Trends In Income Inequality Research Articles

Are We Really Addressing the Core of Children’s Environmental Health?

More than 3 million children 10 million child deaths annually throughout the world [World Health Organization (WHO) 2005]. Some factors of susceptibility, including race, ethnicity, and socioeconomic status, are generally not well understood in the context of risk assessment. For children’s environmental health the focus is almost exclusively on age-related differences and exposure hazards, without much discussion of the myriad additional factors including nutritional status, preexisting health status, multiple exposures, and gender differences that can affect the life course of a child.

USING THE P90/P10 INDEX TO MEASURE U.S. INEQUALITY TRENDS WITH CURRENT POPULATION SURVEY DATA: A VIEW FROM INSIDE THE CENSUS BUREAU VAULTS

The March Current Population Survey (CPS) is the primary data source for estimation of levels and trends in U.S. earnings and income inequality. However, time‐inconsistency problems related to top coding lead many CPS users to measure inequality via the ratio of the 90th to the 10th percentile (P90/P10) rather than by more traditional summary measures. With access to public use and restricted‐access internal CPS data, and by applying bounding methods, we show that using P90/P10 does not completely obviate time‐inconsistency problems, especially in capturing household income inequality trends. Using internal data, we create consistent cell mean values for all top‐coded public use values that, when used with public use data, closely track inequality trends in earnings and household income using internal data. But estimates of longer‐term inequality trends with these corrected data based on P90/P10 differ from those based on the Gini coefficient. The choice of inequality measure still matters.

Income inequality in tourism services-dependent counties

Income inequality has been increasing across the USA, but little is known about income inequality in tourism services-dependent counties. Using data from the 1990 and 2000 US Population and Housing Census, this study examines the patterns and trends of income inequality for tourism services-dependent counties. The analysis reveals that in the US tourism services-dependent counties have greater income inequality than non-tourism services-dependent counties. Furthermore, inequality has increased faster in tourism services-dependent counties than for the nation as a whole. Among tourism services-dependent counties, ski resort, coastal ocean resort, and South Appalachian mountain resort counties manifest the highest income inequality. In contrast, income inequality of northwoods lakes/second home areas and northeast mountains/lakes/second home areas is relatively low. The need for additional research on economic inequality in tourism services-dependent areas is also discussed.

Does Economic Integration Process Matter for Income Inequality in Central and Eastern European Countries?

Economic integration can be defined as the expansion of markets from the national to the regional or to the world level. Therefore, two channels of market integration can be determined: regional integration, for instance, within the EU, and globalization. The purpose of this paper is to investigate the impact of the economic integration process on differences in income among and within Central and Eastern European countries (CEECs). The hypotheses on 1) the economic integration relevance and 2) the mechanisms through economic integration affecting income inequality are tested with data on 10 CEECs (Bulgaria, Czech Republic, Estonia, Latvia, Lithuania, Hungary, Poland, Slovakia, Slovenia, Romania) for the 2000-2006 period. An unbalanced panel induces to estimate Random-effects regressions and fixed-effects regressions. The results show that globalization contributed significantly to income inequality among CEECs as well as to the upward trend in income inequality within the societies of these countries, while regional integration with and within the EU did not explain considerably the changes in income distribution over the study period.

Comment on “Inequality in Japan”

Comment on “Inequality in Japan”

Comment on “Income Inequality in Malaysia”

Comment on “Income Inequality in Malaysia”

Introduction: Globalization–Poverty Channels and Case Studies from Sub-Saharan Africa

In 2004 the United Nations University World Institute for Development Economics Research (UNU-WIDER) embarked on a large-scale research project on the ‘Impact of Globalization on the World’s Poor’ co-directed by Machiko Nissanke and Erik Thorbecke. The first conference was essentially conceptual in nature, meant to understand better the various mechanisms and channels through which globalization affects the poor either directly or indirectly. The other three conferences focused on each of the major regions of the developing world: Asia, Africa and Latin America. Theobjectivesofthisintroductionarethreefold:first,toreviewbrieflyhow the forces of globalization influence poverty in general; second, to describe and discuss the main transmission channels and mechanisms; and third to analyze the impact of globalization on Africa and present an overview of the six Africa case studies included in this issue. 1. The Impact of Globalization on the World’s Poor Globalization provides a strong potential for a major reduction in poverty in the developing world because it creates an environment conducive to fastereconomicgrowthandtransmissionofknowledge. 1 However,structural factors and policies within the world economy and national economies have impeded the full transmission of the benefits of the various channels of globalization for poverty reduction. In particular sub-Saharan Africa (SSA) hasbeenrelativelylessaffectedbytheforcesofglobalizationthanotherparts of the world. World income distribution continues to be very unequal and many poor countries particularly in Africa are stagnating. Moreover, there is much empirical evidence that openness contributes to more within-country

Equalizing or Not? The Effect of Changing Household Characteristics on Income Inequality

Among the various factors which have been explored to explain differences and trends in income inequality, there is one which has received relatively little attention: differences and changes in household characteristics. Using the data from the Bank of Italy Survey of Household Income and Wealth, this article examines the relationship between family demographic and economic characteristics and income inequality. More precisely, it analyses how much and in which direction (boosting vs. containing) recent changes in household forms have affected the level of income inequality in Italy. The analysis shows that the equalizing power of Italian families has decreased in recent decades, and that the most recent changes in household forms do not have a clear equalizing effect. On the other hand, it is also found that the relevance of income differences between household forms in determining the level of income inequality is on the increase.

