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.     

MEASURING INEQUALITIES: DO HOUSEHOLD SURVEYS PAINT A REALISTIC PICTURE?

The paper addresses the issue of the accuracy of standard‐of‐living measurements using household survey data. First, it highlights the fact that lighter data collection processes in some developing countries have added to measurement errors in consumption and income aggregates measurement errors. The paper reasserts the need to apply reference guidelines to the measurement of household consumption in order to compute comparable distribution indicators across countries and over time. Second, it contends that it is hard to analyze inequality solely from consumption patterns without taking income and savings into account. Two solutions are proposed for the correction of income measurement errors: by using savings declarations and by implementing a multiple imputation procedure. The results are based on a careful analysis of the EPM93 survey of Madagascar whose design is quite close to the LSMS household surveys, and the ENV98 survey of Côte d'Ivoire representative of surveys conducted nowadays in most Sub‐Saharan African countries.     

INCOME INEQUALITY IN URBAN COLOMBIA: A DECOMPOSITION ANALYSIS

The persistence of poverty and income inequality in less developed countries (LDCs) is a source of serious concern to development economists. To understand the structure of inequality, several researchers using a variety of methodologies have measured the importance of various contributory factors to overall income variability. The available literature—which now includes studies of Brazil, Mexico, Iran, the Philippines, Taiwan, Thailand, Pakistan, and Colombia-has been reviewed elsewhere (Fields, forthcoming). This paper presents additional evidence for urban Colombia, in the process raising some important methodological issues which bear on the design of future research studies.
The data set used in this paper is described in Section I. The decomposition of Colombian inequality by functional income source is presented in Section 11 for micro data. Section I11 examines the robustness of source decomposition procedures to data aggregation. Section IV presents inequality decompositions by city, and Section V by other income-determining characteristics. Conclusions appear in Section VI.     

EVIDENCE ON RELATIONSHIPS AMONG ALTERNATIVE MEASURES OF CONCENTRATION: A TOOL FOR ANALYSIS OF LDC INEQUALITY

The evidence on economic inequality in nearly all developing countries is both seriously incomplete and of moderate to poor quality. In addition, information often corresponds to distributions which appear to be less revealing and useful than other ones; thus it can be argued that the frequently available distribution of income among households ranked by household income is less helpful than the seldom found distribution of consumption among persons ranked by per capita household consumption. Whether one's objective is to assess inequality in some absolute sense or (especially) to make comparisons across countries or evaluate trends over time, it is useful to know whether systematic relationships exist among various measures of inequality, in particular between those most commonly available and those conceptually most interesting. Illustrative comparisons of a variety of inequality indicators are presented. They suggest that in developing countries the concentration of income among persons (assuming equal distribution within the family) does not differ much from the concentration among households. They also suggest that the concentration of consumption is somewhat less unequal than that of income, the ratio of the respective Gini coefficients tending to cluster around 0.85 to 0.90.     

How large are wage differentials in Austria?

The OECD has repeatedly recommended that wage bargaining in Austria be decentralised to allow wage diferentials to widen. But the status quo itself is in question. While studies of aggregate industry data indicate a high degree of wage dispersion, research based on data from household surveys seems suggest that income inequality in Austria is as small as in the Scandinavian countries. This paper seeks to reconcile these opposing views. It shows that data from the household surveys underestimate the size of inter-industry wage differentials. An analysis of the structure of contractual wage rates supports the view that wage inequality is very pronounced in Austria and that a narrowing of the wage gap would lead both to an increase in productive efficiency and an increase in income equality.     

A Comparison of Income and Expenditure Inequality Estimates: The Australian Evidence, 1975–76 to 1993–94

Using Australian unit record data this paper compares income and expenditure inequalities over the period 1975–76 to 1993–94. The study finds inconsistencies between the two inequality movements over much of this period. We also observe differences in the nature of income and consumption disparities. Both approaches show that the 'within group' inequality dominates the 'between group' component when the population is divided into household types. The inequality estimates are sensitive to the equivalence scale used as the household size deflator but not to the cost of living index used as the price deflator.     

Wage,income and consumption inequality in Japan, 1981–2008: From boom to lost decades

In this paper we document the main features of the distributions of wages, earnings, consumption and wealth in Japan since the early 1980s using four main data sources: the Basic Survey on Wage Structure (BSWS), the Family Income and Expenditure Survey (FIES), the National Survey of Family Income and Expenditure (NSFIE) and the Japanese Panel Survey of Consumers (JPSC). We present an empirical analysis of inequality that specifically considers the path from individual wages and earnings, to household earnings, after-tax income, and finally consumption. We find that household earnings inequality rose substantially over this period. This rise is made up of two distinct episodes: from 1981 to 1996 all incomes rose, but they rose faster at higher percentiles; from 1996 to 2008 incomes above the 50th percentile remained flat but they fell at and below the 50th percentile. Inequality in disposable income and in consumption also rose over this period but to a lesser extent, suggesting taxes and transfers as well as insurance channels available to households helped to insulate household consumption from shocks to wages. We find the same pattern in inequality trends when we look over the life cycle of households as we do over time in the economy. Additionally we find that there are notable differences in the inequality trends for wages and hours between men and women over this period.     

