THE EFFECT ON POVERTY STATUS IN ISRAEL OF CONSIDERING WEALTH AND VARIABILITY OF INCOME

This paper assesses the effects of including wealth and the variability of income on the incidence of poverty and the degree of income inequality in Israel. A special survey, which includes data on the wealth and income of a national sample of Israeli families in 1963–64 and 1964–65, allows us to go beyond measures based on current income alone.
The first section reviews earlier studies of poverty in Israel. The next section looks at poverty and inequality in terms of current income, current wealth, and a combined measure of income and wealth. The combined measure is the Hansen-Weisbrod measure (HW), which equals income plus the annuity value of wealth, assuming all wealth is just consumed at the time of death. It is interesting that, in spite of the much higher wealth inequality than income inequality, the HW measure was slightly more equally distributed than income. This result occurred because the annuity component made up a low share of the total HW measure and the correlation between income and wealth was well under 1. Although overall inequality and poverty were similar for income and HW measures, the incidence of poverty by subgroup depended on the measure used.
The final section presents a dynamic view of poverty and inequality. Year-to-year changes in poverty were substantial. Because of the use of a relative poverty concept and the rise in real incomes, the real income poverty line rose by 15 percent between 1963 and 1964. Still, of those in income poverty in 1963, 37 percent managed to escape poverty in 1964. The paper shows how the degree to which poverty was stable or transitory varied substantially by age and country of origin.     

POVERTY AND INCOME DISTRIBUTION IN BRAZIL1

The article refutes the contention that Brazil's development has not benefited the poor and that rapid growth has had a polarizing effect on the distribution of income. It uses the National Household Expenditure Survey of 1974–75 to try to quantify the extent of poverty and concludes that the incòme levels of the poor have been underestimated in the past. The evidence suggests also that occupational and regional variables are powerful determinants of income stratification. Wage rate statistics convey information about long-term trends in income. The article notes considerable increases in rural wages during the 1970s as well as wage improvements in the urban informal sector. Shifts in the structure of employment have probably been the most powerful cause of economic improvement in Brazil. The enormous absorption of rural-urban migrants occurred without a flooding of the lower income urban categories. Social indicators and statistics referring to ownership of household durable consumer goods corroborate income and labor market evidence to the effect that there has been considerable progress for the poor during the 1970s. The article reviews statistical evidence bearing on distribution. There is little doubt that the distribution of income in Brazil is very skewed. It is not possible, however, to come to conclusions about changes that might have occurred in the degree of inequality over time. Finally, the article includes data on the “distribution of education” and the “distribution of life expectancy” and notes improvement over time in both. This article takes advantage of the Brazilian population census of 1980 to bring up to date some of the statistical material that bears on the issues of poverty and income distribution. First, the article describes the overall context of Brazilian development since 1960. The second part analyzes the extent of poverty in the mid-1970s. The third part deals with trends in wages, employment and selected welfare indicators. The last section briefly summarizes the information relating to income distribution: what is the extent of skewedness and how has it evolved over time?     

Welfare Measurement and Measurement Error

The approximate effects of measurement error on a variety of measures of inequality and poverty are derived. They are shown to depend on the measurement error variance and functionals of the error–contaminated income distribution, but not on the form of the measurement error distribution, and to be accurate within a rich class of error–free income distributions and measurement error distributions. The functionals of the error–contaminated income distribution that approximate the measurement error induced distortions can be estimated. So it is possible to investigate the sensitivity of welfare measures to alternative amounts of measurement error and, when an estimate of the measurement error variance is available, to calculate corrected welfare measures. The methods are illustrated in an application using Indonesian household expenditure data.     

Redistribution in the age of austerity: evidence from Europe 2006–2013

We examine the relationship between changes in a country’s public sector fiscal position on inequality at the top and bottom of the income distribution during the age of austerity from 2006 to 2013. We use a parametric Lorenz curve model and Gini-like indices of inequality as our measures to assess distributional changes. Based on Statistics of Income and Living Conditions (EU-SILC) and IMF data for 12 European countries, we find that more severe adjustments to the cyclically adjusted primary balance (i.e., more austerity) are associated with a more unequal distribution of income driven by rising inequality at the top. The data also weakly suggests a decrease in inequality at the bottom. The distributional impact of austerity measures reflects the reliance on regressive policies and likely produces increased incentives for rent-seeking while reducing incentives for workers to increase productivity.     

