Decomposing US regional income inequality from 1969 to 2009

This article analyses changes in levels and composition of income inequality among US counties from 1969 to 2009. It also decomposes inequality using the Theil coefficient into between-State and within-State inequality. The article finds that income inequality has increased in the period studied with between-State inequality decreasing and within-State inequality increasing. We subsequently decompose income inequality into the proportion arising from differences in productivity and employment–population ratios across counties. The results suggest that inequality arising from differentials in labour productivity has fallen over the period studied while those arising from employment–population ratio differences have increased.     

Measuring inequality change in an economy with income growth

This paper analyzes how to measure changes in inequality in an economy with income growth. The discussion distinguishes three stylized kinds of economic growth:

• 1.(1) high income sector enrichment,
• 2.(2) low income sector enrichment,
• 3.(3) high income sector enlargement, in which the high income sector expands and absorbs persons from the low income sector.

Th e two enrichment types pose no problem for assessing inequality change in the course of economic growth: for high income sector enrichment growth, inequality might reasonably be said to increase, whereas for low income sector enrichment, inequality might be said to decrease. These adjustments are non-controversial and non-problematical. Where problems arise is in the case of high income sector enlargement growth. In that case, the two alternative approaches have been shown in this paper to yield markedly results:

• 1.(1) The traditional inequality indices generate an inverted-U pattern of inequality. That is, inequality rises in the early stages of high income sector enlargement growth and falls thereafter.
• 2.(2) The new approach suggested here, based on axioms of gap inequality and numerical inequality, generates a U pattern of inequality. That is, inequality falls in the early stages of high income sector enlargement growth and rises thereafter.

The discrepancy between the familiar indices and the alternative approach based on axioms of gap inequality and numerical inequality bears further scrutiny. Two courses of action are possible. One might try to axiomatize inequality in ways that generate an inverted-U pattern in high income sector enlargement growth, thereby rationalizing the continued use of the usual inequality indices with the inverted-U property. Alternatively, one might retain the axioms proposed here, embed them into a more formal structure, and construct a family of inequality indices consistent with them. Others might wish to pursue the first course; I am at work on the second.     

A refinement of the relationship between economic growth and income inequality

There is mixed evidence in the literature of a clear relationship between income inequality and economic growth. Most of that work has focused almost exclusively on developed economies. In what we believe to be a first effort, our emphasis is solely on developing economics, which we classify as high-income and low-income developing countries (HIDC and LIDC). We make such distinction on theoretical and empirical grounds. Empirically, the World Bank has classified developing economies in this manner since 1978. The data in our sample are also supportive of such classifications. We provide theoretical scaffolding that uses asymmetric credit constraints as a premise for separating developing economies in such a way. We find strong evidence of a negative relationship between income inequality and economic growth in LIDC to be in stark contrast with a positive inequality–growth relationship for HIDC. Both correlations are statistically significant across multiple econometric specifications. Using international data from 1960 to 2010, this article explores the effect of income inequality on economic growth using dynamic panel technique, such as system generalized method of moments (GMM) that is believed to mitigate endogenous problem. These results are strikingly contrasting to the previous estimation results of Forbes (2000) displaying significant positive correlation between two variables in the short to medium term.     

影响我国农村居民收入差距的主要因素:从收入构成角度的分解分析

This paper attempts to explore the causes behind the change of the inequality in China rural areas at the very beginning of this century by decomposing the inequality of the total per capita income into the contributions from different income components. Furthermore, we develop the decomposition method of Gini coefficients from the income components and use it not only in the static analysis but also in comparative static analysis. Namely it can be used to explore the change of the overall inequality by decomposing the change of Gini Coefficient from income components. The empirical results show that the wage from local employment, the income from agricultural household business and the incomes from non-agricultural household business are the three income components that made the largest contributions to the inequality of the total per capita income. The total contribution to the overall inequality of non-agricultural incomes was much more than that of agricultural incomes. The incomes from agricultural household business, the incomes from non-agricultural household business and the wages from migration made the positive impact on the increase of the overall inequality. The incomes donated by relatives and friends made the most important negative impact on the increase of the overall inequality.     

