Inequality and growth: What comes from the different inequality measures?

The objective of the paper is to verify if income inequality impedes the growth rates in OECD countries in the period of 1990–2014 and to reveal whether the choice of the income inequality measure determines the sign and the strength of the estimated relationship. We use system GMM to estimate parameters of a dynamic panel growth model. The research indicates that income inequality negatively affects economic growth. We also find evidence that various measures of inequality bring the different scale of consequences for economic growth, with measures that give more weight to the middle part of the distribution being the weakest predictor of GDP growth. Simultaneously, we present the test of weak instruments, which helps to explain these differences.     

What causes violent crime?

This study uses panel data of intentional homicide and robbery rates for a sample of developed and developing countries for the period 1970-1994, based on information from the United Nations World Crime Surveys, to analyze the determinants of national crime rates both across countries and over time. A simple model of the incentives to commit crimes is proposed, which explicitly considers possible causes of the persistence of crime over time (criminal inertia). A panel-data based GMM methodology is used to estimate a dynamic model of national crime rates. This estimator controls for unobserved country-specific effects, the joint endogeneity of some of the explanatory variables, and the existence of some types of measurement errors afflicting the crime data. The results show that increases in income inequality raise crime rates, crime tends to be counter-cyclical, and criminal inertia is significant.     

Income Inequality and Economic Growth: Evidence from American Data

While most cross-country studies find a negative relationship between income inequality and economic growth, studies that use panel data suggest the presence of a positive relationship between inequality and growth. This paper uses a cross-state panel for the United States to assess the relationship between inequality and growth. Using both standard fixed effects and GMM estimations, this paper does not find evidence of a positive relationship between inequality and growth but finds some evidence in support of a negative relationship between inequality and growth. The paper, however, shows that the relationship between inequality and growth is not robust and that small differences in the method used to measure inequality can result in large differences in the estimated relationship between inequality and growth.     

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.     

Keeping up by robbing the Joneses

In this article, we find evidence of a ‘keeping up with the Joneses’ effect in the relationship between inequality and crime in Italy. We use data on minor and major crimes in the 20 Italian regions in the years 2004–2015 and show that for higher (lower) income levels, inequality leads individuals to commit major (minor) crimes to try to keep up with richer people.     

TOP INCOMES AND NATIONAL SAVINGS

The relationship between income inequality and national savings is theoretically ambiguous, and past empirical studies have delivered mixed results. We revisit the question using a newly available source of data on inequality: the income share of the richest 10 percent and the richest 1 percent. Combining this with historical data on national savings rates, we are able to investigate the relationship for 11 developed countries over the period 1921–2002. We find no consistent relationship between lagged top income shares and current savings rates, and our standard errors are small enough that we are able to reject more than modest effects in either direction. We view this as suggesting that inequality at the top end of the distribution is not a major driver of national savings rates.     

Volume and Quality of Infrastructure and the Distribution of Income: An Empirical Investigation

We provide evidence on the link between infrastructure development and the distribution of income for the period 1960–97. We use roads, railways, telecommunications, and energy measures. The approach is comprehensive as individual measures and composite indices are used. Cross-country and panel regressions are applied. In the latter, we apply GMM dynamic methods to minimize for endogeneity problems. We find that both quantity and quality of infrastructure are negatively linked with income inequality. The quantitative link tends to be stronger in developing countries than the qualitative link. These findings hold when using different econometric methods and most infrastructure measures.     

The tale of the tails: Canadian income inequality in the 1980s and 1990s

Abstract.  We present new evidence on levels and trends in after-tax income inequality in Canada between 1980 and 2000. We argue that existing data sources may miss changes in the tails of the income distribution, and that many of the changes in the income distribution have been in the tails. For this reason, we turn to an alternative source. In particular, we construct data on after-tax and transfer income using Census files augmented with predicted taxes based on information available from administrative tax data. Using these data, we find that Canadian after-tax inequality levels are substantially higher than has been previously recognized, primarily because income levels are lower at the bottom of the distribution than in commonly used survey data. We also find larger long-term increases in after-tax income inequality and far more variability over the economic cycle. This raises interesting questions about the role of the tax and transfer system in mitigating both trends and fluctuations in market income inequality.     