Indexing Out of Poverty? Fiscal Drag and Benefit Erosion in Cross-National Perspective

We assess how tax-benefit policy developments in 2001–11 affected the household income distribution in seven EU countries. We use the standard microsimulation-based decomposition method, separating further the effect of structural policy changes and the uprating of monetary parameters, which allows us to measure the extent of fiscal drag and benefit erosion in practice. The results show that despite different fiscal effects, policies overall mostly reduced poverty and inequality and both types of policy developments had sizeable effects on the income distribution. We also find that the uprating of monetary parameters not only had a positive effect on household incomes, meaning fiscal drag and benefit erosion were avoided, but generally also contributed more to poverty and inequality reduction than structural policy reforms.     

浅析贫困、经济增长与脱贫时间——基于中国城镇居民调查数据的分析

20世纪90年代以来，经济增长和收入分配不平等对于城镇人口脱贫时间产生了消极影响。研究发现，城镇贫困在1997年达到高峰，然后逐渐缓和；贫困人口的收入增长在初期能使脱贫时间迅速减少，但边际效果是递减的；贫困人口之间的收入分配不平等延长了脱贫时间，如果贫困人口的初始收入增加，则会明显缩短脱贫时间。     

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.     

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.     

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.     

The Redistributive Effects of a Minimum Wage Increase in New Zealand: A Microsimulation Analysis

This paper examines the potential effects on inequality and poverty of a minimum wage increase, based on a microsimulation model that captures the details of household composition and the income tax and welfare benefit system and allows for labour supply responses. Results suggest that, largely due to the composition of household incomes, a policy of increasing the minimum wage has a relatively small effect on the inequality of income per adult equivalent person, and a money metric utility measure, using several inequality indices. Hence, the minimum wage policy does not appear to be particularly well targeted, largely due to many low wage earners being secondary earners in higher income households, while many low income households have no wage earners at all. These results are reinforced when allowing for wage spillovers further up the wage distribution. Nevertheless, a minimum wage increase can have a more substantial effect on some poverty measures for sole parents in employment.     

INCOME MOBILITY IN SPAIN: HOW MUCH IS THERE?

Traditional cross-sectional research is unable to measure the degree of income mobility in an income distribution. Using longitudinal data and various income stability indices, this paper measures the level of permanent inequality (immobility) in Spain for the period 1985–92. Results indicate that the transitory component of inequality is large and the level of income mobility increases over time while income inequality decreases slightly. More stability is found at the top than at the bottom of the income distribution and the range of the registered movements is rather short.     

Migration and urban poverty and inequality in China

Using data from recent surveys of migrants and local residents in ten cities in 2005, this paper examines how migration influences measurements of urban poverty and inequality in China, and also compares how other indicators of well-being differ for migrants and local residents. Contrary to previous studies that report that the income poverty rate of migrant households is 1.5 times that of local resident households, we find relatively small differences in the poverty rates of migrants and local residents. Although the hourly wages of migrants are much lower than those of local residents, migrant workers work longer hours and have lower dependency ratios and higher labor force participation rates. Including migrants increases somewhat measures of urban income inequality. Significant differences between migrants and local residents are found for non-income welfare indicators such as housing conditions and access to social insurance programs.     

INEQUALITY AND THE MEASUREMENT OF RESIDENTIAL SEGREGATION BY INCOME IN AMERICAN NEIGHBORHOODS

American metropolitan areas have experienced rising residential segregation by income since 1970. One potential explanation for this change is growing income inequality. However, measures of residential sorting are typically mechanically related to the income distribution, making it difficult to identify the impact of inequality on residential choice. This paper presents a measure of residential segregation by income, the Centile Gap Index (CGI), which is based on income percentiles. Using the CGI, I find that a one standard deviation increase in income inequality raises residential income segregation by 0.4–0.9 standard deviations. Inequality at the top of the distribution is associated with more segregation of the rich, while inequality at the bottom and declines in labor demand for less-skilled men are associated with residential isolation of the poor. Inequality can fully explain the rise in income segregation between 1970 and 2000.     

INEQUALITY AND POVERTY IN JAPAN*

This paper presents a brief survey of inequality and poverty in Japan. It shows empirical evidence on the extent of both inequality in income distribution and of poverty rates; the paper discusses the cause of increases in both these variables, and the implication of such trends. The paper goes on to argue the difference between inequality of opportunity and inequality of outcome and shows some related empirical evidence. Finally, the paper investigates the relationship between economic efficiency and equity, supposed to be in a trade‐off relationship, and presents my personal view of that relationship and policy recommendations.     

