Total Income Inequality Research Articles

Income and consumption inequality trends: a comparative analysis between paid employees and the self-employed

This paper aims to analyze trends in income and consumption inequality for paid and self-employed households and examine to what extent changes in aggregate consumption and income inequality can be explained by changes in their permanent and transitory components over time using data from the Italian Survey of Household Wealth (SHIW) covering the period 1989-2016. The results obtained from the Generalized Method of Moments (GMM) analysis reveal differences in consumption and income inequality, as well as their permanent and transitory components, between self-employed and payroll households. In particular, self-employed households experience higher levels of both income and consumption inequality, the increase in total income and consumption inequality is mainly driven by an increase in its transitory component. Furthermore, findings from other descriptive measures of inequality, such as the Gini coefficient, the variance of the log, 90th/10th, and 50th/10th percentile ratios, support the notion that income inequality is higher than consumption inequality across all groups, with self-employed households exhibiting a more pronounced difference.

Decompositions of Inequality and Poverty by Income Source

Abstract There is ample empirical literature on the contributions of different income sources to total income inequality. In contrast, studies estimating the contributions of income sources to income poverty are scarce. This paper presents a new decomposition of the Foster–Greer–Thorbecke poverty index, based on a marginal approach previously employed to decompose income inequality. We apply these marginal decompositions to data for 15 EU countries and classify six income sources according to their impact on inequality and poverty. Our results indicate that there are significant differences in the contributions of income sources to poverty compared to their respective contributions to inequality.

Inequality Among Agricultural Households in Rural Punjab: The Effect of Income Sources

This study examined income inequality among agricultural households in Punjab using primary data collected during the agricultural year 2020-21. The study employed the Gini coefficient and Theil index to measure and decompose income inequality. The results indicated that agricultural household's involvement in off-farm and ad-hoc sources increased with their income level. Crop cultivation contributed the highest to total income inequality due to its dominance in household income. Still, it had an inequality-decreasing effect in marginal, small, semi-medium, and medium-category households. Livestock income was also identified as a potential tool for reducing inequality, especially in the south-western zone of the state. However, the off-farm income sources were inequality enhancing, likely due to disparities in skills and education required for engaging in such activities compared to agricultural activities. The Theil index revealed that intra-zonal and intra-landholding size inequality were the main contributors to overall inequality. These results indicated that there was a need for targeted policy interventions to enhance the livestock sector, promote income diversification, and address intra-zonal and intra-landholding disparities to promote inclusive and equitable development in Punjab's agricultural sector.

Subsidies and the income inequality in the Hungarian wine sector

The paper investigates the impact of different sources of income on wine farm total income inequality in Hungary using Farm Accountancy Data Network data for the period 2013-2019. The decomposition of the Gini coefficient is applied to focus on the impact of the Common Agricultural Policy (CAP) shift from market to government budgetary support on wine farm total income inequality. Off-farm income has a rather stable impact on wine farm total income inequality. CAP Pillar 1 subsidies have remained more important than CAP Pillar 2 subsidies, both in the structure of wine farm total income and in the reduction of wine farm total income inequality. The most striking finding is regarding a shift in wine farm market income from a negative (losses) to a positive (profit) value and its increasing role in wine farm total income inequalities. The 20% of the largest wine farms created from almost 90% to less than 80% of wine farm total incomes between 2013 and 2019, but during the same period their participation in CAP subsidy payments was reduced much more from more than 80% to around 60%. Subsidies from Pillars 1 and 2 were reduced, and wine market income increased wine farm total income inequality, while it remained constant for off-farm income. The wine farm market income has driven wine farm total income inequalities. This might strengthen because of the ongoing market selection process with the exit of less efficient and loss-making wine farms and the increasing role of surviving profitable wine farms. This market selection process can be related to managerial, entrepreneurial, and innovation activities based on the differentiation and segmentation of wine farm products and their market incomes.

