State Income Inequality Research Articles

The price of inequality: How state tax policies widen the wealth gap

State taxation has become particularly regressive in recent decades. Across the country, states have increasingly begun to rely on sales and consumption taxes to fund significant portions of their expenditures. Given that these taxes disproportionately hurt lower classes that spend a larger portion of their income on consumable goods and services, these trends widen wealth gaps. By replacing and reducing progressive income taxes with these regressive forms of taxation, levels of inequality have risen. This paper examines the impact of such state and local taxes on the levels of income inequality within each state. Through empirical analysis, it identifies a substantial and positive correlation between the regressivity of state tax codes, as measured by the relative tax burdens on different income brackets, and the levels of inequality, as quantified by the income share of the top 1%. In this study, I examine the relationship between state tax policies and income inequality in the United States. By analyzing the tax structures of different states, I identify a significant correlation between regressive taxes, that disproportionately burden the less wealthy, and increased income inequality. Using quantitative data from 2013 to 2019, I show that states that rely more on taxes that burden working class families, like sales and excise taxes, witness larger portions of wealth concentration within the top 1%. These findings suggest that tax policy at the state level significantly shapes wealth distribution and highlight the need for reforms to reduce inequality at the state level.

Military expenditure and income inequality in European NATO Member States

The purpose of this investigation was to empirically assess the association between military expenditure and income inequality in the 19 European member states of NATO between 2011 and 2022. To achieve this, the authors carried out multivariate statistical analysis using Kaplan-Meier life tables and survival estimation techniques. The results highlighted a trend in the countries analysed that income inequality tended to decrease when investment in the military increased during the period under consideration. The association manifested itself in the shortest time in the group of countries with the lowest military spending per capita, while emerging in the longer term in the countries with the highest. Furthermore, under high threat of war, the association tends to be shortest in relative terms in countries with the lowest military expenditure per capita. The results also revealed that the association between military spending and income inequality is more pronounced in the smallest countries by population and those with the lowest military expenditure per capita. The authors believe that this investigation will enrich scientific knowledge with new insights.

Income inequality, economic openness and current account imbalances in new EU member states

Income inequality, economic openness and current account imbalances in new EU member states

Kernel Estimation of the Quintile Share Ratio index of Inequality for Heavy-tailed Income distributions

Evidence from micro-data shows that capital incomes are exceedingly volatile, which makes up a disproportionately high contribution to the overall inequality in populations with the heavy-tailed nature on the income distributions for many countries. The quintile share ratio (QSR) is a recently introduced measure of income inequality, also forming part of the European Laeken indicators and which cover four important dimensions of social inclusion (health, education, employment and financial poverty). In 2001, the European Council decided that income inequality in the European Union member states should be described using a number of indicators including the QSR. Non-parametric estimation has been developed on the QSR index for heavy-tailed capital incomes distributions. However, this method of estimation does not give satisfactory statistical performances, since it suffers badly from under coverage, and so we cannot rely on the non-parametric estimator. Hence, we need another estimator in the case of heavy tailed populations. This is the reason why we introduce, in this paper, a class of semi-parametric estimators of theQSR index of economic inequality for heavy-tailed income distributions. Our methodology is basedon the extreme value theory, which offers adequate statistical results for such distributions. Weestablish their asymptotic distribution, and through a simulation study, we illustrate their behaviorin terms of the absolute bias and the median squared error. The simulation results clearly showthat our estimators work well.

Pollution, income inequality and green finance in the new EU member states

Income inequality and pollution represent major challenges for the New EU Member States. In this context, the main objective of this paper is to check if income inequality enhances pollution in the EU-13 countries in the period 2002–2021. The results depend on the type of method that was employed (Fully Modified Least Square (FMOLS) estimators and method of moments quantile regression). In most of the cases, Gini index and gender pay gap have a negative impact on GHG emissions. An inverse U pattern is supported for the pollution—economic growth nexus. Foreign direct investment contributes to pollution, while renewable energy consumption proved to be the most efficient tool in the fight with pollution. For robustness check, in the period 2006–2021, the environmental protection investments of general government reduced the GHG emissions only in the long run. The results are the basis for the formulations of various proposals to reduce pollution in the New EU Member States.