ICT and income inequality: a cross-national perspective

The importance of information and communications technology (ICT) for economic growth and development is widely researched and seemingly well understood, but the effect of such investments on income inequality is less well documented. On the one hand, improvements in infrastructure are expected to expand economic opportunities for previously underserved populations. On the other hand, ICT growth may exacerbate inequality due to differential access and skill premiums. We use panel data from 109 countries during the period 2001–2014 to examine the empirical connection between ICT and income inequality in a cross-national context. Our results suggest that the effect of ICT on income inequality depends both on the specific type of ICT and on the measure of income inequality. In addition, the magnitude of ICT’s effect on income inequality is comparable to that of more traditional forms of economic infrastructure. Finally, we find that the association between ICT and income inequality is conditional on other economic and political characteristics.     

Regional income inequality in China revisited: A perspective from club convergence

Growing income inequality in China has elicited considerable concern, and consensus has not been reached regarding whether regional income converges into one common steady state. The controversy may be attributed to the various definitions and methodologies for testing convergence. This study analyzes regional income inequality and convergence in China from the perspective of club convergence proposed by Phillips and Sul (2007). Instead of one convergence at the national level, we determine that provincial incomes are converging into two clubs: seven east-coastal provinces (Shanghai, Tianjin, Jiangsu, Zhejiang, Guangdong, Shandong, and Fujian) and Inner Mongolia are converging into a high income club, and the remaining provinces are converging into a low income club. In addition, we obtain strong evidence that income inequality within a club decreases, while that between clubs deteriorates over time. Between-club inequality is associated with investment in physical and human capital, as well as population growth rates.     

Growing income inequality due to biased technological change

Inequality is rising in many countries. This paper presents a growth model in which technological change increases the income share of reproducible factors at the expense of non-reproducible ones. Agents are heterogeneous in wealth. Preferences imply that the saving rate increases with wealth. Consequently, assets (reproducible factor) are less equally distributed than raw labor (non-reproducible factor). This implies that technological change raises the share of the less equally distributed factor, increasing inequality along permanent growth path. When reproducible factors and the state of know-how are low, to adopt new technologies is not profitable, learning-by-doing and technological change ceases, arising stagnation.     

The effect of growth volatility on income inequality

This paper assesses the long-run effect of growth volatility on income inequality using a comprehensive panel of annual U.S. state-level data during the 1945 to 2004 period. Using the pooled mean group (PMG) estimator, we find evidence supporting the hypothesis that larger growth volatility positively and significantly associates with higher income inequality. Our key finding is robust to alternative lag structures, conditioning variables, inequality measures, volatility indicators, time periods, and panel estimators. Our key finding does change for asymmetric effects, where larger growth volatility positively and significantly associates with higher income inequality only for positive economic growth. The volatility effect proves positive, but insignificant, for negative economic growth.     

Status-seeking behavior,the evolution of income inequality,and growth

Using an overlapping generations model, this paper investigates the implications of status-seeking behavior, induced by preferences for relative income, for the evolution of income inequality. When average income rises, an individual’s marginal utility of their own income may increase (keeping up with the Joneses, or KUJ), or decrease (running away from the Joneses, or RAJ). It is shown that income inequality is shrinking over time in the KUJ economy, whereas it is expanding in the RAJ economy. We also explore the implications for long-run growth and inequality, in the existence of both KUJ and RAJ agents. I am truly grateful to Koichi Futagami for his encouragement and guidance in writing this paper. I have benefitted from comments by an anonymous referee, Been-Lon Chen, Giacomo Corneo, Akiomi Kitagawa, Kazuo Mino, Kazuhiro Yuki, and seminar participants at Osaka University, the 2006 Japanese Economic Association Autumn Meeting at Osaka City University, the Far Eastern Meeting of Econometric Society 2007 at Taipei, SER Conference 2007 at Singapore, and the European Meeting of Econometric Society 2007 at Budapest. All remaining errors are, of course, my own. The financial support from JSPS Research Fellowships for Young Scientists is greatly acknowledged.     

Estimating the long-run relationship between income inequality and economic development

There are several theories describing the effect of income inequality on economic growth. These theories usually predict that there exists some optimal, steady-state growth path between inequality and development. This study uses a new measure of income distribution and panel data cointegration methods to test for the existence of such a steady-state equilibrium relation. It is shown that there is a long-run equilibrium relationship between the variables, and that this relationship is negative in developed economies.     