Do minimum wages deliver what they promise? Effects of minimum wage on employment, output, and income inequality from occupational choice theory

This paper addresses the unresolved debate on the effects of minimum wages on output, employment, and income inequality by modeling an occupational choice economy calibrated for a representative OECD economy. The minimum wage sets a minimum skill requirement for employees, which reduces the effective labor supply and raises its price. Consequently, salaries increase, business profits fall, and some entrepreneurs transition to solo self-employment. With a minimum-to-average wage ratio of 0.43 (the OECD countries average in 2020), a 10% increase in the minimum wage reduces output, employment, and inequality among employees by 0.2%, 1.0%, and 2.1%, respectively, and increases total income inequality by 0.57%. If the minimum-to-average wage ratio were 0.55, output, employment, and inequality among employees would decrease by 0.87%, 3.55%, and 5.19%, respectively, and income inequality would rise by 2.09%. In summary, the effects are mainly negative, contrary to what is promised, and quantitatively large for high minimum-to-average wage ratios.

Understanding the mediating role of labor out-migration in household income generation and distribution under a reforestation policy in rural China

Income inequality is a critical issue of socio-economic development, particularly in rural areas where forest-dependent people are often vulnerable to the intervention of forest policies. This paper aims to elucidate income distribution and inequality of rural households influenced by China's largest reforestation policy implemented in early 2000s. Drawing on socioeconomic and demographic data from household surveys in two rural sites, we applied the Gini coefficient to measure income inequality and used a regression-based approach to examine the underlying factors that are associated with income generation among households. We also performed a mediation analysis to test the role of labor out-migration in shaping household income distribution under the reforestation policy. Results show that remittances sent by rural out-migrants substantially contribute to household income but tend to worsen inequality, particularly for households having retired cropland for reforestation. The inequality in total income depends on capital accumulation for land endowment and labor availability that render diversified livelihoods possible. Such linkage reveals regional disparity, which, along with policy-implementing institutions (e.g., rules for tree species choice for reforestation), can influence income generation from a given source (e.g., agriculture). Rural out-migration of female labor significantly mediates the economic benefits of the policy delivered to the households with an estimated mediating share of 11.7%. These findings add value to the knowledge of poverty-environment interrelationships in a sense that supporting rural livelihoods of the more vulnerable and underrepresented groups is essential for securing and sustaining the stewardship of forests. Policymaking for such forest restoration programs needs to integrate strategies for targeted or precise poverty alleviation to strengthen the conservation effectiveness.

Polarization of employment and wages in China

AbstractIn China, between 1995 and 2018, the proportion of workers employed in unskilled job categories grew, while the share holding middle‐skilled jobs declined. The resulting income polarization magnified a major redistribution of wages within job categories, which is not only the main component of total income inequality but is also the driving factor contributing to changes in total income inequality over the 1995–2018 period. Our counterfactual simulation results support our conjecture that the large employment shift from middle‐skilled to unskilled jobs reflects the adoption of labor‐saving technologies and the response to increased demand for services. We believe that our study sheds light on similar transformations in other developing economies.

IMPACT OF TOTAL FACTOR PRODUCTIVITY AND INCOME INEQUALITY ON TAX

Nexus of total factor productivity, inequality, and taxes (selected SAARC Countries) along with other control variables like corruption, consumption expenditure, capital, and labor. For short and long-run elasticities along with different estimation techniques are applied. Total factor Productivity (TFP) data of SAARC countries were unavailable, so only Pakistan, India, Bangladesh, and Sri Lanka are estimated. Tax to GDP ratio is low, and income equality is negative as it will decrease the tax revenue, and increase in anti-corruption policies will increase tax revenue, an increase in TFP will reduce in tax revenue, increase in employment, there will be an increase in tax to GDP ratio and consumption expenditure is found negative and significant on tax The results confirm that most of the variables of the long-run elasticities are significant. All the models are robust because there is no slope heterogeneity, heteroscedasticity, multicollinearity, and cross-section dependence among the variables.

