Measures Of Income Inequality Research Articles

Digital divide, globalization and income inequality in sub-Saharan African countries: analysing cross-country heterogeneity

PurposeThis study aims to analyse the impact of digital divide (DD) on income inequality in sub-Saharan Africa over the period 2004–2016.Design/methodology/approachIn applying a finite mixture model (FMM) to a sample of 35 sub-Saharan African (SSA) countries, this study posits that DD affects income inequality differently.FindingsThe findings show that the effect of DD on income inequality varies across two distinct groups of countries, which differ according to their level of globalization. In addition, the study shows that most globalized countries are more inclined to be in the group where the effect of DD on income inequality is negative. The results are consistent with several robustness checks, including alternative measures of income inequality and additional control variables.Originality/valueThis study complements that extant literature by assessing linkages among the DD, globalization and income inequality in sub-Saharan African countries contingent on cross-country heterogeneity.

Does income inequality affect individual happiness? Evidence from Seoul, Korea

Positive neighborhood characteristics are important for quality of human live. However, our understanding of the effects of intangible factors on individual subjective well-being remains limited. Among other intangible neighborhood variables, income inequality should be carefully assessed by planners at the neighborhood level because leaving it unaddressed may make communities unsustainable. However, relatively little attention has been paid to the relationship between income inequality and happiness at the neighborhood level in the previous literature. In this study, we investigate how small-scale income inequality affects individual happiness, focusing on the city of Seoul, Korea. To do this, we employ an ordered-probit model using Seoul Survey Data and micro income data obtained from a private sector to measure income inequality. Our empirical analyses show that income inequality is negatively associated with individual subjective well-being. In particular, findings show that the relationship between income inequality and individual subjective well-being varies by income, education level, and age. To reduce spatial income inequality, we suggest that various place-based planning strategies, including provision of affordable housing, relaxed zoning requirements, and increased social mix, be provided.

Assessing spatial inequality in cancer service access in regional areas

This paper applies economic concepts from measuring income inequality to an exercise in assessing spatial inequality in cancer service access in regional areas. We propose a mathematical model for accessing chemotherapy among local government areas (LGAs). Our model incorporates a distance factor. With a simulation we report results for a single inequality measure: the Lorenz curve is depicted for our illustrative data. We develop this approach in order to move incrementally towards its application to actual data and real-world health service regions. We seek to develop the exercises that can lead policy makers to relevant policy information on the most useful data collections to be collected and modeling for cancer service access in regional areas.

Income Inequality Measurements through Tax Data: the case of Greece

Abstract The goal of this research was to measure income inequality and the distribution of the tax burden in Greece, by using open tax data released by the Greek Independent Authority of Public Revenues. The findings reveal multiple distortions in the disperse of tax burden among taxpayers’ income groups, along with very high income inequality among the population. The calculated Gini coefficient and S80/S20 ratio were found to be considerably higher than any previous measurements performed by international organizations and European statistical authorities through household surveys. The findings indicate an urgent need for an income and tax policy overhaul in the country, while the methodology that was used in the research can be replicated in other countries. JEL classification number: D63, H2, O2. Keywords: Tax, Income inequality, Greece, Gini coefficient.

Income Inequality, Race/Ethnicity, and Obesity in U.S. Men 20 Years and Older: 1999 to 2016.

