Economic Growth Evens Out Happiness: Evidence from Six Surveys

In spite of the great U‐turn that saw income inequality rise in Western countries in the 1980s, happiness inequality has fallen in countries that have experienced income growth (but not in those that did not). Modern growth has reduced the share of both the “very unhappy” and the “perfectly happy.” Lower happiness inequality is found both between and within countries, and between and within individuals. Our cross‐country regression results suggest that the extension of various public goods helps to explain this greater happiness homogeneity. This new stylized fact arguably comes as a bonus to the Easterlin paradox, offering a somewhat brighter perspective for developing countries.     

Aging and inequality: The link and transmission mechanisms

There exists a shortage of rigorous empirical analyses that focus on the aging‐to‐inequality transmission mechanisms although both developed and some developing countries have been confronted with the challenge of population aging. Using cross‐country panel data covering the period of 1975 to 2015, this paper contributes to the literature by directly modeling the relationship between aging and inequality and exploring the transmission mechanisms. Our estimation results show that (1) Aging worsens income distribution; (2) This adverse impact is attributable to its negative correlation with the share of labor income that in general is more equally distributed than capital income; (3) The labor share‐reducing effect of aging can be further attributed to the significant and negative impact of aging on both labor input or supply and wage or labor productivity; and (4) Our findings are robust to changes in model specifications, use of different indicators of aging, different inequality and labor share data sources.     

Wealth inequality and financial inclusion: Evidence from South African tax and survey records

Theoretical models show that financial inclusion reduces wealth inequality. Existing empirical models are restricted to estimates using income inequality because of a lack of cross country wealth inequality data. We used 2010-11 and 2014-5 waves of the National Income Dynamics Study combined with South African tax records to estimate wealth and income inequality. Using Re-centered Influence Function regressions on the micro-level records, we confirmed the negative cross-country relationship between financial inclusion and income inequality. Wealth inequality is different. Financial inclusion improved wealth shares of only the middle class. Because of predatory lending, expansion of credit reduced the wealth share of the poor. Improved savings by the middle class, providing better oversight over financial services targeted at the poor and removing impediments to the small business sector are pre-conditions for financial inclusion to reduce wealth inequality.     

Genetic distance,economic growth and top income shares: Evidence from OECD countries

The relationship between economic growth and income inequality remains a puzzle in the literature. The main problem has been finding a way to account for the endogeneity of growth. Using century-long data of 14 OECD countries, this study disentangles the growth–inequality relationship. In doing so, our main contribution is employing genetic and geographical distances as instruments for economic growth. The instruments are constructed on the premise that the growth of one country spills over to the others if they are connected through trade and other forms of exchange; however, the genetic and geographical distances between countries represent barriers to such spillovers. Using alternative specifications and measures, we find that growth reduces the inequality measured by top income shares. As capital share increases in the growth process and capital substitutes labour, inequality-reducing strength of growth declines. Another important finding is that the effect of growth on top income shares is more significant among the highest income groups.     

Income Inequality and Macroeconomic Volatility: An Empirical Investigation

We explore the impact of macroeconomic volatility on the distribution of income. Using a cross‐section of developed and developing countries, we find that greater output volatility, defined as the standard deviation of the rate of output growth, is associated with a higher Gini coefficient and income share of the top quintile. The coefficients suggest that a strong effect on inequality resulting from a reduction in volatility: the Gini coefficient of a country like Chile would fall by 6 points if it were to reduce its volatility to the same level as Sweden or Norway. Our results seem not to be driven by the high‐inequality/high‐volatility Latin American countries.     

Inequality and credit growth in Russian regions

We test the Rajan hypothesis using data for Russian regions from 2000 (after the ruble crisis) to 2012 (before the introduction of international sanctions). The Rajan hypothesis predicts that rising income inequality leads politicians to expand credit for the poor, which in turn, fuels a consumer credit boom. Russia provides a unique research opportunity becaise it is a post-communist transition country with 75 diverse regions. We find that a rise in income inequality is positively correlated with personal loan growth in Russia. We also find a statistically weaker, albeit economically larger, relationship between economic inequality and corporate credit. Taken together, our results provide support for the Rajan hypothesis in a country with extreme regional differences and a long history of populist policies.     

State‐owned Enterprises,Inequality, and Political Ideology

State‐owned enterprises continue to play a considerable role in many economies. In this study we empirically investigate the connections between these enterprises and inequality as mediated through political ideology. Using cross‐country data on the relative size of the state‐owned enterprise sector, we find strong empirical support for an inverted U‐shaped relationship between its size and income inequality. We also find strong evidence that left‐wing (vis‐a‐vis right‐wing) governments are associated with a larger state‐owned enterprise sector in countries with higher inequality. This result is robust to using cross‐sectional vs. panel data, different identification strategies, and various controls.     

