Growth,inequality, and poverty reduction in developing countries: Recent global evidence

The study presents comparative global evidence on the transformation of economic growth to poverty reduction in developing countries, with emphasis on the role of income inequality. The focus is on the period since the early-mid-1990s when growth in these countries as a group has been relatively strong, surpassing that of the advanced economies. Both regional and country-specific data are analyzed for the $1.25 and $2.50-level poverty headcount ratios using World Bank Povcalnet data. The study finds that on average income growth has been the major driving force behind both the declines and increases in poverty. The study, however, documents substantial regional and country differences that are masked by this ‘average’ dominant-growth story. While in the majority of countries, growth was the major factor behind falling or increasing poverty, inequality, nevertheless, played the crucial role in poverty behavior in a large number of countries. And, even in those countries where growth has been the main driver of poverty-reduction, further progress could have occurred under relatively favorable income distribution. For more efficient policymaking, therefore, idiosyncratic attributes of countries should be emphasized. In general, high initial levels of inequality limit the effectiveness of growth in reducing poverty while growing inequality increases poverty directly for a given level of growth. It would seem judicious, therefore, to accord special attention to reducing inequality in certain countries where income distribution is especially unfavorable. Unfortunately, the present study also points to the limited effects of growth and inequality-reducing policies in low-income countries.     

Bivariate income distributions for assessing inequality and poverty under dependent samples

As indicators of social welfare, the incidence of inequality and poverty is of ongoing concern to policy makers and researchers alike. Of particular interest are the changes in inequality and poverty over time, which are typically assessed through the estimation of income distributions. From this, income inequality and poverty measures, along with their differences and standard errors, can be derived and compared. With panel data becoming more frequently used to make such comparisons, traditional methods which treat income distributions from different years independently and estimate them on a univariate basis, fail to capture the dependence inherent in a sample taken from a panel study. Consequently, parameter estimates are likely to be less efficient, and the standard errors for between-year differences in various inequality and poverty measures will be incorrect. This paper addresses the issue of sample dependence by suggesting a number of bivariate distributions, with Singh–Maddala or Dagum marginals, for a partially dependent sample of household income for two years. Specifically, the distributions considered are the bivariate Singh–Maddala distribution, proposed by Takahasi (1965), and bivariate distributions belonging to the copula class of multivariate distributions, which are an increasingly popular approach to modelling joint distributions. Each bivariate income distribution is estimated via full information maximum likelihood using data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey for 2001 and 2005. Parameter estimates for each bivariate income distribution are used to obtain values for mean income and modal income, the Gini inequality coefficient and the headcount ratio poverty measure, along with their differences, enabling the assessment of changes in such measures over time. In addition, the standard errors of each summary measure and their differences, which are of particular interest in this analysis, are calculated using the delta method.     

A SYNTHESIS OF POVERTY LINE DEFINITIONS*

A fundamental point of discussion in poverty research is whether poverty is an absolute or a relative concept. If poverty is seen to be a situation of absolute deprivation, a poverty line will usually be defined to be independent of the general style of living in society. If poverty is considered to be a situation of relative deprivation, a poverty line will be defined in relation to the general style of living in society. The choice for one of these two approaches has important consequences for social policy, as absolute poverty may be reduced by economic growth, while relative poverty will only decrease when income inequality decreases. This paper suggests a poverty line definition that is not a priori meant to be either absolute or relative, but depends on the perception of poverty in society. If the poverty line is higher in countries with higher median income (as an indicator of “general style of living”) the poverty line is said to be relative; if the poverty line does not vary with median income, it is said to be absolute. The poverty line definition suggested appears to be a generalization of almost all well-known poverty line definitions. Poverty lines thus defined are estimated for eight European countries on the basis of a 1979 survey. The resulting lines appear to have an elasticity with respect to median income of 0.51, and hence can be said to be halfway on the scale between absolute and relative.     

GROWTH, POVERTY, AND INEQUALITY IN LATIN AMERICA: A CAUSAL ANALYSIS, 1970–94

Taking advantage of consistent poverty and income inequality data for 12 Latin American countries between 1970 and 1994, we analyze the determinants of changes in the incidence of urban and rural poverty and in Gini coefficients over spells of years, stressing in particular the role of aggregate income growth. We find that income growth reduces urban and rural poverty but not inequality. We also find that income growth is more effective in reducing urban poverty if the levels of inequality and poverty are lower, and the levels of secondary education higher. We show that there is an asymmetry in the impact of growth on poverty and inequality, with recession having strong negative effects on both poverty and inequality. Since growth does not reduce inequality, economic cycles create ratchet effects on the level of inequality. However, post-structural adjustment growth is quite effective at reducing poverty, particularly if inequality is low.     