Inequality of opportunity in sub-Saharan Africa

Inequality of opportunity is defined as the difference in individuals’ outcome systematically correlated with morally irrelevant pre-determined circumstances, such as ethnicity, socio-economic background, area of birth. This definition has been extensively studied by economists on the assumption that, in addition to being normatively undesirable, it can be related to low potentials for growth. However, empirical estimations of inequality of opportunity require accessing rich data sources, rarely available in poorer countries. In this paper, we exploit 13 consumption household surveys to evaluate inequality of opportunity in 10 Sub-Saharan African countries. According to our results, the portion of total inequality that can be attributed to exogenous circumstances is between 40% and 56% for the generality of countries. Our estimates are significantly higher than what has been found by previous studies. We detect a positive association between total consumption inequality and inequality of opportunity, and we study the different sources of unequal opportunities. The place of birth and the education of the father appear to exert the most relevant role in shaping inequality of opportunity in the region.     

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.     

The role of education and household composition for transitory and permanent income inequality–evidence from PSID data

Transitory and permanent shocks to income have been shown to be important determinants of household consumption. This paper shows that there are significant differences in the trends of transitory and permanent income inequality between demographic groups since the 1980s. Using data from the Panel Study of Income Dynamics, educational attainment and the composition of a household are found to play a key role. While permanent inequality increases steadily for educated households, it is flat over large parts of the sample period for the less educated households. Transitory inequality increases for all households headed by couples whereas it is constant for single households. Altogether, permanent shocks account for a larger part of the income variance of educated households whereas transitory shocks are relatively more important for the less educated. These results are able to shed light on the transmission of changes in income inequality to consumption inequality.     

INCOME AND CONSUMPTION DISTRIBUTION TRENDS IN THE PHILIPPINES, 1950–70*

Unlike most developing countries, the Philippines has had several (four) reasonably comparable family income and expenditure surveys, covering a reasonable period of time (15 years). This study draws on those surveys and on wage data in an attempt to judge how, if at all, the distribution of income has been changing. The household survey data shows a declining share of both income and consumption for the top income groups; for the bottom quintile the share of recorded income fell while that of recorded consumption rose. When possible biases of the data are allowed for, it is hard to argue that either a narrowing or widening of income differentials occurred over these years. Real wages of a number of important occupations appear to have fallen, however. Only a partial reconciliation of the trends indicated by these wage series and the income trends for various occupational groups implicit in the household survey data was possible, indicating either data problems or the need for more subtle interpretations of the data. Since structural change in the labour force has been rapid (an increasing share being found in the high income occupations as time passed), declining wage rates for certain lower income groups cannot be taken to imply a general worsening of distribution. Our final conclusion is that distribution has probably changed little, and is about as likely to have changed one way as the other.     

Fairness and inequality tolerance: Evidence from the Life in Transition Survey

This paper examines the link between inequality and individual well-being using household survey data from 27 transition economies, where income inequality increased considerably since 1989. A test of inequality aversion in individual preferences that draws on the Fehr and Schmidt (1999) specification of inequality aversion is proposed, and the difficulties of implementing it in a non-experimental setting are discussed. Estimates based on this model confirm aversion to inequality among individuals both in the pooled sample and separately among the EU and non-EU countries. The Gini index, on the other hand, is unable to capture this negative effect of inequality on well-being. Notably, inequality aversion is not intrinsic. Rather, it appears to be tied to a concern with the fairness of the institutions underlying the distribution of fortunes in society. The evidence is suggestive of inequality of opportunity driving attitudes toward overall inequality.     

Measuring lnequality in the Middle East 1990–2016: The World’s Most Unequal Region?

In this paper we combine household surveys, national accounts, income tax data and wealth data in order to estimate income concentration in the Middle East for the period 1990–2016. According to our benchmark series, the Middle East appears to be the most unequal region in the world, with a top decile income share as large as 64 percent, compared to 37 percent in Western Europe, 47 percent in the US and 55 percent in Brazil (see Alvaredo et al. 2018). This is due both to enormous inequality between countries (particularly between oil‐rich and population‐rich countries) and to large inequality within countries (which we probably under‐estimate, given the limited access to proper fiscal data). We stress the importance of increasing transparency on income and wealth in the Middle East, as well as the need to develop mechanisms of regional redistribution and investment.     