Understanding the Trends in Income, Consumption and Wealth Inequality and How Important are Life-Cycle Effects?

Rising inequality in income, wealth and consumption has received a good deal of public attention in the past years. At the same time, also macroeconomists are more and more interested in inequality as they have expanded their models to incorporate heterogeneity in the household sector. We supply these models with empirical benchmarks for their calibration and contribute to the understanding of the reasons underlying the trends in inequality. Specifically, we employ a variance decomposition and estimate life-cycle profiles of inequality in income, consumption and wealth based on two measures of inequality. We deepen the discussion on wealth inequality by evaluating the relative importance of savings, portfolio choice and inheritances for the accumulation of wealth. To do so, we project active and passive savings based on the observed saving and investment behavior of synthetic cohorts from the German Income and Expenditure Survey (EVS).

Racing Away? Income Inequality and the Evolution of High Incomes

This Briefing Note provides an analysis of the characteristics of high-income individuals and how their incomes have evolved over time. We begin by setting out recent trends in overall income inequality and why these lead us to focus on the pattern of income growth at the very top of the income distribution. We then present some basic facts about high-income individuals and how they compare with the rest of society (for example, what is their average before-tax income, what is their average tax rate, how much of total personal income do they receive, in what industries do they tend to work?). We then discuss recent trends in their incomes over time and how this pattern compares with that for the rest of the income distribution. We then briefly summarise some recent research on longer-term trends in high incomes.

Estimating Trends in U.S. Income Inequality Using the Current Population Survey: The Importance of Controlling for Censoring

Using internal and public use March Current Population Survey (CPS) data, we analyze trends in US income inequality (1975-2004). We find that the upward trend in income inequality prior to 1993 significantly slowed thereafter once we control for top coding in the public use data and censoring in the internal data. Because both series do not capture trends at the very top of the income distribution, we use a multiple imputation approach in which values for censored observations are imputed using draws from a Generalized Beta distribution of the Second Kind (GB2) fitted to internal data. Doing so, we find income inequality trends similar to those derived from unadjusted internal data. Our trend results are generally robust to the choice of inequality index, whether Gini coefficient or other commonly-used indices. When we compare our best estimates of the income shares held by the richest tenth with those reported by Piketty and Saez (2003), our trends fairly closely match their trends, except for the top 1 percent of the distribution. Thus, we argue that if United States income inequality has been substantially increasing since 1993, such increases are confined to this very high income group.

Three faces of international inequality

Recent studies of international inequality have focused mostly on the trend in international income inequality. This article extends the analysis of international inequality to also include inequalities in education and health. Analyses of time-series data for more than 100 countries show that international income inequality declined from 1980 to 2003 as several large, poor Asian countries outpaced many Western countries in national income growth. By contrast, international health inequality followed a U-shaped trend, falling in the 1980s before rising in the 1990s. The turnaround in health inequality coincides with a trend of declining life expectancy in sub-Saharan Africa. International educational inequality experienced the sharpest recent decline, spurred by the global expansion of formal schooling. These findings confirm that there is more to international inequality than income inequality alone and suggest that patterns of inequality in the current era of globalization are likely more complex than many leading theories suggest.

Income Inequality Trends and their Challenges to Redistribution Policies in Japan

This article is an overview of income inequality trends during the 1980s and 1990s and a discussion of their challenges to redistribution policies in Japan. The key results are summarized as follows. First, a widening disparity in market income for the working-age population has been driving rising income inequality in society as a whole, while population aging has added to the uptrend. Second, wide income inequality for the aged population reflects high rates of co-residency and labor force participation among the elderly. This unique feature to the Japanese elderly explains the fact that population aging has led to a rise in overall inequality measures. Third, the current scheme of redistribution policies is less effective for reducing income inequality compared to other countries of the Organization for Economic Co-operation and Development countries (OECD), leaving distribution of disposable income relatively uneven in Japan.

Income inequality across Canadian provinces in an era of globalization: explaining recent trends

In this article, I use panel data methods to investigate possible factors influencing recent trends in income inequality across Canadian provinces. The ratio of the income share of the highest‐to‐lowest quintiles and the Gini coefficient of total income are used as measures of inequality. Both point to rising levels of inequality from 1981 to 1999, especially during the 1990s, and the estimation results suggest that several factors have had significant effects on such an increase. In particular, an increase in international trade, technological change, educational heterogeneity, and the unemployment rate are found to contribute to greater inequality. Deindustrialization and declining government transfer payments to persons are also factors explaining the rise in inequality. In contrast, an increase in the female labour force participation rate appears to have dampened inequality. There is also some evidence of a negative association between de‐unionization and inequality while no significant association is found between inequality and other demographic shifts, such as immigration and the share of the population over the age of 65.

