Self‐Assessed Social Position and Poverty

In this article, we use microlevel data extracted from the 2006 Japanese General Social Surveys to analyze the relationships between self‐assessed social position and socioeconomic factors such as income and poverty. We provide the posterior results of the estimation of the Bayesian multivariate ordered probit model and propose an inequality measure for self‐assessed social position on the basis of the posterior results. We call the inequality measure “regret” and show that the distributions of regret differ for people above and below the poverty line.     

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.     

Equity in Poverty Program Evaluations

Poverty‐reducing programs often use indicators other than household income to transfer resources to the poor which has important implications in terms of equity of the program. This paper offers a decomposition methodology to analyze the horizontal and vertical equity components of a redistribution policy for subgroups defined according to policy‐relevant characteristics. Our measures are derived by comparing the cost of inequality in terms of equally distributed equivalent poverty gaps in the pre‐transfer income and post‐transfer income distributions. An application to the poverty‐reducing program Oportunidades in Mexico in 2006 reveals that the use of indicator variables more strongly correlated with pre‐transfer incomes in rural households can improve the redistributive effect while it also points out the difficulties of the program in targeting different levels of support among the poor, both within and between groups.     

A Proposal to Compare Consistently the Inequality Among the Poor

A poverty index should be sensitive to the number of poor people, the extent of the shortfall of the poor, and the inequality among the poor. A difficulty arises when inequality among the poor needs to be assessed. The inequality may be analyzed in terms of either incomes or gaps. Depending on what side we focus on, the inequality level comparisons may be contradictory. This paper proposes a reinterpretation of the inequality component involved in the decompositions of well‐known poverty indices. The alternative indices we introduce measure equally the income and gap inequality among the poor. The comparisons in inequality as measured by these indices are then independent of the viewpoint. An empirical application illustrates the proposal.     

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.     

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.     

Second‐Order Discrimination and Generalized Lorenz Dominance

We propose a definition of second‐order discrimination that does not require the reference distribution to first‐order dominate the comparison one, and allows rankings of discrimination patterns when both the reference and the comparison distributions differ. It involves comparing the probabilities that randomly selected individuals in the reference and comparison distributions belong to subgroups having the same cumulative mean income, yields orderings of distributions equivalent to those from generalized Lorenz dominance, and allows orderings of discrimination patterns, partial or complete, across pairs of distributions. We compare discrimination against U.S. seniors (inter‐distributional inequality between seniors and non‐seniors) by ethnicity.     

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.     

PROGRESSIVITY AND REDISTRIBUTION IN NON‐REVENUE NEUTRAL TAX REFORMS: THE LEVEL AND DISTANCE EFFECTS

Kakwani and Reynolds–Smolensky indices are used in the literature to measure the progressivity and redistributive capacity of taxes. These indices may, however, show some limits when used to make normative assessments about non‐revenue neutral tax reforms. Two approaches have traditionally been taken to overcome this problem. The first of these consists of comparing after‐tax income distributions through generalized Lorenz (concentration) curves. The second approach is based on the decomposition of changes in the Reynolds–Smolensky index into changes in the average tax rate and variations in progressivity. Nonetheless, this decomposition between the average tax rate and progressivity may be further exploited to obtain some information that can be relevant to assess tax reforms. The main aim of this study is to draw up some indicators that can be useful to quantify the effects of non‐revenue neutral tax reforms. These indicators are used to investigate the last personal income tax reforms that have taken place in Spain.     

Channels of redistribution: Inequality and poverty in the Russian transition

Contrary to popular perception, Russia entered the transition with significant inequality. Using the large Russian Longitudinal Monitoring Survey dataset, we demonstrate that inequality has subsequently risen yet further and by end-1996 was roughly comparable to inequality in Mexico, Colombia or Malaysia. Driving this increase has been not only wealth transfers through privatization but also changes in government expenditure and a sharp growth in earnings dispersion. There has been a large, associated shift in the structure of income. The paper also looks at the incidence and depth of poverty over the period 1992-96. At the start of transition, roughly half the population of households fell below the poverty line. While this has subsequently declined, at end-1996 nearly 40 per cent of households were below the poverty line and a substantial stratum of households were locked in chronic poverty.     

Poverty decompositions with counterfactual income and inequality dynamics

Traditional poverty accounting decomposes changes in a country's poverty headcount ratio into changes in income and inequality. We argue that this approach is unsatisfactory from the perspective of policy analysis because it compares a country in two points of time without taking the country's initial situation, and hence its potential for poverty reduction, into account. We thus suggest comparing traditional poverty decompositions with a counterfactual situation. This counterfactual indicates what a country starting from its initial situation could be expected to achieve in terms of income, inequality, and, hence, poverty developments. We construct those counterfactuals by modeling income and inequality trends characterized by convergence and a “Kuznets” relationship between inequality and development. Parameters in those relationships are estimated using PovcalNet survey data from 144 countries and we construct our counterfactual poverty predictions for 71 developing countries. While there is overall a tight relationship between actual developments and counterfactuals, we identify several cases, where both deviate from each other and discuss the policy implications. We also check for commonalities in differently performing countries and find that those who fell particularly short of expectations often underwent political transition and state fragility.     

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.     

