Gini Coefficient Of Income Research Articles

Financial Development and Income Inequality in Bangladesh: Empirical Evidence from Vector Auto-Regression (VAR) Model

This study investigates the effect of financial development on inequality in Bangladesh. We run a vector autoregressive (VAR) model for the economy of Bangladesh from 1980 to 2020. Using the impulse response functions (IRFs), we find that the disposable income and market income Gini coefficients respond positively to private credit. It suggests that financial development contributes to raising inequality in Bangladesh. We also find that growth has an adverse impact on inequality whereas income inequality has a positive effect on economic growth. However, economic growth has a greater and more pronounced negative effect on inequality than inequality itself, even though these two variables exhibit opposite interaction responses. It indicates that growth lowers inequality in Bangladesh.The forecast error variance decomposition function shows that private credit can explain the variations of disposable income Gini by 8.65 percent; on the other hand, disposable income Gini can explain the variation of private credit by 8.90 percent.

Effect of Non-Farm Income on Income Inequality in Pakistan

The portion of farm households' income outside the farm, such as non-farm salaries and wages, pensions, and interest income, is referred to as non-farm income. In Pakistan, non-farm profit is an essential source of income. "income inequality" describes the inequitable income distribution between people or families in a community or economy. Income inequality is a significant issue worldwide, including in Pakistan. This research estimated the effect of non-farm income on rural and urban areas and analyzed the relationship between non-farm income and income inequality within households. Secondary data from the Pakistan Social and Living Standard Measurement Survey Household data (2019-20) was used. Multinomial Logistic Regression was applied to the data, and income inequality was calculated using the Gini coefficient. The population was divided into quartiles to measure income distribution. The research found that non-farm income raises income inequality, while farm income is an income equalizer among the population. The reason behind this is that a major portion of income or wealth is accessed by the upper society, with only a minor portion reaching the lower levels of the population. Specifically, the Gini coefficient for non-farm income was 0.65, indicating higher inequality, compared to 0.45 for farm income. In urban areas, non-farm income provides large opportunities, while rural areas predominantly depend on the farm sector. There is a need to raise awareness about the non-farm sector in rural sector. The study's policy implications include the following: In order to improve agricultural households' income and low-income disparity, non-farm income activities have to be promoted. The study also suggests that Inequalities within rural communities should be addressed as part of an equal development strategy, in addition to the rural-urban gap.

House prices and credit as transmission channels from monetary policy to inequality: Evidence from OECD countries

Using a panel vector autoregressive model, this paper assesses the impact of monetary policy on the Gini coefficient of disposable income for 30 OECD countries between 1995Q1 and 2019Q4. We assume house prices and household credit as transmission channels, representing households’ financial balance. To capture the effect of the financial crisis, the analysis further distinguishes the period that started in 2008Q4. We find that a contractionary monetary policy increases the Gini coefficient in a moderate way. For the entire period, house prices are an effective transmission channel, a positive shock decreasing inequality, while credit is not statistically significant. Following the crisis credit stands out as the transmission mechanism, a positive credit shock reducing the Gini coefficient, while house prices lose relevance. These results are robust to different model specifications.

Multifaceted Regional Educational Inequality: Evidence from Türkiye

ABSTRACT Educational equality is a priority in sustaining economic and human development. This study examines regional educational inequality in Türkiye by considering educational attainment, income distribution, and education spending. Average years of schooling improved in all regions between 2008 and 2020. The Education Gini and Theil indexes indicate diminishing intra-regional inequality while significant inter-regional differences persist. The income Gini coefficient was unexpectedly found to be negatively correlated with equality in educational attainment for the country and three regions. The results also show the disproportionate dominance of the top income group in the distribution of education spending and the share of education in consumption expenditures. The growing gap in educational expenditures between the top and last quintiles accompanies rising educational attainment. The recent achievement in educational attainment needs to be followed by new programs that address social and spatial educational inequality in Türkiye.