Using the P90/P10 Index to Measure US Inequality Trends with Current Population Survey Data: A View from Inside the Census Bureau Vaults

The March Current Population Survey (CPS) is the primary data source for estimation of levels and trends in labor earnings and income inequality in the USA. Time-inconsistency problems related to top coding in theses data have led many researchers to use the ratio of the 90th and 10th percentiles of these distributions (P90/P10) rather than a more traditional summary measure of inequality. With access to public use and restricted-access internal CPS data, and bounding methods, we show that using P90/P10 does not completely obviate time-inconsistency problems, especially for household income inequality trends. Using internal data, we create consistent cell mean values for all top-coded public use values that, when used with public use data, closely track inequality trends in labor earnings and household income using internal data. But estimates of longer-term inequality trends with these corrected data based on P90/P10 differ from those based on the Gini coefficient. The choice of inequality measure matters.

Income Inequality and Redistribution Policies in Japan During the 1980s and 1990s

We examine the long-term trend of income inequality and the effects of redistribution policies over the past two decades in Japan. The key findings are as follows. First, more than half of the widening inequality is attributable to population aging and declining household size. Notably, the increasing share of the elderly who reside apart from their children has raised income inequality in terms of pre-tax pre-transfer income. Second, the effects of redistribution policies were concentrated on reducing inequality among the elderly, but most of the inequality was caused by income transfers from the young, and withinage redistribution was generally limited. Third, the younger cohorts tend to face greater inequality of disposable income, suggesting that the redistribution policies have become less progressive on a lifetimeincome basis.

Changing regional rural inequality in China 1980–2002

Regional rural inequalities in China since the reform are examined based on Theil's regional inequality index. By using data from the three zones (east, central and west) and provinces in the period 1980–2002, I find that China's rural regional inequality has an overall increasing trend with a short period of decrease during the entire reform period. However, the trends vary in different indicators and different geographical scales. The trend of income inequality does not always match that of rural economic inequality. The decomposition of Theil's regional inequality further reveals that, since 1987, interregional inequalities between the eastern, central and western regions have been more serious than provincial inequality within the regions themselves. For example, when rural non‐agriculture inequality decreased substantially within the east, it increased greatly within the west. Similarly, the income inequality increased within the west and the east but decreased within the central region. China's regional rural inequality remained at a high level and the coastal/interior income differential continued to increase.

Why Have Urban Poverty and Income Inequality Increased So Much? Argentina, 1991–2001

Abstract This article analyzes the trends in income inequality and poverty among Argentine households during the nineties. We assess the effect of changes in labor force participation, unemployment, educational levels, and returns to individual characteristics on income inequality and poverty by using a microsimulation approach. We found that unemployment accounts for a large part of the increase in income inequality and poverty experienced in the past decade. Changes in labor force participation had an equalizing effect over the whole period, while changes in the returns to workers’ sociodemographic characteristics could be associated with a small increase in income inequality. With respect to poverty, unemployment affected negatively the proportion of households below the poverty line, amplified the poverty gap, and increased the severity of poverty. In contrast, changes in labor force participation are associated with a reduction in the poverty rate.

Family structure and income inequality in families with children, 1976 to 2000

Using 24 years of data from the March supplements to the Current Population Survey and detailed categories of family structure, including cohabiting unions, I assess the contribution of changes in family structure to the dramatic rise in family income inequality. Between 1976 and 2000, family structure shifts explain 41% of the increase in inequality, but the influence of family structure change is not uniform within this period or across racial-ethnic groups. In general, the estimated role of family structure change is inversely related to the magnitude of the changes in inequality. Furthermore, by including cohabitation, I find lower levels of total inequality and a weaker role for demographic shifts in family structure for trends in income inequality.

Explaining macro-regional trends in global income inequalities, 1950–2000

This paper analyses levels and trends in within-country income inequality during the second-half of the 20th century. Two broad general trends were visible: beginning in the 1950s and 1960s inequality declined substantially in most countries, and in the 1980s and 1990s it increased more variably and more slightly. However, we focus here on presenting and explaining the distinct ‘macroregional’ regimes of inequality that became evident in this period. We identify six: Anglo, Nordic, Continental West European, Latin American, East Asian and South Asian. We show that intra-regional variations in inequality have been much less than inter-regional variations, and that the six regional regimes did not remain constant but had distinct trajectories through time. The Anglos were at first the most egalitarian, only later developing the greater inequality supposedly characteristic of their ‘liberalism’. The Nordics only became the most egalitarian in the middle of our period. The Euro-Continentals began as the most unequal among the Western countries, but then became almost as equal as the Nordics. Latin America began and remained the most unequal region of all. East Asia was rather egalitarian, while South Asia converged towards a middling inequality. Though pressures towards more inequality strengthened from 1980, regional responses remained varied and path-dependent. Then, in more speculative vein, we seek to explain these regional patterns in macro-sociological terms. Beginning from a model of dynamic interactions between economic, ideological, military and political power relations, we trace the political institutionalization of distinct macro-regional ideologies of ‘best practices’ of socio-economic development.