Differences in access to social capital across societies

Abstract This paper explores country-level macro-structural conditions that are associated with social capital, measured as individuals’ access to social resources. To explain differences in social capital across societies, we formulate hypotheses based on welfare state generosity, cultural orientations (collectivism vs. individualism), and income inequality. We test our hypotheses using data from the International Social Survey Programme (ISSP) 2017, which comprises a total sample size of 50,010 individuals living in 33 countries. We use the position generator survey instrument to build two composite measures of social capital: the diversity and the socio-economic status of social contacts. Multilevel regression models reveal that diversity of social contacts is generally greater among individuals in countries with generous welfare states, while access to contacts of a higher socio-economic status is generally better among individuals in countries with higher levels of individualism. A country’s income inequality is not associated with the social capital of its citizens. However, the association between a person’s socioeconomic status and the diversity of their social capital is moderated by income inequality. As such, our study serves to demonstrate that macro-social conditions at the country level do influence individual social capital and have different implications depending on the dimension considered.

Sleepless in inequality: findings from the 2018 behavioral risk factor surveillance system, a cross-sectional study

BackgroundDespite the large body of research on the adverse effects of income inequality, to date, few studies have examined its impact on sleep. The objective of this investigation is to examine the association between US state income inequality and the odds for regularly obtaining inadequate (< 7 h) and very inadequate (< 5 h) of sleep in the last 24 h.MethodsWe analysed data from 350,929 adults participating in the US 2018 Behavioral Risk Factor Surveillance System (BRFSS). Multilevel modeling was used to determine the association between state-level income inequality, as measured by the Gini coefficient, and the odds for obtaining inadequate and very inadequate sleep. We also determined if associations were heterogeneous across gender.ResultsA standard deviation increase in the Gini coefficient was associated with increased odds for inadequate (OR = 1.06, 95% CI: 1.00, 1.13) and very inadequate sleep (OR = 1.11, 95% CI: 1.03,1.20). Also, a cross-level Gini Coefficient X Gender interaction term was significant (OR = 1.07, 95% CI:1.01,1.13), indicating that increasing income inequality was more detrimental to women’s sleep behavior.ConclusionFuture work should be conducted to determine whether decreasing the wide gap between incomes can alleviate the burden of income inequality on inadequate sleep in the United States.

The intersection of welfare stigma, state contexts and health among mothers receiving public assistance benefits

The stigmatizing nature of the US welfare system is of particular importance not only because it has shown to deter eligible applicants from participating in public assistance programs despite facing economic hardship, but also because stigma is an important fundamental cause of health inequities. Although scholars agree stigma is shaped by individual and contextual dimensions, the role of context is often overlooked. Given the heterogeneous nature of US state welfare environments, it may be critical to consider the ways in which state policy, social and economic contexts condition the relationship between welfare stigma and health. Using a multilevel lens, this study first examined the impact of experienced and perceived welfare stigma on self-reported health among female public assistance recipients with children. Second, we assessed the moderating effect of uneven state TANF policies, income inequality, and negative public welfare attitudes in shaping these associations. Using data from the Fragile Families and Child Wellbeing Study merged with state-level economic and social measures, we employed a series of multilevel logit models with random effects. Findings show experiences and perceptions of welfare stigma are significantly linked to poor health regardless of state contexts, and outcomes vary markedly by race, ethnicity and education. States with strong anti-welfare attitudes amplified the relationship between experienced welfare stigma and poor health for Black and Hispanic mothers, and state economic contexts modified the relationship between experienced welfare stigma and poor health for mothers with less than a high school education. TANF generosity had no moderating effect on health suggesting state policy environments have limited ability to protect welfare recipients against the stigmatizing effects of the US welfare system. Results have implications for explaining stigma related disparities in health within the context of U.S. welfare environments and informing policies that may be key levers for reducing health inequities.