Incomes and income inequality in Stockholm, 1870–1970: Evidence from micro data

This paper analyzes incomes and income inequality in Stockholm from 1870 to 1970. The paper builds on a new dataset of 38,022 randomly sampled Stockholm residents 1870–1950, with information on income, occupation, age, gender, and household composition. This is complemented by the Census of 1930 and a Statistics Sweden sample for 1960 and 1970. Incomes were very unequally distributed between 1870 and 1920, with Gini coefficients of pre-tax income around sixty. After 1920 inequality fell quite steadily. A drop in capital incomes contributed, and when looking at post-tax incomes the growth of progressive taxation after 1930 also contributed, but most of the high inequality up to 1920 and equalization after this date depended on the distribution of labour income. In the early 1900s professional groups had huge income advantages over workers, but this advantage was drastically reduced after 1920 when working-class incomes grew rapidly. An important mechanism of income growth was the upgrading of the jobs structure, highlighting the importance of structural change, beyond the Kuznetsian binary of agriculture–manufacturing, for understanding long-run economic inequality.

Livelihood strategies, baobab income and income inequality: Evidence from Kordofan and Blue Nile, Sudan

This paper analyses the relationship between livelihood strategies, baobab income, and income inequality in rural Sudan. Baobab is an emerging commercial crop with emerging specialised value chains in Kenya and Malawi. In Sudan, baobab traditionally has been used with limited research on evolving business opportunities and associated implications for rural development. The study utilizes survey data from 374 randomly sampled households from two states in Sudan (Kordofan and Blue Nile) and examines livelihood strategies, income inequalities and the role of baobab income for rural households. We use principal component analysis (PCA) and hierarchical cluster analysis to identify three household clusters in each region based on the income sources. In Kordofan, the identified strategies were ‘livestock and baobab-based’, ‘livestock and crop-based’, and ‘business-based’. In Blue Nile, they were ‘mixed’, ‘business-based’, and ‘crop-based’. The clusters exhibited variations in asset endowments and wealth, with differences in access to land, savings, credit, and technology. Households classified under the livestock-baobab strategy (Kordofan) and the mixed strategy (Blue Nile) had the highest degree of poverty, lowest per capita income, and baobab contributed 33% and 26% of total income, respectively, underscoring the importance of baobab income to the livelihood security of poorer households. To analyse inequality in distribution of income Gini coefficients are estimated for regions and livelihood strategy categories. Baobab income contributes to reducing income inequality: 10% increase in baobab income reduces inequality by 6.5% and 11% in Kordofan and Blue Niles, respectively, but shows also in Kordofan better off households generate higher incomes from baobab.

The Rise of Guard Labor in the United States: Evidence from Local Labor Markets

We examine the rise of “Guard Labor”—defined as occupations devoted to labor extraction—at the commuting zone level in the United States. Between 1950 and 2017 the share of the labor force employed in guard labor increased from 19.5 percent to 29.4 percent. We explore the local labor market correlates of guard labor and validate several predictions of the labor discipline model, while extending the model to the context of contemporary racial capitalism. The share of the labor force employed in guard labor is positively correlated with the household income Gini coefficient, negatively correlated with the fraction of the labor force in a union, and positively correlated with contemporary measures of local racial animosity. Consistent with the labor discipline model, an increase in the share of the labor force employed in supervisory occupations has a significant negative effect on nonsupervisory wages. JEL Classification: O17, P16, Z13, B51, B52

Non-linear links between human capital, educational inequality and income inequality, evidence from China.

This study aims to reveal short-run and long-run asymmetries among human capital, educational inequality, and income inequality in China over the period 1975-2020 using a nonlinear autoregressive distributed lag (NARDL) model. The estimated long-run asymmetry parameters reflect that positive shocks to secondary education (SSE) and higher education (HE) are negatively correlated with income Gini coefficient. The adverse shocks of secondary education (SSE) and higher education (HE) stimulate the Gini coefficient of income, but the effect of secondary education (SSE) on the Gini coefficient of income is not significant, while that of higher education (HE) is significant. The results also highlight that, in the long run, there is a significant asymptotic effect of the education Gini coefficient (educational inequality) and economic growth on the income Gini coefficient (income inequality). However, physical capital stock has a significant adverse effect on income inequality in the long run. Higher education significantly promotes educational inequality, while the square of higher education significantly reduces educational inequality, thus verifying the inverted U-shaped Kuznets curve hypothesis between higher education and educational inequality. Strategically, this study suggests higher education as a powerful tool for mitigating income inequality by emphasizing educational equity.