A NON‐PARAMETRIC MEASURE OF POVERTY ELASTICITY

We estimate the growth elasticity of poverty (GEP) using recently developed non‐parametric panel methods and the most up‐to‐date and extensive poverty data from the World Bank, which exceeds 500 observations in size and represents more than 96 percent of the developing world's population. Unlike previous studies which rely on parametric models, we employ a non‐parametric approach which captures the non‐linearity in the relationship between growth, inequality, and poverty. We find that the growth elasticity of poverty is higher for countries with fairly equal income distributions, and declines in nations with greater income disparities. Moreover, when controlling for differences in estimation technique, we find that the reported values of the GEP in the literature (based on the World Bank's now‐defunct 1993‐PPP based poverty data) are systematically larger in magnitude than estimates based on the latest 2005‐PPP based data.     

Short-term trends in China’s income inequality and poverty: evidence from a longitudinal household survey

In the past three decades, income inequality in China has increased rapidly relative to both China’s own past and other countries at similar levels of economic development. Using recent longitudinal data from the China Family Panel Studies (CFPS), this article examines changes in income inequality and poverty prevalence between 2010 and 2012. Surprisingly, we find a modest decline in income inequality as measured by the Gini coefficients in the CFPS data. The urban–rural gap narrowed, with rural families enjoying faster income growth than urban families enjoyed. Income growth was greater for middle-income families than for families with either high or low incomes in 2010. By all measures, poverty was greatly reduced between 2010 and 2012. Two-thirds of families that had been poor in 2010 escaped poverty by 2012.     

Decomposing the changes in poverty: Poverty line and distributional effects

When measuring poverty in developed countries, the poverty line used to identify the poor is usually relative and set as a percentage of the median (or of the mean) of the total income. In consequence, when poverty is analyzed over a period of time, changes in the poverty level depend on the impact of evolving standards. To eliminate this effect, sometimes, an anchored poverty line is used. Furthermore, changes in the mean of the distribution and in the inequality among the poor may also affect the poverty levels. This note proposes a decomposition of the changes in poverty as the sum of four terms. The first two reflect the impact in poverty of changes in living standards and the other two measure the effect of the distributional growth and redistribution. This decomposition will help policymakers in the implementation of a more specific antipoverty agenda. An application with data from the European Union Survey on Income and Living Conditions shows the potential of the decomposition proposed.     

The effects of fragility and financial inequalities on inclusive growth in African countries

Africa has the largest number and proportion of fragile states in the world. Fragile states are characterized by slower economic growth, higher incidences of poverty, and persistent inequality. Thus, there is a circular relationship between fragility, inequality, and slow economic growth. This study examines the relationship between fragility, financial inequalities, and inclusive growth in African countries. We introduce a novel way of examining inclusive growth in African countries by developing a unified measure of inclusive growth that captures the two dimensions of inclusive growth: income growth and income distribution. This enables us to adequately assess not just increased opportunities arising from economic growth, but also see how those new opportunities are distributed across all segments of the population. We captured the fragile status of African countries by using an index of fragility. We measured financial inequalities using new data on financial inclusion. The data analysis suggested negative relationships between fragility and inclusive growth in African countries. In addition, the results suggest positive relationships between financial inclusion and inclusive growth. Thus, inclusive growth can be fostered through policies that reduce financial inequalities. Therefore, a less fragile environment is conducive to inclusive growth both directly and indirectly through financial inclusion.     

The Pro‐Poorness,Growth and Inequality Nexus: Some Findings From a Simulation Study

An income growth pattern is pro‐poor if it reduces a (chosen) measure of poverty by more than if all incomes were growing equiproportionately. Inequality reduction is not sufficient for pro‐poorness. In this paper, we explore the nexus between pro‐poorness, growth, and inequality in some detail using simulations involving the displaced lognormal, Singh–Maddala, and Dagum distributions. For empirically relevant parameter estimates, distributional change preserving the functional form of each of these three‐parameter distributions is often either pro‐poor and inequality reducing, or pro‐rich and inequality exacerbating, but it is also possible for pro‐rich growth to be inequality reducing. There is some capacity for each of these distributions to show trickle effects (weak pro‐richness) along with inequality‐reducing growth, but virtually no possibility of pro‐poorness for growth which increases overall inequality. Implications are considered.     

ON THE ESTIMATION OF GROWTH AND INEQUALITY ELASTICITIES OF POVERTY WITH GROUPED DATA

After decades of intensive research dedicated to efficient and flexible parametric statistical distributions, the lognormal distribution still enjoys, despite its empirical weaknesses, widespread popularity in the applied literature related to poverty and inequality analysis. In the present study, we emphasize the drawbacks of this choice for the calculation of the elasticities of poverty. For this purpose, we estimate the growth and inequality elasticities of poverty using 1,132 income distributions, and 15 rival assumptions on the shape of the income distributions. Our results confirm that the lognormal distribution is not appropriate in most cases for the analysis of poverty: the magnitude of the elasticities is generally overestimated and the estimation of the relative impact of growth and redistribution on poverty alleviation is biased in favor of the growth objective.     

