Changing Contours of Income Stratification and Decomposition of Income Inequality: Evidence from Recent Longitudinal Survey in India

The paper, based on India Human Development Survey (IHDS) data, tries to address the question- how unequal is India in terms of income distribution? Accordingly, the paper examines the trends, levels, sources and factors of income inequality in India between 2005 and 2012. Three important results stemmed from our analysis. First, in this paper we use Gini as a measure of inequality and find that income inequality in rural India has increased from 0.50 to 0.54 between 2005 and 2012, whereas, in urban India income inequality has increased from 0.48 to 0.49 during the same period. Next and most importantly, we decompose income inequality by income sources and find that amongst different sources of income inequality; the contribution of farm income in total inequality has decreased from 35 percent in 2005 to 21 percent in 2012 in rural India. On the other hand, the contribution of salaried income in total inequality has plummeted drastically from 65 percent in 2005 to 16 percent in 2012 in urban India. Finally, we use Theil’s T index from the class of Generalized Entropy (GE) inequality measures, while decomposing income by four most important factors; namely, place of residence, social, educational and occupational groups. It is irrespective of these factors; the relative share of within-group inequality is not only much higher than that of between-group inequality, also its share has increased between these two periods. Thus, our paper suggests that these mutually reinforcing inequalities, in the long run, if not addressed effectively, will create a hard-hitting division between the privileged and the rest in Indian society.

     

Infant mortality,relative income and public policy

Do health outcomes depend on relative income as well as on an individual's absolute level of income? We use infant mortality as a health status indicator and find a significant and positive link between infant mortality and income inequality using cross-national data for 93 countries. Holding constant the income of each of the three poorest quintiles of a country's population, we find that an increase in the income of the upper 20% of the income distribution is associated with higher, not the lower infant mortality. Our results are robust and not just caused by the concave relationship between income and health. The estimates imply a decrease in infant mortality by 1.5% for a one percentage point decrease in the income share of the richest quintile. The overall results are sensitive to public policy: public health care expenditure, educational outcomes, and access to basic sanitation and safe water can explain the inequality–health relationship. Thus, our findings support the hypothesis of public disinvestment in human capital in countries with high income inequality. However, we are not able to determine whether public policy is a confounder or mediator of the relationship between income distribution and health. Relative deprivation caused by the income distance between an individual and the individual's reference group is another possible explanation for a direct effect from income inequality to health.     

Decomposing Global Inequality

This paper provides an intuitive additive decomposition of the global income Gini coefficient with respect to differences within and between countries. In 2005, nearly half the total global income inequality is due to income differences between Europeans and North Americans on the one side and inhabitants of Asia on the other, with the China‐USA income differences alone accounting for six percent of global inequality. Historically, income differences between Asia and Europe have driven a large part of global inequality, but the quantitative importance of within‐Asia income inequality has increased substantially since 1950.     

Calculation and decomposition of income inequality in low- and middle-income countries: a survey data analysis

This article estimates income inequality in a sample of four low- and middle-income (LMI) countries namely; Albania, Nepal, Tajikistan and Tanzania using the household survey data – Nepal Living Standard Measurement Survey Second. First, we estimate the income generation function for each country and calculate the income inequality using Gini index (GI). Second, we decompose the income Gini into the determinants of income generation functions. Based on the decomposition result, socio-economic factors are the most important determinants of income inequality followed by geographic factors. Demographic factors have the least effect on income inequality in all four countries. Third, we propose a new method to quantify the effect of change in each covariate of income generation function on income Gini. That allows us to quantify the effects of change in specific policy such as increase in investment in schooling or public health to specific group of the population in society on income inequality. A carefully chosen, integrated policy can significantly reduce inequality in all four countries under study.     

Indian Income Inequality, 1922‐2015: From British Raj to Billionaire Raj?

We combine household surveys and national accounts, as well as recently released tax data to track the dynamics of Indian income inequality from 1922 to 2015. According to our benchmark estimates, the top 1 percent of earners captured less than 21 percent of total income in the late 1930s, before dropping to 6 percent in the early 1980s and rising to 22 percent in the recent period. Our results appear to be robust to a range of alternative assumptions seeking to address numerous data limitations. These findings suggest that much more can be done to promote inclusive growth in India. We also stress the need for more transparency on income and wealth statistics, which is key to allow an informed democratic debate on inequality.     

The Dilemmas of Technology: A Review Article

During the 1990s, all of the European transition economies (TE) experienced a major recession and suffered from the explosion of income inequality. However, distribution of income between labor and capital differed greatly from one group of post-communist countries to another. The paper discusses and analyzes linkages between models of capitalism that emerged in former communist countries in the 1990s and the outcome of capitalist transition for labor in terms of income distribution and inequality. It is based on the estimates of the Marxian rate of exploitation and other indicators of labor income performance during the reform period.     