A Twofold Subjective Measure of Income Inequality

Social scientists have been aiming to calculate a “subjective income Gini coefficient”of survey respondents that would describe their beliefs about income inequality in their country. Niehues (Subjective perceptions of inequality and redistributive preferences: an international comparison, Cologne Institute for Economic Research, IWTRENDS Discussion Paper, 2014) derives this estimate from respondents’ beliefs about the relative sizes of different social classes (answers to “shape of society” questions), while Kuhn (The individual perception of wage inequality: a measurement framework and some empirical evidence, Technical report, Institute of Labor Economics (IZA), 2015) estimates it using beliefs about the pay structure. We combine their efforts to calculate what we call a twofold subjective Gini coefficient, which incorporates both pieces of information independently from one another. We present the country-level distribution of perceived and desired twofold subjective Gini coefficients using the ISSP Social Inequality V survey (ISSP Research Group in International social survey programme: social inequalityv—issp 2019, 2019. https://doi.org/10.4225/13/511C71F8612C3). Accounting for both subjective class structure and pay structure yields much lower perceived and desired levels of inequality. At the country level the averages of the twofold subjective Gini coefficients are closer to actual income Gini coefficients than the previous measures. At the individual level the twofold subjective Gini coefficients are better predictors of the individual’s verbal assessment of inequality and their preferences towards redistribution.

Explaining the rise of populism in European democracies 1980–2018: The role of labor market institutions and inequality

AbstractObjectivesThis article aims to find country‐level factors that explain the rise of populist parties in European democracies. While populism is often connected to inequality, we not that right‐wing populist parties tend to thrive on fear, including fear of job loss. If flexible labor markets mean that unemployment is dedramatized because finding a new job is easier, labor market flexibility could dampen populism and inequality may be less important.MethodsWe run country‐level fixed effects regressions on populist party vote shares in 26 European countries from 1980 to 2018. We use two different classifications of right‐wing and left‐wing populist parties and control for employment protection strictness as measured by OECD, Gini coefficients of disposable income, and a large set of control variables.ResultsUnemployment is positively associated with left‐wing populism. Strict employment protection is positively associated with right‐wing populism. Gini inequality of income is unrelated to (both types of) populism.ConclusionStrong employment protection and low‐income inequality may not be the most efficient way to combat right‐wing populism. A strategy that promotes flexible labor markets, and job upgrading may be an alternative. More research on the link between labor market institutions and (in particular, right‐wing) populism is needed.

Does local income and wealth inequality affect mortality? A register-based fixed effects study of 58 million person-years.

Aim: The Income Inequality Hypothesis asserts that income inequality causes negative health burdens within wealthy nations. We aimed to test the hypothesis in Norway, examining the relationship between both income and wealth inequality, net of individual economic resources, and individual all-cause mortality. To this day, little is known about the association between wealth inequality and mortality. In Norway, wealth is far more unequally distributed than income and can be a more prevalent indicator of long-term financial security. Methods: We estimated discrete-time event history models from Norwegian register data, covering all Norwegian-born men and women aged 25-84 years during the period 1993-2013. We include fixed effects at the municipal level, adjusting for time-invariant characteristics in the local area. Our data contain approximately 58.5 million person-year observations after sample restrictions. Results: Overall, increased income and wealth inequality (measured using Gini coefficients of individuals' pensionable income and net worth) is not associated with higher mortality risk in Norway. With a one percentage point increase in income inequality, odds ratio (OR) for mortality was estimated at 0.998 (95% confidence interval (CI) 0.996-1.001) for men and 1.002 (95% CI 0.999-1.006) for women. Corresponding OR from increased wealth inequality was 0.998 (95% CI 0.997-1.000) for men and 0.999 (95% CI 0.998-1.001) for women. Conclusions: Our results raise further doubts about the existence of a contextual effect of economic inequality on health, at least in a Nordic setting. Extensive health policies, relatively generous benefits and high levels of trust could potentially function as a buffer against negative health consequences of increased economic inequality in Norway.

Distributional national accounts for the Netherlands and a comparison with 12 other countries

Most inequality studies rely on micro data that do not capture a substantial share of income identified in the national accounts. In the Netherlands, almost one fifth of household disposable income is missed by current inequality statistics. In this paper, we present inequality statistics for the Netherlands that capture all of household income, so‐called distributional national accounts. Compared to the current inequality statistics, the Gini coefficient for disposable income increases substantially from 0.289 to 0.337. Cross‐country comparisons show that such a change between Gini coefficients based on micro‐data versus Gini coefficients based on distributional national accounts does not apply to all countries. The difference between both Gini coefficients varies not only between countries in the size, but also in the sign of the difference.