The effects of U.S. county and state income inequality on self-reported happiness and health are equivalent to zero

PurposeA popular idea in the social sciences is that contexts with high income inequality undermine people’s well-being and health. However, existing studies documenting this phenomenon typically compare a small number of higher-level units (countries/regions). Here, we use local income inequality indicators and temporal designs to provide the most highly powered test to date of the associations between income inequality and self-reported happiness and health in the USAMethodWe combined county-level income inequality data (county-level Gini coefficients) with the responses from the General Social Survey (GSS) Cross-sectional dataset (13,000 + participants from ≈1000 county-waves) and Panels (3 × 3000 + participants from 3 × ≈500 county-waves); we used the GSS happiness (“not too happy,” “pretty happy,” or “very happy”) and health (“poor,” “fair,” “good,” or “excellent”) variables.ResultsMultilevel-ordered logistic models and equivalence tests revealed that the within-county effects of income inequality on self-reported happiness and health were systematically equivalent to zero. Additional analyses revealed that the within-state effects were identical, that using alternative measures of state income inequality led to the same conclusions, and that lagged effects (between + 1 and + 12 years) were never significant and always equivalent to zero.ConclusionThe present work suggests that—at least in the USA—income inequality is likely neither associated with self-reported happiness nor with self-reported health.

Income Inequality in Small States and the Caribbean: Stylized Facts and Determinants

Rising income inequality has emerged as a major policy issue facing policymakers, but there is a dearth of empirical work on inequality in small states, including the Caribbean. Despite data limitations, the empirical analysis using a sample of small states finds that increased openness and deeper economic integration including financial market openness is associated with lower income inequality, whereas elevated debt levels limit fiscal space and are associated with higher income inequality. An important policy implication is that well targeted social sector spending aimed at improving education and health indicators will support increased redistribution and reduce income inequality.

Income Inequality in Small States and the Caribbean

Rising income inequality has emerged as a major policy issue facing policymakers, but there is a dearth of empirical work on inequality in small states, including the Caribbean. Despite data limitations, the empirical analysis using a sample of small states finds that increased openness and deeper economic integration including financial market openness is associated with lower income inequality, whereas elevated debt levels limit fiscal space and are associated with higher income inequality. An important policy implication is that well targeted social sector spending aimed at improving education and health indicators will support increased redistribution and reduce income inequality.

Economic Complexity and Inequality: Does Regional Productive Structure Affect Income Inequality in Brazilian States?

Recent research on the effects of the productive structure of an economy has turned to examining whether economic complexity is associated with lower income inequality. In contrast to the commonly adopted approach that estimates the impact of economic complexity in a cross-country setting, we use panel data for Brazilian states to identify the relationship between economic complexity and income inequality at the sub-national level. Our findings show that the relationship between economic complexity and income inequality has an inverted U-shape, indicating that growing levels of complexity first worsen and then improve the income distribution in Brazilian states. Our findings also show that this relationship is particularly prominent in those states that have relatively high levels of urbanization and overall development. Furthermore, we identify separate effects on income inequality from the degree to which regional productive structures are characterised by diversity in terms of industries and occupations. These effects are particularly pronounced in less developed states with a more rural character. In combination, these findings confirm the important role that the productive structure plays in processes that drive improvements in income distributions and suggest that more research on this impact is warranted at the regional level.