Equality of opportunity and the expansion of higher education in the UK

Using nine waves of data from Understanding Society (UKHLS), we study the expansion of higher education in the UK and its consequences for levels of and inequalities in income, physical and mental health. University expansion was characterized by a large increase in the proportion of graduates, with higher rates of graduation among individuals from more advantaged socioeconomic backgrounds. Having controlled for birth cohort and lifecycle effects, there is evidence of significant inequality of opportunity (IOp) in the actual outcomes. However, comparing actual outcomes with counterfactual projections, that freeze the likelihood of university graduation and the joint distribution of graduation and circumstances to the pre-1963 levels, we do not detect an impact of the expansion of higher education on IOp in income and only small reductions in IOp in physical and mental health.     

INCOME DISTRIBUTION STATISTICS IN LATIN AMERICA AND THEIR RELIABILITY

This paper is addressed to the question of how far income distribution statistics currently available in Latin America can be relied upon, either to assess the degree of inequality in the national distribution of income or to undertake comparisons between countries or over time. It gives a summary account of research carried out on Latin American data.
The sources available in Latin America for estimating income distributions are discussed. Concentrating the attention on household surveys conducted in various Latin American countries, an inventory of such surveys and their characteristics is offered, along with a detailed exposition of survey methods and income concepts used for estimating household income. Methods used for assessing the representativeness of samples are summarily reviewed. The case for comparing income data from household surveys and population censuses with national accounts estimates is put forward, along with the procedures and assumptions used for carrying out such comparisons. The relative discrepancy between the two sources is taken as indicative of the degree of underestimation of each type of income in each survey. An analysis of such discrepancies across the set of surveys considered gives clues on possible underestimation biases in measuring each type of income and total household income in different types of survey and in population censuses.
Differential effects on comparability of survey results call for appropriate methods of adjusting income distribution estimates to account for the missing incomes. A method for carrying out such an adjustment is applied to income distributions from a selected number of Latin American surveys. The results obtained provide an indication of how much difference it makes to use unadjusted or adjusted data to assess income concentration or to carry out comparisons over time or space.     

Decomposing World Income Distribution: Does The World Have A Middle Class?

Using the national income/expenditure distribution data from 111 countries, we decompose total inequality between the individuals in the world, by continents and regions. We use Yitzhaki's Gini decomposition which allows for an exact breakdown of the Gini. We find that Asia is the most heterogeneous continent; between-country inequality is much more important than inequality in incomes within countries. At the other extreme is Latin America where differences between the countries are small, but inequalities within the countries are large. Western Europe/North America is fairly homogeneous both in terms of countries' mean incomes and income differences between individuals. If we divide the world population into three groups: the rich (those with incomes greater than Italy's mean income), the poor (those with incomes less than Western countries' poverty line), and the middle class, we find that there are only 11 percent of people who are "world middle class"; 78 percent are poor, and 11 percent are rich.     

Perceptions of inequality

Individual perceptions of (income or wealth) inequality have strong effects on their decisions as economic agents or voters. It is therefore important to know more about the relation between perceived and measured inequality. We present a novel formal framework that is based on the assumption that people typically do not observe the entire income (wealth) distribution and that their guesses about the extent of inequality are based on “self-centered” reference groups. This framework predicts that perceptions of inequality will change along positions in the income distribution and that for a specific position various dimensions of inequality perception are related to each other. First, low (high) income individuals overestimate (underestimate) their own position. Second, subjective estimates of average earnings increase with the own income position. Third, high or low income people have different perceptions about the skewness and the “shape” of the income distribution (e.g. pyramid or diamond). Fourth, the subjective perception of inequality is lower for high-income individuals. Survey data from 40 countries provide strong support for the framework.     

代际流动约束下生育率与收入不平等关系的国际检验

收入不平等问题和人口生育率过低问题是当下中国面临的两大难题,但目前理论界关于人口因素与收入不平等关系的研究,很少从生育率视角来考察以及考虑代际收入流动在其中的作用.文章从理论与经验两个方面来考察生育率对收入不平等的影响,理论模型表明:在关于代际收入流动的假设下,一个经济体中生育率的提高会使穷人比重提高,进而拉大收入不平等.进一步地,文章利用1970-2011年76个国家(地区)面板数据的经验研究发现:(1)总和生育率的提高会拉大收入不平等,如果每个妇女平均多生育一个孩子,将会使基尼系数增加0.025;(2)以出生率作为总和生育率替代指标的实证结果与基准结果基本一致,这说明不同生育率测算指标高度相关且可相互替代;(3)对于代际收入流动弹性越高、收入水平越低或生育率越高的国家(地区),其生育率提高对收入不平等的拉大作用越大.文章关于生育率对收入不平等影响的作用机制和异质性特征的考察,对于我国如何在实施"全面二孩"政策下寻求应对严峻的收入分配问题之策提供了国际经验和启示.     