Foreign direct investment and inequality in developing countries: Does sector matter?

Scholars have studied the relationship between inward foreign direct investment (FDI) and within‐country income inequality in cross‐national contexts, but have not empirically investigated how FDI in different sectors might affect inequality in different ways. We use error correction models to analyze sectoral FDI data compiled from UNCTAD investment reports in 60 middle‐income countries from 1989 to 2010, arguing that FDI in services is more likely to be associated with inequality than FDI in other sectors. We argue that skill biases and changes in employment patterns associated with service sector investments can help explain these findings.     

我国收入差距与经济增长的面板协整与因果关系研究

笔者运用最近发展起来的面板协整技术,分析了我国收入差距与经济增长的关系。研究结果表明,全国以及东中西部的收入差距与经济增长之间存在长期的稳定关系;尽管对于全国和东部地区,收入差距和经济增长的因果关系并不明显,但对于中部和西部,收入差距和经济增长之间存在长期和短期的因果关系。     

A META‐ANALYSIS ON THE RELATIONSHIP BETWEEN INCOME INEQUALITY AND ECONOMIC GROWTH

In recent years there is a growing interest in determining the impact of inequality on economic growth. Theoretical papers as well as empirical applications have, however, produced controversial results. Although there is a considerable part of the literature that considers inequality detrimental to growth, more recent studies have challenged this result and found a positive effect of inequality on growth. In this paper, we provide a contribution to the empirical puzzle by using meta‐analysis to systematically describe, identify and analyse the variation in outcomes of empirical studies. We find that estimation methods, data quality and sample coverage systematically affect the results. The results point out that it will be particularly useful to increasingly focus research on determining the impact of income inequality on economic growth using single‐country data at the regional level, or a relatively homogeneous set of countries with adequate controls for country‐wide differences in economic, social and institutional characteristics.     

A panel analysis of income inequality and energy use

This paper investigates the relationship between energy consumption and income inequality in an unbalanced panel of 144 countries over the period 1990–2018. Using fixed effect and instrumental variable panel methods and controlling for other determinants of inequality, I find a large and strong negative relationship between energy use and income inequality. The paper also demonstrates that results hold for models which divide the total sample into subsamples of economic blocs and regions. In addition, greater energy use reduces the income share of the top 10% and increases the share of the bottom 40%.     

LIFE SATISFACTION AND INCOME INEQUALITY

Do people care about income inequality and does income inequality affect subjective well‐being? Welfare theories can predict either a positive or a negative impact of income inequality on subjective well‐being and empirical research has found evidence of a positive, negative, or non‐significant relation. This paper attempts to determine some of the possible causes of such empirical heterogeneity. Using a very large sample of world citizens we test the consistency of the effect of income inequality in predicting life satisfaction. We find that income inequality has a negative and significant effect on life satisfaction. This result is robust to changes of regressors and estimation choices and also persists across different income groups and across different types of countries. However, this relation is easily obscured or reversed by multicollinearity generated by the use of country and year fixed effects. This is particularly true if the number of data points for inequality is small, which is a common feature of cross‐country or longitudinal studies.     

The relationship between inequality and innovative activity: a Schumpeterian theory and evidence from cross‐country data

This article examines the effect of inequality on technological progress when innovations are protected by patents of finite length. It provides a Schumpeterian theory of the non‐linear relationship between income distribution and innovative activity in a dynamic general equilibrium setting. Additionally, the theory is empirically tested by investigating how inequality affects innovative activities in a cross‐country setting. Using two new data sets on inequality, one linear and two non‐linear dynamic panel data models are estimated. The results are robust to two common inequality measures. They support the hypothesis that there is an overall negative relationship between inequality and innovative activity and the relationship is non‐linear but not necessarily an inverted‐U.     