Trends in real income in Britain: A microeconomic analysis

Trends in real national income are typically assessed using aggregate indicators such as GDP per capita, or mean household income, whereas the income distribution literature focuses on trends in income inequality. By contrast this paper takes an integrated approach to real national income measurement; it uses methods incorporating both size and distributional considerations, and applies them to household income microdata in order to measure changes in real income in the U.K. during the 1980s. A parametric class of decomposable real income indisces is proposed which complements quasi-ordering methods such as rank and generalised dominance criteria by telling us how much real income increased over the period (if at all). The indices are also additively decomposable by population subgroup, a property which helps reveal who the gainers and losers were. The analysis also draws attention to the normative and statistical issues raised by the presence of a few very small incomes.     

Sources of Inequality: Measuring the Contributions of Income Sources to Rising Family Income Inequality

We develop a simulation method for measuring the impact of changes in the distributions of the main income sources on growth in family income inequality. We simulate the entire distribution of family income under the counterfactual, “What if the distribution of each source had not changed?” The simulation method allows us to evaluate the impact of changes at any point in the distribution as well as with multiple measures of inequality. We incorporate married‐couple and single‐person families, appropriately accounting for changes in the proportion married. We apply the simulation method to investigate the impact of changes in male earnings, female earnings, and capital income on the distribution of family income in the United States between 1969 and 1999. We find that changes in the distribution of male earnings account for more of the growth in family income inequality than do changes in any other source of income. Changes in the distribution of female earnings have reduced family income inequality.     

The Intensity and Shape of Inequality: The ABG Method of Distributional Analysis

Inequality is anisotropic: its intensity varies by income level. We here develop a new tool, the isograph, to focus on local inequality and illustrate these variations. This method yields three coefficients which summarize the shape of inequality: a main coefficient, α, which measures inequality at the median; and two correction coefficients, β and γ, which pick up any differential curvature at the top and bottom of the distribution. The analysis of a set of 232 microdata samples from 41 different countries in the LIS datacenter archive allows us to provide a systematic overview of the properties of the ABG (α β γ) coefficients, which are compared to a set of standard indices including Atkinson indices, generalized entropy, Wolfson polarization, and the GB2 distribution. This method also provides a smoothing tool that reveals the differences in the shape of distributions (the strobiloid) and how these have changed over time.     

The Great Recession,Austerity and Inequality: Lessons from Ireland

The advent of the Great Recession and the widespread adoption of fiscal austerity policies have heightened concern about inequality and its effects. We examine how the distribution of income in Ireland—a country which experienced one of the most severe economic contractions—has evolved over the years 2008 to 2013. Standard cross‐sectional analysis of the income distribution shows broad stability in the Gini coefficient and in decile shares, with one main exception: the share of the bottom decile fell sharply, with the largest fall in average incomes being for that group. Longitudinal analysis shows that the falls in the average income for the bottom decile were not due to decreasing income for those remaining in the bottom decile, but to falls in income from those initially located in higher deciles. The extent of redistribution through taxes and transfers increased strongly, as measured by the Reynolds‐Smolensky index, which rose from 0.20 before the onset of the crisis to 0.27 in 2013. Analysis indicates that about three‐quarters of this increased redistribution is due to automatic stabilisers and one‐quarter to discretionary policy changes.     

Income inequality in China: causes and policy responses

The phenomenal economic growth in China has been accompanied by a rapid increase in income inequality. This paper reviews the historical trends and patterns of income inequality in China, discusses the potential causes underlying rising income inequality, and applies the functional distribution of income approach in understanding China’s income inequality. This analytical approach highlights how rising return to capital relative to wage incomes can be an important source for increasing income inequality in China. The paper provides the evidence which shows that the rapid economic growth in China has been relying on a model that pays high returns to various kinds of capital including financial capital and real estate, while the ownership of capital is very unequal. This finding prompts us to rethink about the causes of China’s income inequality and to formulate appropriate policies based on the new way of understanding this pressing issue of income distribution in China.     

POVERTY AND INCOME INEQUALITY IN PUERTO RICO, 1969–89: TRENDS AND SOURCES

The paper examines Puerto Rican trends in income distribution during the 1970s and 1980s, then attempts to ascertain the source of the changes in income inequality through a decomposition of the Gini coefficient by factor income source. The study finds that poverty and inequality declined unambiguously during the twenty-year period. The source of the fall in income concentration was found to have been tied, not to changes in the distribution or share of earned income, but to that of unearned income, particularly transfers. These appear to have also accounted for the decline in poverty.