收入分配不平等对刑事犯罪的影响

本文利用1988—2006年中国省级面板数据,采用动态面板数据估计了收入分配不平等对刑事犯罪率的影响。研究发现,控制跨省人口迁徙、福利支出、失业率等因素并作相关的稳健性检验以后,以基尼系数度量的收入分配不平等上升1个百分点,刑事犯罪率将至少上升0.185个百分点,并且收入不平等程度不断上升会导致政府增加福利支出以降低刑事犯罪率;城市化会导致刑事犯罪率上升;提高人力资本水平和增加福利支出都会对遏制犯罪发挥重要影响。     

Neighbors' Income,Public Goods,and Well‐Being

How does neighbors' income affect individual well‐being? Our analysis is based on rich U.S. local data from the Behavioral Risk Factor Surveillance System, which contains information on where respondents live and their self‐reported well‐being. We find that the effect of neighbors' income on individuals' self‐reported well‐being varies with the size of the neighborhood included. In smaller areas such as ZIP codes, we find a positive relationship between median income and individuals' life satisfaction, whereas it is the opposite at the county, MSA, and state levels. We provide evidence that local public goods and local area characteristics such as unemployment, criminality, and poverty rates drive the association between satisfaction and neighbors' income at the ZIP code level. The neighbors' income effects are mainly concentrated among poorer individuals and are as large as one quarter of the effect of own income on self‐reported well‐being.     

Effects of monetary and government spending policy on economic inequality

Using detailed micro-level income and expenditure data, we study the effects of monetary and government spending policy shocks on income and expenditure inequality in the US from 1990 to 2018. We find that expansionary monetary and government spending policy shocks systematically decrease income, disposable income and expenditure inequality. There is evidence of time variation on the effects and monetary policy and transfer payment shocks. Various impulse responses suggest that the impacts of the policy shocks increase during and after the Great Recession. The responses of income and expenditures of households at different percentiles suggest that expansionary monetary and government spending policy have a larger positive impact on households with low income and expenditures relative to those at the top of the distribution. We do not find evidence of the significant impact of Quantitative Easing policies on income inequality, however, expenditure inequality appear to increase due to the policies.     

The distributional impact of public services when needs differ

Despite a broad consensus on the need to take into account the value of public services in distributional analysis, there is little reliable evidence on how inclusion of such non-cash income actually affects poverty and inequality estimates. In particular, the equivalence scales applied to cash income are not necessarily appropriate when including non-cash income, because the receipt of public services is likely to be associated with particular needs. In this paper, we propose a theory-based framework designed to provide a coherent evaluation of the distributional impact of local public services. The valuation of public services, identification of target groups, allocation of expenditures to target groups, and adjustment for differences in needs are derived from a model of local government spending behaviour. Using Norwegian data from municipal accounts and administrative registers we find that the inclusion of non-cash income reduces income inequality by about 15% and poverty rates by almost one-third. However, adjusting for differences in needs for public services across population subgroups offsets about half the inequality reduction and some of the poverty decrease.     

中国农村的收入差距与健康

随着收入差距的扩大,收入分配对健康和健康不平等的影响日益受到关注。本文利用中国健康营养调查(CHNS)1997年和2000年农村的面板数据回答两个问题:收入差距对健康的影响以及影响健康的方式;收入差距的扩大是否会导致健康不平等的加剧,尤其是低收入人群的健康是否受到更为不利的影响。研究发现,首先收入差距对健康的影响存在滞后效应;其次,收入差距对健康的影响呈现“倒U”型,在收入差距较高时,收入差距对健康的影响主要为负向的,一个可能的原因是收入差距影响到公共卫生设施的供给。再次,收入差距的扩大会加强收入效应,其含义是如果低收入人群的收入更容易受到负向冲击,那么收入差距对低收入人群的健康更为不利。     