Inequality,poverty and development

Dicussion explores the nature of the relationship between the distribution of income and the process of development on the basis of cross country data on income inequality. The results presented are based on a sample of 60 countries, including 40 developing countries, 14 developed countries, and 6 socialist countries. The approach adopted is essentially exploratory. Multivariate regression analysis was used to estimate cross country relationships between the income shares of different percentile groups and selected variables reflecting aspects of the development process which are likely to influence income inequality. The estimated equations are then used as a basis for broad generalizations about the relationship between income distribution and development. There was strong support for the proposition that relative inequaltiy increases substantially in the early stages of development, with a reversal of this tendency in the later stages. The propositions held whether the sample was restricted to developing countries or expanded to include developed and socialist countries. The process was most prolonged for the poorest group. There were a number of processes occurring "pari passu" with development which were correlated with income inequality and which can plausibly be interpreted as causal. These were intersectoral shifts in the structure of production, expansion in education attainment and skill level of the labor force; and reduction in the growth of population. The operation of these processes appeared to explain some of the improvement in income distribution observed in the later stages of development, but they did not serve to explain the marked deterioration observed in the earlier stages. The cross section results failed to support the stronger hypothesis that the deterioration in relative inequality reflected a prolonged absolute impoverishment of large sections of the population in the course of development. The cross country pattern showed average absolute incomes of the lower percentile groups rising as per capita gross national product rises, although slower than for upper income groups. The cross section results failed to support the view that a faster rate of growth is systematically associated with higher inequality than can be expected given the state of development realized. An appendix identifies data sources and problems.     

Global and regional inequality in the distribution of income: Estimation with limited and incomplete data

The paper examines the nature and extent of global and regional inequality using the most recent country level data on inequality drawn from World Bank studies, and real per capita income from the Penn World Tables, for the period 1980–1990. The methodology employed in the paper is based on a mixture of parametric and non-parametric approaches to inequality measurement. It is designed to handle the limited and incomplete nature of income distribution data from different countries. Empirical results show a very high degree of global inequality, but with some evidence of catch-up and convergence between regions.     

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.     

CONTRADICTORY TRENDS IN GLOBAL INCOME INEQUALITY: A TALE OF TWO BIASES

Did global income inequality rise or fall over the last decades of the twentieth century? The answer depends on how cross‐country income comparisons are made. Exchange rate comparisons suggest that inequality rose whilst the purchasing power comparisons of the Penn World Table suggest it fell. We show that both measures of real incomes lead to biased international income comparisons. Exchange rate comparisons ignore the relative price of non‐tradables, whilst the fixed price method underlying the Penn World Table is subject to substitution bias. The contradictory trends are due to growing dissimilarity between national price structures increasing the degree of bias in each method. When we correct the income data to eliminate bias we find no compelling evidence of a significant change in world inequality.     

Population increase,economic growth,educational inequality,and income distribution: some recent evidence

The relationship between population increase, economic growth, education and income inequality was examined in a cross-section study based on data from 26 developing and 2 developed countries. As other studies have noted, high population growth is associated with a less equal income distribution. A 1 percentage point reduction in the rate of population growth tends to raise the income share of the poorest 80% in the less developed world by almost 5 percentage points and is associated with a 1.7 percentage point increase in the income share of the poorest 40%. The relationship between short-run income growth and equality, on the other hand, is strong and positive. Estimates suggest that a 1 percentage point increase in the short-run rate of growth of the gross domestic product (GDP) increases the income share of the bottom 80% by about 2 percentage points and that of the poorest 40% by almost 1 percentage point. Although higher mean schooling appears to be a mild equalizer, educational inequality does not appear to have an adverse effect on income distribution. Overall, these results challenge the widely held belief that there must be a growth-equity trade-off. Moreover, they suggest that the impact of educational inequality on income distribution may be different from that observed in earlier studies, implying a need for caution in using these earlier results as a basis for educational policy development.     

Trade and Inequality with Limited Labor Mobility: Theory and Evidence from China

Does globalization increase inequality in developing countries, and if so, how? In a theoretical model of a regionally heterogeneous economy, we show how different regional rates of technical progress due to trade and FDI interact with constraints to unskilled labor mobility. As favored regions benefit more from trade, their growing demand for skills drains skilled workers from disadvantaged areas, and average incomes in the former grow faster than in the latter. Moreover, this unbalanced regional growth may also raise inequality within each region. It could even reduce absolute income per capita in the less favored region. We test these predictions with Chinese data from the Open Door era. Results confirm that different regional growth rates have increased both interregional and intraregional inequality. Moreover, growth of skills‐based export industries in coastal regions is associated, other things equal, with lower incomes for the poor in inland provinces.     

Regional Inequality and Internal Conflict

This paper studies the influence of regional inequality within countries on internal conflicts. Regional inequalities are measured by the population‐weighted coefficient of variation of regional GDP per capita. As the main innovation, I use a panel dataset of country‐level regional inequalities, which covers 56 countries (835 subnational regions) between 1980 and 2009. I also consider a broader cross section dataset for the year 2005, which covers 110 countries (1569 subnational regions). Conflict is measured by the incidence of civil war (UCDP/PRIO data) and a risk measure of internal conflict (war, terrorism and riots) provided by the PRS Group's International Country Risk Guide. Logit estimations are employed as well as OLS fixed effects panel regressions. I find that regional inequalities increase the risk of internal conflict.