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?     

GROWTH, INEQUALITY, AND POVERTY: A CAUTIONARY NOTE

Economic growth had less impact on poverty rates in the 1980s than in the 1960s. Could this be explained by Locke Anderson's observation that the higher median income, the greater the amount of growth needed to achieve a percentage point fall in the poverty rate? No, higher poverty rates are due instead to the rise in income inequality. With higher inequality, however, trickle down could be as effective in the 1990s as it was in the late 1960s. More generally, assessments of anti-poverty policy must recognize that inequality is as vital to changes in the poverty rate as growth in mean income.     

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.     

CHANGES IN CANADIAN FAMILY INCOME AND FAMILY CONSUMPTION INEQUALITY BETWEEN 1978 AND 1992

This paper uses Canadian cross-sectional income and expenditure data to examine changes in the distribution of family income and family consumption during the period 1978 to 1992. Family consumption data are analyzed because in the presence of intertemporal consumption smoothing, the cross-sectional distribution of consumption may characterize the distribution of lifetime wealth. I find that both Canadian family income inequality and Canadian family consumption inequality moved countercyclically. In addition, both Canadian family income inequality and Canadian family consumption inequality trended upward over the period; however, the change in family consumption inequality was much smaller than the change in family income inequality, suggesting that inequality in the distribution of lifetime wealth may have changed much less than is suggested by changes in the distribution of income.     

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.     

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。     

收入不平等与经济增长：移动的库兹涅茨曲线*——新时期收入分配改革的思路与意义

准确判断收入不平等对经济增长的影响，对于客观评价中国各个阶段的收入分配制度改革尤为重要。本文在统一增长理论的框架下引入收入不平等因素，构建了一个人口数量、不平等和经济增长同时内生的理论模型，并利用CGSS数据构造收入不平等指标，使用中国省际非平衡面板数据进行经验检验。研究发现：收入不平等与经济增长之间呈现倒U型关系。更重要的是，随着经济发展水平的提高，倒U型曲线将逐渐向左移动，即最优的收入不平等程度随着经济发展水平的提高而逐渐降低。这一发现意味着改革开放以来，中国各个时期的收入分配制度改革均是在特定历史条件下的最优选择。本文的结论具有深刻的政策含义：为了提高经济增长率，需要进一步巩固“脱贫攻坚”成果，逐渐加大收入分配调节力度，使收入分配制度改革紧跟经济发展的步伐，根据经济发展水平不断缩小收入不平等程度。     

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.     

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.     

INEQUALITY OF WAGE RATES,EARNINGS AND FAMILY INCOME IN THE UNITED STATES, 1975–2002

This paper analyzes distributional changes over the last quarter of the twentieth century. We focus on four distinct distributions: the distribution of hourly wage rates, the distribution of annual earnings of individuals, the distribution of annual earnings of families, and the distribution of total family income adjusted for family size. Both male wage rate inequality and family income inequality accelerated during the early 1980s, increased at a slower rate through the early 1990s and then stabilized at a high level through the early 2000s. The similarity in the timing of changes in these two distributions has been used as evidence that increased family income inequality primarily reflects increased inequality of wage rates. We show that other important factors were also at work.     

Income Inequality in Malaysia*

The objective of this paper is to examine the changes in Malaysian income distribution during the last three and a half decades and the reasons for the changes. It was found that the Gini ratio for Malaysia peaked in 1976 and fell thereafter to 1990. However, inequality seems to reverse its direction since then. Policies that could explain the changes in income distribution include the promotion of export‐oriented industrialization, education, and training, and the restructuring of equity ownership and assistance in asset accumulation. While the various other redistributive measures in the form of rural development helped in poverty eradication, their effectiveness in redistribution needs to be improved. Several hypotheses have been forwarded to explain the widening of income inequality after 1990. These include the difference in the growth rates of incomes of the rural and urban areas, trade and globalization, and impediments to the process of internal migration.     

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 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.     

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.     

POVERTY, TNEQUALTTY, AND FAMTLY LIVING STANDARDS IMPACTS ACROSS SEVEN NATIONS: THE EFFECT OF NONCASH SUBSIDIES FOR HEALTH, EDUCATION AND HOUSING

The main aim of this paper has been to summarize the impact of noncash income–health and health education benefits, and imputed rent-on living standards, income distribution and poverty in seven nations at the beginning of the 1980s using the Luxembourg Income Study database. Our results do not give rise to a pattern of national differences in poverty rates or income inequality which are markedly different from that which emerges from previous LIS research based on cash income alone. While these results may be sensitive to the techniques used to measure and value noncash benefits in this paper, it appears that noncash income reinforces the redistributive impact or conventional (cash) tax-transfer mechanisms rather than acting to offset them in any major way.     

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.     

Understanding Rising Income Inequality in Germany, 1999/2000–2005/2006

We examine the factors behind rising income inequality in Europe's most populous economy. From 1999/2000 to 2005/2006, Germany experienced an unprecedented rise in net equivalized income inequality and poverty. At the same time, unemployment rose to record levels, part‐time and marginal part‐time work grew, and there was evidence for a widening distribution of labor incomes. Other factors that possibly contributed to the rise in income inequality were changes in the tax and transfer system, changes in the household structure (in particular the rising share of single parent households), and changes in other socio‐economic characteristics (e.g., age or education). We address the question of which factors were the main drivers of the observed inequality increase. Our results suggest that the largest part of the increase was due to increasing inequality in labor incomes, but that changes in employment outcomes and changes in the tax system also contributed considerable shares. By contrast, changes in household structures and household characteristics, as well as changes in the transfer system only seem to have played a minor role.     

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.     

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.