Multidimensional Inequality Across Three Developed Countries

This paper produces comparable estimates of multidimensional inequality for the U.S., Germany, and Australia. Two alternative approaches with differing interpretations are employed. The first method projects all facets of welfare onto a single variable which is then analyzed using standard univariate techniques. The second approach establishes equivalent‐income distributions that would lead to an equalization of welfare, such that the difference between this counterfactual and the true income distribution can be measured. This difference is then interpreted as the degree of income redistribution required to offset welfare inequality. Using data on permanent incomes, health scores, years of education, and leisure times, we observe much higher levels of inequality in the U.S. than in Germany or Australia. Our results are highly statistically significant and hold over a large variety of weighting specifications.     

CONTRADICTORY TRENDS IN GLOBAL INCOME INEQUALITY: A TALE OF TWO BIASES

Did global income inequality rise or fall over the last decades of the twentieth century? The answer depends on how cross‐country income comparisons are made. Exchange rate comparisons suggest that inequality rose whilst the purchasing power comparisons of the Penn World Table suggest it fell. We show that both measures of real incomes lead to biased international income comparisons. Exchange rate comparisons ignore the relative price of non‐tradables, whilst the fixed price method underlying the Penn World Table is subject to substitution bias. The contradictory trends are due to growing dissimilarity between national price structures increasing the degree of bias in each method. When we correct the income data to eliminate bias we find no compelling evidence of a significant change in world inequality.     

Africa is on time

We present evidence that the recent African growth renaissance has reached Africa’s poor. Using survey data on African income distributions and national accounts GDP, we estimate income distributions, poverty rates, and inequality indices for African countries for the period 1990–2011. We show that: (1) African poverty is falling rapidly; (2) the African countries for which good inequality data exists are set to reach the Millennium Development Goal (MDG) poverty target on time. The entire continent except for the Democratic Republic of Congo (DRC) will reach the MDG in 2014, one year in advance, and adding the DRC will delay the MDG until 2018; (3) the growth spurt that began in 1995, if anything, decreased African income inequality instead of increasing it; (4) African poverty reduction is remarkably general: it cannot be explained by a large country, or even by a single set of countries possessing some beneficial geographical or historical characteristic. All classes of countries, including those with disadvantageous geography and history, experience reductions in poverty. In particular, poverty fell for both landlocked as well as coastal countries; for mineral-rich as well as mineral-poor countries; for countries with favorable or with unfavorable agriculture; for countries regardless of colonial origin; and for countries with below- or above-median slave exports per capita during the African slave trade.     

A Consistent Poverty Approach to Assessing the Sensitivity of Income Poverty Measures and Trends

This paper examines the sensitivity of estimates of income poverty rates and trends to variations in the poverty line and to whether or not certain households are included or excluded from the sample used to estimate poverty. The approach draws on the concept of consistent poverty, which has been used to identify those with incomes below the poverty line who also experience deprivation. Our approach involves excluding households with incomes below the poverty line if they report zero or negative income or are self‐employed, have expenditure well in excess of their income, have substantial wealth holdings, or if they do not report having experienced financial stress over the past year. The combined impact of all four exclusions is to reduce the half‐median income poverty rate from 9.9 per cent to 5.4 per cent, but also suggests that poverty increased by more over the decade to 2003–04 than the original estimates indicate.     

National pro-poor spending programmes and their effect on income inequality and poverty: Evidence from Vietnam

This article examines the causal effects of the national (pro-poor) targeted programmes (NTPs) on both poverty incidence and inequality in Vietnam over the period 2002–2010. While the links between NTPs and poverty alleviation and income inequality have previously been analysed independently, this study is the first to offer a comprehensive analysis of NTPs expenditure on poverty and inequality simultaneously. Applying the system generalized method of moments estimator to a panel of Vietnamese regional data, we are unable to establish that NTPs have significantly mitigated poverty incidence. However, we estimate that NTPs have significantly increased inequality. We offer possible explanations why the NTPs have resulted in these unintended outcomes and discuss potential policies which can reduce both poverty and inequality.     

Negative income taxes,inequality and poverty

We use a neoclassical growth model with heterogeneous agents to analyze the redistributive effects of a negative income tax system, which combines a flat rate tax with a fully refundable credit (“demogrant”). We show that changing the demogrant‐to‐output ratio causes significant changes in the distribution of income. Specifically, we find that increasing the demogrant‐to‐output ratio sharply reduces the level of inequality as well as both relative and absolute poverty (all measured in terms of post‐tax total income). However, these reductions in inequality and poverty come at the expense of a significant reduction in output.     

Income distribution and economic development: Insights from machine learning

We draw upon recent advances that combine causal inferences with machine learning, to show that poverty is the key income distribution measure that matters for development outcomes. In a predictive framework, we first show that LASSO chooses only the headcount measure of poverty from 37 income distribution measures in predicting schooling, institutional quality, and per capita income. Next, causal inferences with post‐LASSO models indicate that poverty matters more strongly for development outcomes than does the Gini coefficient. Finally, instrumental variable estimates in conjunction with post‐LASSO models show that compared to Gini, poverty is more strongly causally associated with schooling and per capita income, but not institutional quality. Our results question the literature's overwhelming focus on the Gini coefficient. At the least, our results imply that the causal link from inequality (as measured by Gini) to development outcomes is tenuous.     

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.