Income Inequality in OECD Countries: Data and Explanations

There is much disagreement about both the facts and the explanationsof income inequality. Even if we confine attention to OECD countries,we find people arguing that there has been a great U-turn, withinequality rising sharply after its post war fall, and otherswho believe that the speed of change is glacial. In order toevaluate the historical record, we need data for a long runof years. The present paper reviews evidence about coveringthe period 1945–2001 for nine OECD countries. It is widelybelieved that rising inequality is attributable to technologicalchange and to globalisation. The second part of the paper arguesthat these are only part of a complex story. Household incomesdepend on public policy and on sources of income apart fromwork. What is happening at the top of the distribution may needto be explained quite differently. (JEL H0, E6)     

CORRUPTION AND INCOME INEQUALITY IN THE UNITED STATES

In this study we analyze the effects of corruption on income inequality. Our analysis advances the existing literature in three ways. First, instead of using one of the corruption indices assembled by various investment risk services, we use an objective measure of corruption: the number of public officials convicted in a state for crimes related to corruption. Second, we minimize the problems which are likely to arise because of data incomparability by examining the differences in income inequality across the United States. Finally, we exploit both time series and cross‐sectional variation in the data. We find robust evidence that an increase in corruption increases income inequality. (JEL D31, D73, I32)     

Crime and growth convergence: Evidence from Mexico

Scholars have often argued that crime hinders growth, but the empirical literature assessing such an effect is scarce. By exploiting cross-municipal income and crime data for Mexico, in this study we find evidence indicating that drug-related crime indeed deters growth.     

Crime and local inequality in South Africa

We examine the effects of local inequality on property and violent crime in South Africa. The findings are consistent with economic theories relating local inequality to property crime and also with sociological theories that imply that inequality leads to crime in general. Burglary rates are 25–43% higher in police precincts that are the wealthiest among their neighbors, suggesting that criminals travel to neighborhoods where the expected returns from burglary are highest. Finally, while we find little evidence that inequality between racial groups fosters interpersonal conflict at the local level, racial heterogeneity itself is highly correlated with crime.     

Income inequality and credit expansion in post-communist countries

There is an on-going debate on the antecedents and consequences of income inequality. Recent studies find that income inequality was a cause of the recent financial crisis. However, the findings on the inequality–indebtedness relationship are mixed and based on analyses of developed countries. The aim of this research is to test how income inequality influences borrowing in post-communist countries, whose financial markets are not very developed, which has important implications for income inequality. Therefore, we include financial system development in the analysis. We base our analysis on state-level panel data and find that income inequality will increase indebtedness in the private sector. However, these results are model and region specific. To preclude higher income inequality and the emergence of a financial crisis, policies should be directed towards improving the role of financial intermediaries and stock markets.     

Income, income inequality, and health: Evidence from China

This paper tests using survey data from China whether individual health is associated with income and community-level income inequality. Although poor health and high inequality are key features of many developing countries, most of the earlier literature has drawn on data from developed countries in studying the association between the two. We find that self-reported health status increases with per capita income, but at a decreasing rate. Controlling for per capita income, we find an inverted-U association between self-reported health status and income inequality, which suggests that high inequality in a community poses threats to health. We also find that high inequality increases the probability of health-compromising behavior such as smoking and alcohol consumption. Most of our findings are robust to different measures of health status and income inequality. Journal of Comparative Economics 34 (4) (2006) 668–693.     

Do liberalization and globalization increase income inequality?

Using the Standardized World Income Inequality Database, we examine if the KOF Index of Globalization and the Economic Freedom Index of the Fraser institute are related to within-country income inequality using panel data covering around 80 countries 1970–2005. Freedom to trade internationally is robustly related to inequality, also when adding several control variables and controlling for potential endogeneity using GMM. Social globalization and deregulation is also linked to inequality. Reforms towards economic freedom seem to increase inequality mainly in rich countries, and social globalization is more important in less developed countries. Monetary reforms, legal reforms and political globalization do not increase inequality.