Income Inequality in Small States and the Caribbean: Stylized Facts and Determinants

Income Inequality in Small States and the Caribbean: Stylized Facts and Determinants

Welfare State Spending, Income Inequality and Food Insecurity in Affluent Nations: A Cross-National Examination of OECD Countries

Few studies examine the distribution of food insecurity in advanced capitalist nations. This research investigates cross-national food insecurity in the world’s largest economies by estimating the impact of welfare spending and income inequality on food availability (measured by the FAO’s Dietary Energy and Protein Supply indicators) and food accessibility (measured by the Food Insecurity Experience Scale) in 36 Organization for Economic Cooperation and Development (OECD) countries between the years of 2000 and 2018. Using a series of regression models on panel and cross-sectional data this research found that increases in state spending on social and health care are associated with (1) increases in food availability and (2) increases in food access. However, the findings also suggest that increases in food supplies do not produce more food security. Thus, for the OECD countries in this analysis, food availability is unrelated to food accessibility. We conclude by suggesting that high income countries that seek to promote global health should not only focus their efforts on poverty reduction polices that increase food accessibility within their own boarders, but must simultaneously ensure a more equitable global distribution of food.

Statehood experience and income inequality: A historical perspective

This study investigates the effects of accumulated statehood experience on contemporary income inequality. Previous studies reveal numerous “proximate” causes of income inequality, but little is known about the fundamental determinants of this widespread social concern. The novelty of this paper lies in the adoption of a historical approach that sheds light on the deep historical roots of cross-country differences in income inequality. The central hypothesis is that statehood experience, measured by the extended state history index, exerts persistent impacts on present-day income inequality. Employing data for 128 countries, I find strong and robust evidence of a U-shaped relationship between state history and income inequality. Accumulated statehood experience, up to a point, strengthens fiscal and legal capabilities, leading to a more egalitarian distribution of income. However, excessive state experience is associated with early emergence of extractive institutions and powerful elites, resulting in persistent inequality. Further analyses suggest that the distributional effects of state history are mediated through institutions.

Population Change and Income Inequality in Rural America.

This paper examines the effects of population growth and decline on county-level income inequality in the rural United States from 1980 to 2016. Findings from previous research have shown that population growth is positively associated with income inequality. However, these studies are largely motivated by theories of urbanization and growth in metropolitan areas, and do not explicitly test for differences between the impacts of population growth and decline. Examining the effects of both forms of population change on income inequality is particularly important in rural counties of the United States, the majority of which are experiencing population decline. We analyze county-level data (N=11,320 county-decades) from the U.S. Decennial Census and American Community Survey, applying fixed-effects regression models to estimate the respective effects of population growth and decline on income inequality within rural counties. We find that both forms of population change have significant effects on income inequality relative to stable growth. Population decline is associated with increases in income inequality, while population growth is marginally associated with decreases in inequality. These relationships are consistent across a variety of model specifications, including models that account for counties' employment, sociodemographic, and ethno-racial composition. We also find that the relationship between income inequality and population change varies by counties' geographic region, baseline level of inequality, and baseline population size, suggesting that the links between population change and income inequality are not uniform across rural America.

State-level income inequality and the odds for meeting fruit and vegetable recommendations among US adults.

BackgroundPrevious research indicates that income inequality is associated with risk for mortality, self-rated health status, chronic conditions, and health behavior, such as physical activity. However, little is known about the relationship between income inequality and dietary intake, which is a major risk factor for common chronic diseases including heart disease, stroke, diabetes, and certain types of cancers. The objective of this study is to determine the association between US state income inequality and fruit and vegetable consumption among adults.MethodsCross-sectional data on 270,612 U.S. adults from the U.S. 2013 Behavioral Risk Factor Surveillance System was used. Fruit and vegetable consumption was assessed from the six-item fruit and vegetable frequency questionnaire, which is part of the Behavioral Risk Factor Surveillance System. Multilevel modeling was used to determine whether US state-level income inequality (measured by the z-transformation of the Gini coefficient) was associated with fruit and vegetable consumption adjusting for individual-level and state-level covariates.ResultsIn comparison to men, women were more likely to consume fruits and vegetables ≥5 times daily, fruits ≥2 times daily, vegetables ≥3 times of daily, and less likely to consume fruit juice daily. Among both men and women, a standard deviation increase in Gini coefficient was associated with an increase in consuming fruit juice daily (OR = 1.07, 95% CI = 1.03, 1.11). However, among women, a standard deviation increase in Gini coefficient was associated with a decreased likelihood in meeting daily recommended levels of both fruits and vegetables (OR = 0.93; 0.87–0.99), fruits only (OR = 0.95; 95% CI, 0.92–0.99) and vegetables only (OR = 0.92; 95% CI, 0.89–0.96).ConclusionsThis study is one of the first to show the relationship between income inequality and fruit and vegetable consumption among U.S. adults empirically. Women’s health is more likely to be detrimentally affected when living in a state with higher income inequality.