Obesity is a significant public health problem globally and within the United States. It varies by multiple factors, including but not limited to income. The literature indicates little evidence of the association between income and obesity. We examined the association between income and obesity in U.S. adult men ages 20 years and older and tested racial and ethnic differences. We used data from the 1999 to 2016 National Health and Nutrition Examination Surveys for analyses. Obesity was determined using body mass index ≥30 kg/m2. We used poverty income ratio (PIR) as a proxy for income and calculated the Gini coefficient (GC) to measure income inequality. We then categorized low-, medium-, and high PIR to examine the relationship between income inequality and obesity. We used Modified Poisson regression in a sample of 17,238 adult men, including 9,511 White Non-Hispanic White (NHW), 4,166 Non-Hispanic Black (NHB), and 3,561 Mexican Americans (MA). We controlled the models for age category, racial and ethnic groups, marital status, education, health behaviors, health insurance coverage, self-reported health, comorbidity, and household structure. Results of our adjusted models suggested a positive and significant association between PIR and obesity among NHWs and NHBs in medium and high PIR; this association was not significant in MAs. Results of our analyses using GC in obese men indicate that compared with NHWs (GC: 0.306, SE: 0.004), MAs (GC: 0.368, SE: 0.005), and NHBs (GC: 0.328, SE: 0.005) had experienced higher-income inequality. In treating obesity, policymakers should consider race/ethnicity strategies to reduce inequality in income.

Exploring the Dynamic Shock of Unconventional Monetary Policy Channels on Income Inequality: A Panel VAR Approach

In response to the “Great Recession and Global Financial Crisis”, central banks had to deploy unconventional monetary policies (UMP) in order to fight the severe impact of the crisis. Therefore, the purpose of this study is to examine the dynamic shock of unconventional monetary policies through earning heterogeneity, income composition, and portfolio channels on income inequality in emerging economies covering the period 2000–2019, using the panel vector autoregressive (PVAR) model. A PVAR model was designed for this study because of its ability to address the dynamics of numerous entities considered in parallel. The findings suggest that the UMPs used by these countries’ central banks may have increased income inequality through all of the channels investigated in this study, as a shock to unconventional monetary policy results in a positive response in income inequality. Even when pre-tax income, held by the top 10%, is adopted to measure income inequality, the study yields similar results. It is evident that a central bank’s objective is and should be to fulfil its mandate of achieving maximum employment and price stability, thus bringing wide economic benefits. Thus, some forms of policies are more appropriate for addressing concerns about inequality (income policy or fiscal policy) than others. However, the current study alerts the central bank to the fact that monetary policies may have a wounding impact on income inequality. Therefore, the central banks should consider the cost of monetary policies on income inequality when drafting or implementing these kinds of policies.

Modelling the nexus between income inequality and shadow economy in Nigeria

Purpose — This paper aims to examine the relationship between the shadow economy and income inequality in Nigeria.Method — The paper employed Autoregressive Distributed Lag (ARDL), Fully Modified Ordinary Least Square (FMOLS), and Granger causality. This methodology is used to avoid endogeneity and heterogeneity in the model. This paper gauged income inequality using two diverse indicators of the Gini coefficient: the Gini index in proportion to household disposable income and the Gini index in proportion to household market income. In accordance with the literature, our empirical analysis draws on data from the Standardized World Income Inequality Database (SWIID), the World Bank, World Development Indicators, and the International Country Risk Guide (ICRG) for Nigeria from 1991 to 2018.Result — The findings of ARDL and FMOLS suggested a positive relationship between income inequality and the shadow economy, based on both measures of income inequality. In the short term, however, the shadow economy and income inequality are negatively correlated. Furthermore, we discovered a one-way causal relationship exists in Nigeria between the shadow economy, household disposable income, institutional democracy, household market income, and corruption control (CCI).Recommendation — Shadow economy has been regarded as an avenue to create job opportunities and raise poverty-income levels. It is critical that, for the shadow economy to reduce income inequality in Nigeria, policymakers should develop much better policies aimed at addressing income inequality.Contribution — In order to understand the relationship between income inequality and shadow economy activities in Nigeria, this study employed three methodologies, namely: Autoregressive Distributed Lags (ARDL), Fully Modified Ordinary Least Squares (FMOLS), and Granger Causality. The result offers reliable recommendations for pro-poor interventions that aim to limit the growth of informality via redistributing incomes.

How Income Inequality and Race Concentrate Depression in Low-Income Women in the US; 2005-2016.