Does the relationship between income and child health differ across income groups? Evidence from India

This study explores the relationship between child health and socioeconomic status (health-income gradient) using the Indian Human Development Survey-II (2011-12) for children up to 5 years of age. Unlike previous studies our empirical analysis allows the gradient to vary across different income intervals using linear and cubic spline regressions. We use objective measure of child health - height-for-age Z-scores and find that an increase in income, on an average leads to reduction in prevalence of stunting. We also find differential effect of income on health across the income distribution with no effect of income on child health for very poor households. Further we explore underlying factors explaining the gradient and find that maternal health, housing quality, sanitation, non-infectious environment, media exposure to women and a safe neighbourhood are transmission channels that affect child health and together they explain almost 40% of the overall income effect. One of the major implication of our findings is that any policy to increase income of poor households should be complemented with a health policy designed specifically towards children as poor households are less likely to allocate additional income to child health.     

The effects of economic growth on income inequality in the US

The paper analyzes the relation between growth and income inequality in the US during the post-war years (1953–2008). We show that the income of the top income groups is more sensitive to growth, defined broadly as current growth and changes in expectations of future growth, compared to the income of the lower income groups. We provide evidence that this increased sensitivity arises for two reasons: (a) the top income groups receive a large portion of their income from wealth, which is more sensitive to growth than labor income and (b) the top income groups receive a large portion of their labor income in the form of pay-for-performance (equity compensation), which is also sensitive to growth. Consequently, we conclude that growth and income inequality are positively associated.     

Finance,income inequality and income redistribution

Using a panel fixed effects model for a large sample of countries covering 1975–2005, we test the hypothesis that income inequality caused by finance (financial development, financial liberalization and banking crises) is related to more income redistribution than inequality caused by other factors. Our results provide evidence in support of this hypothesis. We also find that the impact of inequality on redistribution is conditioned by ethno-linguistic fractionalization. Our findings are robust to the inclusion of several control variables suggested by previous studies.     

Regional differences and the components of growth and inequality change

Inequality change can be decomposed simply in terms of per capita income and population changes, using the Gini index. An illustration based on U.S. data for the two intercensus periods 1960–1970 and 1970–1980 is given. This decomposition analysis is also applied to the study of changes in a welfare index originally proposed by Sen.     

Is there a trade-off between income inequality and corruption? Evidence from Latin America

In contrast to other research, lower corruption is associated with higher income inequality. This result is consistent with the idea that the corruption–inequality relationship may be different where there is a large informal sector, as in Latin America.     

Educational opportunity and income inequality

Affordable higher education is, and has been, a key element of social policy in the United States with broad bipartisan support. Financial aid has substantially increased the number of people who complete university—generally thought to be a good thing. We show, however, that making education more affordable can increase income inequality. The mechanism that drives our results is a combination of credit constraints and the ‘signaling’ role of education first explored by Spence [Spence, A. Michael, 1973. Job Market Signalling, Quarterly Journal of Economics, 87(3) Aug., 355–374]. When borrowing for education is difficult, lack of a college education could mean that one is either of low ability or of high ability but with low financial resources. When government programs make borrowing or lower tuition more affordable, high-ability persons become educated and leave the uneducated pool, driving down the wage for unskilled workers and raising the skill premium.     

Political regimes and income inequality

We construct a theoretically-motivated model of income inequality. Through a pooled regression on an international panel, we demonstrate that political regime (whether extractive, redistributive, or reinvestment-oriented) correlates with within-country income inequality.     

Capitalist systems and income inequality

The paper investigates the relationship between compositional inequality (how the shares of capital and labor income vary along income distribution) and inter-personal income inequality. Using a new methodology and data from 47 countries covering the period 1995–2018, we show that higher compositional inequality is associated with higher inter-personal inequality. This is clearly shown by Latin American countries and India. Nordic countries are exceptional because they combine high compositional inequality with low inter-personal inequality. Their exceptionalism is attenuated when pension income received from largely government-mandated accumulated savings is added to capital income. The analysis shows the theoretical possibility of societies where low compositional inequality may be combined with high income inequality. Currently, China and the United States come closest to that position.     

Technological progress and income inequality

Summary This paper examines the effects of Hicks-neutral, Harrod-neutral, and Solow-neutral technological improvements on the distribution of income in an overlapping generations economy with endogenous labor supply and a bequest motive. Income inequality in this model is generated by a stochastic process representing random variations in intergenerational transfers and pure luck. The comparative dynamics analysis trace the effects of the aforementioned technological changes in each and every period after they occur. These effects depend on the nature of the technological change and on the elasticity of substitution.We thank Carl Davidson, James Foster, and two anonymous referees for their useful comments.