A study of household income inequality in China: perspective of educational homogeneity marriage

Based on the data from the 2006 to 2017 Chinese Social Survey (C.S.S.), we measured the extent of inequality between the total household income and the average household income in China. We conclude that the Gini coefficient of total household income fluctuates between 0.47 and 0.52. The Gini coefficient of household per capita income fluctuates between 0.5 and 0.54, indicating a significant degree of household income inequality in China. We use the kernel density method to obtain the distribution of household income and find that the overall income level of society has increased. Still, the degree of household income inequality has been growing. From the perspective of educational homogeneity marriage, we use the income distribution table to analyse the internal structure of the total household income and draw the following conclusions. High-income households account for most of the whole social gain, and an increase in household income disparities has accompanied the increase in the household size. In addition, the distribution of total household income in China differs significantly in the household head's educational attainment. A relatively small number of households with a high degree of educational attainment account for a relatively large share of income, and households with a combination of high–high and high–low educational attainment have gradually increased. The proportion of social income has continued to rise.

An investigation of the longitudinal relationship between neighbourhood income inequality and individual self-rated health in England.

There are mixed findings on whether neighbourhood income inequality leads to better self-rated health (SRH) or not. This study considers two hypotheses: individuals living in more unequal neighbourhoods have better SRH and the level of neighbourhood income inequality and its impact on SRH is moderated by household and neighbourhood level income related variables. Data from Waves 8-10 of the UK Household Longitudinal Study for respondents living in England at wave 8 were used. Neighbourhood income inequality was measured using Gini coefficients of household income from the Pay As You Earn and benefits systems for Lower Super Output Areas. Longitudinal ordinal multilevel models predicted self-rated health in 2016-18, 2017-19 and 2019-20 by income inequality and its interaction with household income, neighbourhood median income and neighbourhood deprivation, conditional on individual educational attainment, age, sex, ethnic group, years lived in current residence, region of residence and study wave. There were 24,889 respondents analysed over three waves. SRH was worse for those living in more income equal neighbourhoods. There was no indication that neighbourhood inequality was moderated by household income, neighbourhood median income or neighbourhood deprivation. These findings are in line with the balance of existing evidence and support policy interventions that aim to create mixed communities for the purpose of improving population health.

Income Gap Equalization Based on PSO Algorithm in Edge Computing Environment.

In order to explore the current income gap, a method based on the PSO algorithm in the edge computing environment is proposed. PSO calculates and simulates bird flock foraging activities, the Frank Heppner biological group model, and the three rules in bird activities. After studying the activities of these natural creatures, abstract problems are quantified and similar models established. The Gini coefficient is calculated by using grouped data, and the grouping basis is also innovative. The quantile grouping method is adopted, which can effectively solve the difference between the concentration index and the Gini coefficient, and the Gini coefficients of each year can be added up to finally get the Gini coefficient of the stock income. Experimental results show that the Gini coefficient of traffic income in 2017 and 2018 had dropped significantly, but the variation of the Gini coefficient of stock income (Delta CG) was still greater than 0. Obviously, the adjustment speed of the Gini coefficient of stock income was lagging behind, as was the Gini coefficient of traffic income. We found that after 1986, the facilitation effect was greater than the dilution effect, and the facilitation effect continued to push up the stock income gap, which indicated more income flow to the high-income group, with the income flow gap showing an upward trend and the upward trend becoming more and more obvious. It has been proved that the PSO algorithm can effectively identify the income gap in the edge computing environment, and the corresponding policy suggestions are given.

Local Economic Inequality and the Primary Care Physician Workforce in North Carolina.

Income inequality has been associated with multiple adverse health outcomes including diabetes and obesity, with this relationship potentially mediated by limited access to primary care. We explore the association between county-level economic inequality and the primary care physician (PCP) workforce in North Carolina. County-level economic and demographic data were obtained for 2013 to 2018. Economic inequality was quantified using the Gini coefficient of household income. PCP workforce data were obtained from a statewide database and correlated with county characteristics using fixed-effects linear regression. The analysis included 600 county-years. An increase of 0.1 in the Gini coefficient was correlated with a decrease in PCP workforce by 0.58 physicians/1000 residents in a given county. Within family medicine, a 0.1 increase in the Gini coefficient was associated with a decrease of 0.53 family medicine physicians per 1000 residents. Local increases in economic inequality are associated with local decreases in PCP workforce (per capita), particularly in family medicine. Although further research is needed to identify specific reasons for the decrease, medical schools in areas with high economic inequality should consider prioritizing training of physicians in family medicine and other primary care specialties to better serve community health care needs.