Aim: To estimate the association between income and depressive symptoms in adult women, ages 20 years and older. Methods: Data for this study came from the 2005–2016 National Health and Nutrition Examination Survey (NHANES). We measured the presence of depressive symptoms by using a 9-item PHQ (Public Health Questionnaire, PHQ-9) and the Poverty to Income Ratio (PIR) as a proxy for income. We employed Negative Binomial Regression (NBRG) and logistic regression models in a sample of 11,420 women. We adjusted models by age, racial/ethnic groups, marital status, education, health insurance, comorbidity, and utilization of mental health professionals. We calculated the Gini Coefficient (GC) as a measure of income inequality, using PIR. Results: Between 2005 and 2016, 20.1% of low-PIR women suffered from depression (PHQ ≥10) compared with 12.0% of women in medium-PIR and 5.0% in high-PIR. The highest probabilities of being depressed were in Black Non-Hispanics (BNH) and Hispanics (12.0%), and then in White NH (WNH; 9.1%). The results of NBRG have shown that women in medium-PIR (0.90 [CI: 0.84–0.97]) and high-PIR 0.76 (CI: 0.70–0.82) had a lower incidence-rate ratio than women in low-PIR. The logistic regression results showed that income is protective in High-PIR groups (OR = 0.56, CI [0.43–0.73]). Conclusion: Policies to treat depression should prioritize the needs of low-income women of all racial groups and women.

The Impact of Foreign Aid on Income Inequality: Evidence from Developing Countries. Application of the FMOLS Approach

The present study aims to evaluate the impact of foreign assistance on income inequality of selected developing economies. Panel co-integration technique is applied for the purpose of estimation. After confirming the pre-conditions for cointegration, we have applied the Fully Modified-OLS method to estimate the association between foreign aid and income inequality. Controlling for other variables, we find a positive and significant association between foreign aid and inequality. The empirical results are robust concerning the sub-samples of developing economies selected according to the income classification of the World Bank. The empirical results are also robust concerning the alternative measure of income inequality.

EFFECTIVENESS OF GLOBALIZATION AND HUMAN CAPITAL ON MARKET & NET INCOME INEQUALITY IN BRICS COUNTRIES: A PANEL DATA ANALYSIS

This study scrutinizes the impact of defacto and dejure GLOB (KOF GLOB index 2018) on Income inequality on economically emerging countries; BRICS countries. The defacto GLOB indicates the estimate of GLOB including variables representing activities and flows; de jure estimate includes variables which show policies representing enable flows and activities. Our analysis separates the impact of globalization on net and market income inequalities. Pretax/transfer and the post-tax/transfer GINI indices were employed as the measures of income inequality. This analysis used balanced panel for BRICS countries for the period 1990-2015. Economic globalization both defacto and dejure showed positive sign that depicts a significant relationship with dependent variable. It explains that defacto political has positive sign and dejure political globalization decreases inequality while economic globalizations in both divisions have positive sign and significant impact on inequality. Interestingly, defacto social globalization has positive sign but dejure social has positive sign. Moreover, the purchasing power parity and age dependency both have negative sign and significant influence on inequality. These conclusions point out that social and political globalization may be a hindering factor for governance in these countries.

Functional Form of The Zenga Curve Based on Rohde’s Version of the Lorenz Curve

The Zenga curve is a tool to measure income inequality that represents the income ratio between the bottom income group and the top income group. A proper Zenga curve is a Zenga curve that can detect variations in the Ratio. In this paper, we derive the functional form of the Zenga curve from Rohde's Lorenz curve model. The result of this paper is that the functional form of the Zenga curve from Rohde's version of the Lorenz curve model is a constant. It cannot represent the truly happening phenomenon of inequality.

