𝜕∆𝑙𝑛𝑝. 𝑖𝑡 𝜀𝑚𝑖𝑛𝑐 = 𝜕∆𝑙𝑛𝑚𝑖𝑛𝑐 = 𝑏1 + 𝑏2 𝑙𝑛𝑔𝑖𝑛𝑖𝑖𝑡−1+𝑏3 ln𝑍/𝑚𝑖𝑛𝑐𝑖𝑡 ) 𝑖𝑡. . (3a). Inequality elasticity of poverty 𝜕∆𝑙𝑛𝑝. 𝜀𝑔𝑖𝑛𝑖 = 𝜕∆𝑙𝑛𝑔𝑖𝑛𝑖𝑖𝑡 = 𝑏4 + 𝑏5 𝑙𝑛𝑔𝑖𝑛𝑖𝑖𝑡−1 + 𝑏6 (ln𝑍/𝑚𝑖𝑛𝑐𝑖𝑡 ) 𝑖𝑡. (3b). However, these elasticities in Equations (3a) and (3b) appear to be incomplete since the growth-poverty identity model does not account for an important stylised fact, which is the initial level of poverty. 22.

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