Not by growth alone: The role of the distribution of income in regional diversity in poverty reduction

This study examines the role of the distribution of income in determining the responsiveness of poverty to income growth and changes in income inequality using panel data of 58 developing countries for the period 1980-1998. We show that the large cross-regional variation in the capacity of income growth to reduce poverty, i.e. the income elasticity, is largely explained by differences in the initial distribution of income and present region and time specific estimates of the income and Gini elasticities of poverty. We find that the income elasticity of poverty in the mid-1990s equals −1.31 on average and ranges from −0.71 for Sub-Saharan Africa to −2.27 for the Middle East and North Africa, and that the Gini elasticity of poverty equals 0.80 on average and ranges from 0.01 in South Asia to 1.73 in Latin America. Furthermore we show that while differing income growth rates account for most of the regional diversity in poverty trends, the additional impact of differences across regions in rates of inequality change and income and inequality elasticities of poverty is almost always significant and far too large to be ignored, most notably so in Eastern Europe and Central Asia.     

The Making of Pro‐Poor Growth

A system of three endogenous equations is used to estimate the determinants of poverty dynamics. The system incorporates: (i) the direct effect of growth and income inequality on poverty, (ii) the feedback effect of poverty on inequality and growth, and (iii) different channels through which economic policies can contribute to poverty reduction. Results suggest that countries tend to move towards one of two possible equilibria. The positive (virtuous) equilibrium is characterized by fast growth, decreasing inequality, and rapid poverty reduction. The negative (vicious) equilibrium involves slow (or even negative) growth, sharpening inequalities, and resilient poverty. The policy mix is critical in determining to which of the two equilibria a country converges.     

All About the Giants: Probing the Influences on World Growth and Income Inequality at the End of the 20th Century

This paper presents estimates of world output growth from 1970to 2000, the distribution of income among countries and personsfor the years 1980, 1990 and 2000, and world income povertyrates for the same years. It also presents the results of aseries of simulation exercises that attempt to isolate the effectof particular country and regional experiences on world outputgrowth and changes in global income inequality and poverty. The authors find that rapid growth in China (despite a downwardadjustment of official growth estimates) had a powerful impacton the growth of world output in both the 1980s and 1990s, butthat negative economic growth in Eastern Europe more than offsetthat effect in the 1990s. With respect to the distribution ofworld income between countries, the impressive growth performancesof the worlds most populous countries, China and India, ensureddecreasing levels of inequality during both the 1980s and 1990s.When the distribution of world income between persons is measured,the equalizing effect of China's rapid growth remains dominantthrough both the 1980s and 1990s, despite the contradictoryimpact of increasing domestic inequality. Only India's influenceremained substantial by comparison. Other identifiable eventsof the period, such as the economic contraction in Eastern Europeand continued economic decline in Africa, had little statisticalimpact. However, when the combined influence of China and India'sabove-average growth rates is removed, or their size effectdampened, the improving global distribution of (inter-countryand inter-personal) income suggested by all statistical measuresbecomes one of sharply worsening inequality. The impact of thesetwo countries is similarly critical with respect to global povertyreduction. (JEL F0, I3, O4)     

Rent-seeking bureaucracies, inequality, and growth

This paper develops a Schumpeterian growth model in which institutional quality matters for inequality and growth. In particular, asymmetric information between political authorities and rent-seeking bureaucratic agencies diverts resources from innovative activities – crucial for development to take off in middle and low income countries – and unnecessarily exacerbates income inequality. The theoretical predictions not only match empirical facts on inequality, institutional quality and growth well documented in the literature, but are easily assessed in two groups of Latin American and African countries, as shown in the final calibration analysis.     

EQUIVALENCE SCALES, WELL-BEING, INEQUALITY, AND POVERTY: SENSITIVITY ESTIMATES ACROSS TEN COUNTRIES USING THE LUXEMBOURG INCOME STUDY (LIS) DATABASE

The Luxembourg Income Study (LIS) database on which this article is based offers researchers exciting new possibilities for international comparisons based on household income microdata. Among the choices the LIS microdata allows a researcher, e.g. income definition, income accounting unit, etc., is the choice of family equivalence scale, a method for estimating economic well-being by adjusting income for measurable differences in need.
The range of potential equivalence scales that can and are being used in the ten LIS countries and elsewhere to adjust incomes for size and related differences in need span a wide spectrum. The purpose of this paper is to review the available equivalence scales and to test the sensitivity of various income inequality and poverty measures to choice of equivalence scale using the LIS database. The results of our analysis indicate that choice of equivalence scale can sometimes systematically affect absolute and relative levels of poverty; and inequality and therefore rankings of countries (or population subgroups within countries). Because of these sensitivities, one must carefully consider summary statements and policy implications derived from cross-national comparisons of poverty and/or inequality.     