Measurement and Decomposition of Income Inequality among Agricultural Households in Andhra Pradesh

This study attempted to measure and decompose income inequality with the hypothesis that livestock is a major income source, and the value of farm assets is a major factor in increasing income inequality among agricultural households. The results revealed that livestock and agricultural wages had a larger equalizing effect across the income sources, and cultivation and off-farm had an un-equalizing effect on income distribution. The findings suggested that livestock and work opportunities in off-farm as an agricultural labourer can serve as potential sectors for marginal and small farmers to enhance income and minimize income variability across landholding categories.

Impact of Participation in Groundwater Market on Farmland, Income, and Water Access: Evidence from Pakistan

Groundwater irrigation has a critical role in the sustainability of arable farming in many developing countries including Pakistan. Groundwater irrigation is generally practiced to supplement surface water supplies in Pakistan. Nevertheless, uninterrupted and extensive use of groundwater irrigation has raised several concerns about its sustainability and resultant environmental implications. Due to the scarcity of groundwater and heterogeneity in farmers’ resources, informal groundwater markets have emerged in Pakistan, where farmers trade water using a contractual system. Yet, the effects of these markets on agricultural productivity and equity remain largely unknown. This paper aims to analyze the impact of participation in the groundwater market on farmland utilization, cropping patterns, water access, and income. We analyze these impacts using primary data collected from 360 farmers in three different zones of the country’s largest province. The farmers were categorized as buyers, sellers, and self-users of water. Results indicate that participation in water markets increased agricultural land utilization, evinced by a higher cropping intensity among participants. A horizontal and vertical equity analysis of water markets shows that although large farmers have better access to groundwater irrigation, water market participation improves equity to water access. Based on income inequality measures such as the Gini coefficient and the Lorenz curve, water market participation also improves farmer incomes regardless of farm size. Propensity score matching revealed that wheat yield and income among water-market participants went up by approximately 150 kg and PKR 4503 per acre compared with non-participants. Groundwater market participants’ higher crop productivity and income level suggest that water markets need a thorough revisit in terms of policy focus and institutional support to ensure sustainable rural development.

The Effect of Capital Account Liberalization on Income Inequality, focusing on South Asia

As a result of globalisation, countries across the world have opened their capital accounts, affecting economic growth, bargaining power of labor, and income inequality. A disproportionately large number of studies on capital account liberalization has focused on OECD and developed countries, leaving gaps in the literature for developing countries. To address this research gap, this paper focuses on the effect of capital account liberalization on changes in income inequality in South Asian countries, specifically Bangladesh, India, and Pakistan. Following Furceri and Lougani (2018), Li and Su (2020), and Quinn-Toyoda (2008), we examine the relationship between capital account liberalization and Gini coefficient as a measure of income inequality. Our findings reveal a small, positive, but statistically insignificant relationship between capital account liberalization and changes in income inequality for 149 countries, including South Asian countries of interest. The results from this study are inconclusive in determining if capital account liberalization exacerbates or reduces income inequality in the South Asian region.

Income inequality and self-rated health status in Colombia

BackgroundThe negative association between income inequality and health has been known in the literature as the Income Inequality Hypothesis (IIH). Despite the multiple studies examining the validity of this hypothesis, evidence is still inconclusive, and the debate remains unsolved. In addition, relatively few studies have focused their attention on developing or emerging economies, where levels of inequality tend to be the highest in the world. This work examines the statistical association between income inequality and self-rated health status in Colombia, a highly unequal Latin American country.MethodsTo explore whether this association is present in the general population or whether it is only confined to the bottom of the income distribution, we use data from the 2011–2019 National Quality of Life Survey. Multiple probit estimations are considered for testing the robustness of the IIH.ResultsEvidence favouring the IIH was found, even after controlling for individual income levels, average regional income, and socioeconomic characteristics. The link between income inequality and the probability of reporting poor health seems to be present across all income quintiles. However, the magnitude of such association is considerably smaller when using inequality measures with relatively greater sensitivity to income differences among the rich.ConclusionsThe association between regional income inequality and individual's self-rated health status in Colombia is not only confined to low-income individuals but extends across all socioeconomic strata. This association is robust to the income inequality measure implemented, the income-unit of analysis, and changes in the sample. It is suggested that reducing income disparities can potentially contribute to improving individual's health.