Household Debt,Consumption, and Income Inequality

Using the Johansen and Engle–Granger cointegration tests, we show that there is one cointegrating relationship between household debt, consumption, and income inequality in the United States for the period from 1929 to 2009. Given this result, we use a Vector Error-Correction model to further understand the dynamics among the three variables. Results indicate that increases in income inequality and consumption directly contribute to increases in household debt. Interestingly, the results reveal some feedback from household debt to income inequality. We also show that debt-driven consumption should be viewed with caution as the results show that increases in household debt correspond with future declines in the rate of consumption.     

Inequality and volatility moderation in Russia: Evidence from micro-level panel data on consumption and income

We construct key household and individual economic variables using a panel micro data set from the Russia Longitudinal Monitoring Survey (RLMS) for 1994–2005. We analyze cross-sectional income and consumption inequality trends and find that inequality decreased during the 2000–2005 economic recovery. The decrease appears to be driven by falling volatility of transitory income shocks. The response of consumption to permanent and transitory income shocks becomes weaker later in the sample, consistent with greater self-insurance against permanent shocks and greater smoothing of transitory shocks. Finally, expenditure and income inequality in Russia are not far apart.     

Household wealth, public consumption and economic well-being in the United States

Standard official measures of household economic well-beingin several countries are based on money income. The generalconsensus is that such measures are limited because they ignorecertain crucial determinants of well-being. We examine two suchdeterminants—household wealth and public consumption—inthe context of the US. Our findings suggest that the level anddistribution of economic well-being is substantially alteredwhen money income is adjusted for wealth or public consumption.Over the 1989–2000 period, median well-being appears toincrease faster when these adjustments are made than when standardmoney income is used. Adding imputed rent and annuity from householdwealth to household income increases measured inequality, whileadding public consumption reduces it. However, all three measuresshow about the same rise in inequality over the period.     

Distributional consequences of asset price inflation in the Euro Area

We study the distributional consequences of housing price, bond price and equity price increases for Euro Area households using data from the Household Finance and Consumption Survey (HFCS). The capital gains from bond price and equity price increases turn out to be concentrated among relatively few households, while the median household strongly benefits from housing price increases. The capital gains from bond price increases (relative to household net wealth) do not correlate with household net wealth (or income). Bond price increases thus leave net wealth inequality largely unchanged. In contrast, equity price increases largely benefit the top end of the net wealth (and income) distribution, thus amplify net wealth inequality. Housing price increases display a hump shaped pattern over the net wealth distribution, with the poorest and richest households benefitting least, but there exists considerable heterogeneity across Euro Area countries. The ECB's OMT announcements over the summer of 2012 had quantitatively similar distributional implications as an unexpected loosening of the policy rate by about 175 basis points.     

Some Ethnic Dimensions of Income Distribution from Pre- to Post-reform New Zealand, 1984–1998*

Based on unit record data from four household surveys conducted by Statistics New Zealand for the years 1983/1984, 1991/1992, 1995/1996 and 1997/1998, this paper addresses some ethnic dimensions of income inequality among New Zealanders over the period of the surveys. It applies alternative techniques of decomposition of the Gini coefficient of inequality by subgroups of population. It then analyses how changes in the incomes of specific population subgroups affect the overall inequality. The results help quantify the economic distances among the different ethnic populations of New Zealand, and indicate how and why these distances have been changing over time.     

Testing Prediction Performance of Poverty Models: Empirical Evidence from Uganda

This paper examines the performance of a method of predicting poverty rates. Because most developing countries cannot justify the expense of frequent household budget surveys, additional low‐cost methods have been developed and used. The prediction method is based on a model linking the proportion of poor households to suitable explanatory variables (consumption proxies). These consumption proxies are variables that can be collected at much lower cost through smaller annual surveys. Several applications have shown that such models can produce poverty estimates with confidence intervals of a similar magnitude to the poverty estimates from the household budget surveys. There is, however, limited evidence of how well the methods perform out‐of‐sample. A series of seven household budget surveys conducted in Uganda in the period 1993–2005 allows us to test the prediction performance of the model. We test the poverty models by using data from one survey to predict the proportion of poor households in other surveys, and vice versa. The results are encouraging, as all models predict similar poverty trends. Although in most cases the predictions are precise, sometimes they differ significantly from the poverty level estimated from the survey directly.     

Deriving Long-Run Inequality Series from Tax Data*

Prior to the last three decades, regular surveys on household income were rare or non-existent in many developed countries, making it difficult for economists to develop long-run series on income distribution. Using taxation statistics, which tend to be available over a longer time span, I propose a method for imputing the incomes of non-taxpayers, and deriving the underlying distribution of income. Because taxation statistics are typically disaggregated by gender, it is possible to derive separate income distribution series for men and women in countries where individuals file separately. I show that over the past four decades, the distribution of adult male incomes and the distribution of family incomes are highly correlated. Applying this method to Australia, I develop a new annual series for inequality from 1942 to 2001. Inequality fell in the 1950s and the 1970s, and rose during the 1980s and 1990s – a pattern similar to that in the UK.