The impact of financial development,economic growth,income inequality on poverty: evidence from India

This paper examines the impact of financial development, economic growth and income inequality on poverty in India from 1970 to 2015 by employing the autoregressive distributed lag (ARDL) bounds testing procedure. The findings reveal a robust long-run relationship between financial development, economic growth, inequality and poverty. Results show that financial development and economic growth help in poverty reduction in India, whereas income inequality and inflation aggravate poverty. Empirical evidence of the Granger-causality test supports the presence of unidirectional causality from financial development and economic growth to poverty. Moreover, bidirectional causality exists between inequality and poverty. The present study provides evidence on which the policymakers may proceed with detailed investigation of how specific financial sector policies and interventions can be deployed as effective instruments for achieving favorable economic growth and income distribution. The study recommends that policies geared toward increasing financial development and economic growth should be adopted to reduce the high level of poverty and inequality currently prevailing in India.     

Do inward looking trade policies affect poverty and income inequality? Evidence from Indonesia's recent wave of rising protectionism

Unlike previous studies which often focus on trade liberalisation, this paper examines the impact of protectionism in the form of import tariffs and mineral export taxes on rural and urban poverty and income inequality for the first time. Using a dynamic computable general equilibrium model on Indonesia, mineral export taxes were found to adversely affect urban and rural poverty but income inequality hardly changed as the decline in income in the higher income group is not significantly different to the decline in low income groups. However, if smelters for mineral ore are developed, then there is not only a fall in poverty, more so for the rural than urban, but there is some decline in income inequality. On the other hand, although the current imposed import tariffs do not affect poverty or income inequality, any further increases from the current low average MFN applied rates, will see a rise in rural and urban poverty and income inequality. By and large, any small improvements in the trade balance brought upon by the mineral tax and import tariffs are more than outweighed by the substantial decline in real household consumption expenditure due to falls in employment and wages, thereby leading to a fall in GDP growth.     

收入增长和分配对我国农村减贫的影响-方法、特征与证据

改革开放30年来,在农村居民收入水平快速增长的大背景下,农村减贫进程却表现出明显的波动性和不一致性。基于此,本文在贫困分解的基础上,运用贫困弹性的动态特征,从理论和实证的角度探讨了收入增长和收入分配对贫困减少的影响,解释上述问题。文章发现:(1)人均收入水平越高,贫困越有可能和收入不平等联系在一起;(2)收入不平等越严重的地区,贫困对收入不平等的反应越迟钝;(3)1998年是我国农村反贫困性质发生改变的拐点。文章建议,今后农村反贫困政策的重点应从以促进收入增长的开发式扶贫向以改善收入分配为重点的社会保护式扶贫政策转变。     

POVERTY AND INCOME INEQUALITY IN LATIN AMERICA DURING THE 1980s

On average, poverty and income inequality increased in Latin America during the 1980s. Forty-six percent of the increase in poverty took place in the cities of Brazil alone, though part of this reflects the migration of poor rural inhabitants to urban areas. There is strong evidence that both income inequality and poverty mirrored the economic cycle, rising during recession and falling during recovery. Economies that grew (e.g. Colombia, Costa Rica) performed better with respect to poverty and income inequality than those that stagnated. In particular, countries that failed to stabilize effectively (e.g. Brazil, Peru) experienced substantial increases in poverty. Educational attainment has the greatest correlation with both income inequality and the probability of being poor. From a policy standpoint, there is a clear association between the provision of education, lessening of income inequality, and poverty reduction.     

Poverty growth in Scandinavian countries: A Sen multi-decomposition

We show in this paper that the growth rate of the Sen index is multi-decomposable, that is, decomposable simultaneously by subgroups and income sources. The multi-decomposition of the poverty growth yields respectively: the growth rate of the poverty incidence (poverty rate) decomposed by subgroups, the growth rate of the poverty depth (poverty gap ratios) decomposed by sources and subgroups, and the growth rate of inequality decomposed by sources and subgroups. We demonstrate that the multi-decomposition is not unique. It is mainly dependent on poverty lines defined on the space of income sources. An application to Scandinavian countries shows that poverty lines based on non-correlation between the income sources imply serious risks of underestimation of the contribution levels of the different components of the global poverty growth. The main contribution of our paper is to pay particular attention to the poverty growth and its source components in order to avoid underestimation of poverty growth.