AN EXPLORATORY COMPARISON OF INCOME RISK IN GERMANY AND THE UNITED STATES

Using longitudinal data, 1 estimate the impact of redistribution on the welfare cost of income risk in Germany and the United States. The estimates account fully for behavior because individuals in each country have responded optimally to that country's policy. The results indicate that the welfare cost of income risk is 5.4 percent of disposable income in Germany, 8.5 percent in the U.S. Redistribution has reduced these risks from their pre-tax, pre-transfer levels by 43 percent in Germany, 21 percent in the U.S. The political importance of income security is evident in both countries, as risk relief often eliminates the net burden of redistributive taxes among middle-class households. The conclusions are robust across several models of income expectations.     

The contribution of minimum wage valorization policy to the decline in household income inequality in Brazil: A decomposition approach

There is a vast literature that estimates the effect of the minimum wage on wage inequality in various countries. However, as the minimum wage directly affects nonlabor income of families in some countries (in the Brazilian case via the benefits of the pension system and of certain social programs), this article extends the empirical analysis by studying the effects of the minimum wage on the level of inequality of household income as a whole. To accomplish that we employ a decomposition method that gauges the contribution of the increases in the minimum wage that occurred in recent decades in Brazil through the labor and nonlabor sources of household income. The results show that the minimum wage had a contribution of 64 percent to the observed fall in income inequality between 1995 and 2014 and that pensions were the most relevant channel over this period.     

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.     

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)     

Economic Growth Evens Out Happiness: Evidence from Six Surveys

In spite of the great U‐turn that saw income inequality rise in Western countries in the 1980s, happiness inequality has fallen in countries that have experienced income growth (but not in those that did not). Modern growth has reduced the share of both the “very unhappy” and the “perfectly happy.” Lower happiness inequality is found both between and within countries, and between and within individuals. Our cross‐country regression results suggest that the extension of various public goods helps to explain this greater happiness homogeneity. This new stylized fact arguably comes as a bonus to the Easterlin paradox, offering a somewhat brighter perspective for developing countries.     

The impact of macroeconomic factors on income inequality: Evidence from the BRICS

In this paper we investigate how the evolution of income growth, real interest rates, and inflation have driven income inequality across a variety of countries with particular focus on the BRICS economies (Brazil, Russia, India, China, and South Africa) during the period 2001 to 2015. Our work suggests that, when central banks of the BRICS economies use monetary policy for macroeconomic stabilization, they need to consider the impact monetary policy changes have on the distribution of income in their nations. Our estimates reveal that the unintended consequence of policies that induce economic growth and higher prices is higher income inequality. We find that the positive relationship between the three macroeconomic variables and income inequality for the BRICS economies is stronger during the post-2008 period.     

Deterrence and knowledge of the law: The case of drunk driving

While it is necessary that researchers make choices in order to estimate inequality, the reasons for the measurement choices and their impact on inequality estimates have not been widely assessed. This paper uses Canadian data from the 1980s to analyse whether inequality estimates are sensitive to common measurement choices. Seemingly minor technical choices about the treatment of outlying observations, such as the use of top-income coded data, exclusion of very high and low observations, and differences among data sets in the capture of very high observations affect estimates of inequality. Further, the impact of the treatment of outlying observations on inequality estimates are at least as large as the impact of measurement choices of a conceptual nature, such as the income definition and population selection. The sensitivity of inequality estimates to measurement choices, which often remain invisible, affect inferences about the relative degree of inequality at a given point in time among countries and changes over time.     

THE MEASUREMENT OF INEQUALITY OF OPPORTUNITY: THEORY AND AN APPLICATION TO LATIN AMERICA

Building on the existing literature, this paper constructs a simple scalar measure of inequality of opportunity and applies it to six Latin American countries. The measure—which captures between‐group inequality when groups are defined exclusively on the basis of predetermined circumstances—is shown to yield a lower‐bound estimate of true inequality of opportunity. Absolute and relative versions of the index are defined, and alternative parametric and non‐parametric methods are employed to generate robust estimates. In the application to Latin America, we find inequality of opportunity shares ranging from one quarter to one half of total consumption inequality. An opportunity‐deprivation profile that identifies the worst‐off types in each society is also formally defined, and described for the same six countries. In three of them, 100 percent of the opportunity‐deprived were found to be indigenous or Afro‐descendants.     

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.