Income inequality and child maltreatment risk during economic recession

While several studies have examined the link between economic downturns and child maltreatment, the evidence linking economic downturns to child maltreatment is not consistent and cannot be generalized to the U.S. as a whole. This study builds on prior literature by extending the investigation of this association to 48 of the 50 U.S. states using National Child Abuse and Neglect Data System (NCANDS) data on child maltreatment reports from 2004 to 2013. Since the effects of economic recessions are not equally distributed in society, this study also examines whether the association between macroeconomic recessions (measured using large-scale involuntary job losses) and child maltreatment reports differs by the level of income inequality in states. Using a fixed-effects regression approach, we find that involuntary job losses are associated with increased rates of physical abuse reports, but not reports of other types of child maltreatment. We also find that the effects on reports on physical abuse and other types of maltreatment are largest in states with relatively low levels of income inequality. This surprising finding may be explained by the worse prospects of reemployment in low-inequality states, where families may experience more stress and uncertainty related to job losses.

Factors behind the changes in income distribution in the Baltics: income, policy, demography

ABSTRACTThis article aims at disentangling the factors behind changes in income inequality and relative poverty in the Baltic states. An evaluation of income, policy, and demographic effects was based on counterfactual scenarios constructed using tax-benefit microsimulation and reweighting techniques. Decomposition showed that income and policy effects were dominant for changes in inequality and relative poverty. The policy effects were inequality- and poverty-reducing after EU accession and before the 2008 financial crisis and as a whole. The income effects for the same periods were inequality- and poverty-increasing. Despite rapid demographic changes, the demographic effect on income inequality and relative poverty was marginal.

Income Inequality and Health: Expanding Our Understanding of State-Level Effects by Using a Geospatial Big Data Approach

Merging geospatial analytics with big data approaches provides a mechanism for leveraging and maximizing uses of traditional survey data to further extant work in meaningful ways. This study examines the income inequality hypothesis, which proposes that ecological (summary-level) income inequality is harmful for population health. However, findings from extant work are inconsistent across health outcomes and levels of geography. We contribute to this debate by applying a big data geospatial approach to create three innovative measures that capture uniformity in income inequality across counties within U.S. states. Using data from the Behavioral Risk Factor Surveillance System and American Community Survey, we evaluate multilevel models of individuals within states to examine the ways that income inequality, operationalized as the Gini coefficient, and three spatial uniformity measures that capture the way income inequality is dispersed across space within states, are associated with several health outcomes. Specifically, the uniformity measures capture the extent to which (1) inequality is uniformly distributed spatially in states regardless of whether the level is high or low, (2) the extent to which states are more uniformly high in inequality across space, and (3) the extent to which they are more uniformly low in inequality. We conclude that state income inequality did not predict worse health across these outcomes (and indeed was associated with lower odds of depression and obesity). However, residents of states that have more uniformly high inequality across space are more likely to report below-average health, cardiovascular disease, difficulty concentrating, and that they have not sought care because it was too expensive. We conclude with a discussion of how a big data geospatial approach can further contribute to research on this and other public health topics where scholars primarily rely on traditional survey data.