Income-Related Mortality Inequalities and Its Social Factors among Middle-Aged and Older Adults at the District Level in Aging Seoul: An Ecological Study Using Administrative Big Data.

This study investigated income-related health inequality at sub-national level, focusing on mortality inequality among middle-aged and older adults (MOAs). Specifically, we examined income-related mortality inequality and its social factors among MOAs across 25 districts in Seoul using administrative big data from the National Health Insurance Service (NHIS). We obtained access to the NHIS’s full-population micro-data on both incomes and demographic variables for the entire residents of Seoul. Slope Index of Inequality (SII) and Relative Index of Inequality (RII) were calculated. The effects of social attributes of districts on SIIs and RIIs were examined through ordinary least squares and spatial regressions. There were clear income-related mortality gradients. Cross-district variance of mortality rates was greater among the lowest income group. SIIs were smaller in wealthier districts. Weak spatial correlation was found in SIIs among men. Lower RIIs were linked to lower Gini coefficients of income for both genders. SIIs (men) were associated with higher proportions of special occupational pensioners and working population. Lower SIIs and RIIs (women) were associated with higher proportions of female household heads. The results suggest that increasing economic activities, targeting households with female heads, reforming public pensions, and reducing income inequality among MOAs can be good policy directions.

Income inequality and COVID-19 mortality: Age-stratified analysis of 22 OECD countries.

Our study builds on a growing body of research that demonstrates an association between income inequality and COVID-19 mortality. Using Poisson multivariate regression, we age-stratify our analysis by separately examining each of four age groups over a nine-month study period in 22 OECD countries. Our full regression model controls for national median income and relative poverty, and a set of pandemic-specific variables to capture exposure, susceptibility and treatment. We found that country-level income inequality, as measured by the disposable income Gini coefficient, is significantly and positively associated with COVID-19 mortality for all four age groups. Consistent with previous studies that analyzed all-cause mortality by age, our regression results found that the point estimate of the Gini coefficient generally declines with age. Our results suggest that inequality is possibly acting through generic and pandemic-specific processes to increase mortality via a more pronounced negative COVID-19 socio-economic status gradient in higher inequality countries.

Economic Inequality and COVID-19 Deaths and Cases in the First Wave: A Cross-Country Analysis.

The cross-country relationship of coronavirus disease 2019 (COVID-19) case and death rates with previously measured income inequality and poverty in the pandemic’s first wave is studied, controlling for other underlying factors, in a worldwide sample of countries. If the estimated associations are interpreted as causal, the Gini coefficient for income has a significant positive effect on both cases and deaths per capita in regressions using the full sample and for cases but not for deaths when Organisation for Economic Co-operation and Development (OECD) and non-OECD sub-samples are treated separately. The Gini coefficient for wealth has a significant positive effect on cases, but not on deaths, in both sub-samples and in the full sample. Poverty generally has weak positive effects in the full and non-OECD samples, but a relative poverty measure has a strong positive effect on cases in the OECD sample. Analysis of the gap between COVID-19 first-wave cases and deaths per capita in Canada and the higher rates in the United States indicates that 37 percent of the cases gap and 28 percent of the deaths gap could be attributed to the higher-income Gini in the United States according to the full-sample regressions.

Gini in the Taylor Rule: Should the Fed Care About Inequality?

This study investigates whether the Federal Reserve (Fed) should care about inequality. We develop a Heterogeneous Agent New Keynesian (HANK) model, which generates empirically realistic inequalities and business cycle properties observed in the U.S. data. Households in the model economy are subject to the aggregate productivity shock and to the idiosyncratic labor efficiency and preference shocks. In addition, the model distinguishes the extensive and intensive margins of labor supply. We consider the income Gini coefficient in a monetary policy rule to see how an inequality-targeting monetary policy might affect aggregate and disaggregate outcomes, as well as economic welfare. First, we find that a monetary policy rule with an explicit inequality target can be welfare improving, even if inequality becomes volatile. Second, there is an efficiency-equity trade-off: an economy should sacrifice a more volatile output in order to have smaller cyclical variations in its inequality measures. Lastly, when the Fed targets the employment of a specific group of households, it can improve economic welfare and stabilize inequality at the same time.