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.

Lorenz Interpolation: A Method for Estimating Income Inequality from Grouped Income Data

To understand how income inequality affects individuals and communities, researchers must have accurate measures of income inequality at lower geographic levels, such as counties, school districts, and census tracts. Studies of income inequality, however, are constrained by the tabular format in which censuses publish income data. In this article, the author proposes a new method, Lorenz interpolation, for estimating income inequality from binned income data. Using public microsample data from the American Community Survey (ACS), the author shows that Lorenz interpolation produces more accurate and reliable income inequality estimates than do alternative estimation methods. Then, using restricted ACS income data obtained through a Federal Statistical Research Data Center, the author evaluates the accuracy of Lorenz interpolation at the census tract and school district levels. Lorenz interpolation produces reliable school district–level estimates, but the method produces less reliable estimates for some income inequality measures at the tract level. These findings indicate that researchers should refrain from estimating tract-level income inequality measures from tabular data. They also show that aggregating tract income distributions to higher geographic levels can produce valid estimates of income inequality.

The impact of trade unions and government party orientation on income inequality: evidence from 17 OECD economies

PurposeDespite the existing conceptual analysis on the impact of trade unions on employees' welfare and the wider economy, the mediating effect of political party orientation (i.e., right, centre and left) on income inequality remains under researched. In this paper, the authors empirically explore the relationship between the nature of political party orientation, trade unions and income inequality.Design/methodology/approach The authors use three different measures of income inequality and dummy variables that capture government party orientation with respect to economic policy for a panel of 17 OECD economies over the period 2000–2016. The authors employ a panel fixed effects approach and the Driscoll and Kraay's (1998) nonparametric covariance matrix estimator.FindingsThe empirical evidence indicates that strong unions and, to some extent, left party governance, are fundamental institutional elements to combat rising levels of income inequality whilst countries dominated by right-wing political parties appear to exacerbate income inequality. The results pertaining to the impact of centrist parties on income inequality are ambiguous suggesting that a potential fragmentation may exist in their political approach.Originality/valueThe evidence generated can have significant policy ramifications in alleviating rising levels of income inequality as well in relation to the declining unionization rates observed across advanced economies.

Relation Between Two Income Inequality Measures: The Gini coefficient and the Robin Hood Index

The objective of this investigation is to study the relation between two common measures of income inequality, the Gini coefficient and the Robin Hood index. An approximate formula for the Robin Hood index in terms of the Gini coefficient is developed from 100,000 Lorenz curves that are randomly generated based on 100 twenty-parameter families of income distributions. The approximate formula is tested against Robin Hood indexes of commonly-used one-parameter Lorenz curves, income data of several countries, and reported results of Robin Hood indexes. The approximate formula is also tested against results of a stochastic income-wealth model that is introduced in the present investigation. The formula is useful conceptually in understanding why Gini coefficients and Robin Hood indexes are correlated in distribution data and is useful practically in providing accurate estimates of Robin Hood indexes when Gini coefficients are known. The continuous piecewise-linear approximation is generally within 5% of standard one-parameter Lorenz curves and income distribution data and has the form: R ≈ 0.74G for 0 ⩽ G ⩽ 0.5, R ≈ 0.37+0.90(G-0.5) for $$0.5 ⩽ G ⩽ 0.8 and $$ R ≈ 0.64 + 1.26 (G- 0.8) for 0.8 ⩽ G ⩽ 0.95$$ where R is the Robin Hood index and G is the Gini coefficient.

Discussion of Dhaliwal, Goodman, Hoffman, and Schwab (2019): Revisiting Tax-Related Reputational Costs

Discussion of Dhaliwal, Goodman, Hoffman, and Schwab (2019): Revisiting Tax-Related Reputational Costs