Upper and Lower Bound Estimates of Inequality of Opportunity: A Cross‐National Comparison for Europe

I provide lower and upper bound estimates of inequality of opportunity (IOp) for 32 European countries, between 2005 and 2019. Lower bound estimates use machine learning methods to address sampling variability. Upper bound estimates use longitudinal data to capture all‐time invariant factors. Across all years and countries, lower bound estimates of IOp account from 6 percent to 60 percent of total income inequality, while upper bound estimates account from 20 percent to almost all income inequality. On average, upper bound IOp saw a slight decrease in the aftermath of the Great Recession, recovering and stabilizing at around 80 percent of total inequality in the second half of the 2010s. Lower bound estimates for 2005, 2011, and 2019 show a similar pattern. My findings suggest that lower and upper bound estimates complement each other, corroborating information and compensating each other's weaknesses, highlighting the relevance of a bounded estimate of IOp.

Effect of industrial structure on urban–rural income inequality in China

PurposeSince 1978, China has made tremendous economic achievements through industrial upgrading. However, these achievements are accompanied by an expanding income gap between rural and urban areas. The purpose of this paper is to examine the relationship between industrial structure and urban–rural income inequality in China.Design/methodology/approachUsing the fixed-effects model and provincial data for the period 1985–2019, this paper estimates a linear relationship between industrial structure and urban–rural income inequality. By decomposing total income inequality into four components, the paper then analyzes how industrial structure affects each component.FindingsThe results show that industrial structure imbalance and industrial upgrading are positively associated with urban–rural income inequality. The positive effect of industrial imbalance mainly comes from widening the wage gap, while that of industrial upgrading mainly comes from aggravating business income inequality and property income inequality. Moreover, industrial balance and upgrading are conducive to increasing the share of wage income at the cost of property income.Originality/valueBy progressively examining the total inequality and the inequality of income components, this paper provides a better understanding of how industrial structure affects urban and rural income inequality. The findings of this study highlight the “inequality cost” associated with industrial structure adjustment, which provide policy-related insights on the balance development of urban and rural areas.

Risk of Increasing Income Inequality and Poverty: Analysis by Income Source

The high and persistent level of income inequality limits the opportunities for economic growth and contributes to the persistence of a high poverty rate in Russia. Reducing inequality is integral to achieving the Sustainable Development Goals (SDG-10); thus, greater focus is needed to reduce income inequality. We assess income inequality based on a representative income and expenditure data collected at the micro level to determine the risk of increasing inequality and poverty in the context of specific socio-demographic groups and income sources. We look at the contribution of various household income sources to total income inequality, taking into account the differences in the weighting of income components, the unevenness of their distribution, and their correlation with the total distribution of income. The main data source is the project “The Russia Longitudinal Monitoring Survey-Higher School of Economics” (RLMS-HSE) for 2000–2018. Calculation of the elasticity of the Gini index by sources of total income for poor and non-poor households revealed their multidirectional impact on overall inequality. We show that social transfers in poor households do not help to reduce inequality. This indicates the need for closer attention to this phenomenon when making policy decisions connected with social policy. Moreover, the “hidden incomes” appear to be a factor reducing inequality for poor households within the framework of the accepted definitions and the formed sample of households.

Globalization and income inequality: A panel data analysis of 37 developing countries in Africa

The lack of economic facts on the effects of globalization and income inequality in Africa has made it difficult for an effective economic policy response to the problem of inequalities in the continent. Against this backdrop, this paper examined the nexus between globalization and income inequality by estimating Ordinary Least Square (OLS) and the Random model for Panel data of 37 developing countries in Africa over the period of 1970 to 2014. The relationship between income level and income inequality justifies the validity of Kuznets’ U hypothesis. The results showed a negative relationship between the total globalization index and income inequality after taxes and transfer for the (OLS). Results for the globalization sub-indicators such as economic globalization showed a robust positive significant relationship for both measures of income inequality measures (Gini net and Gini market), while political globalization showed a negative relationship with both income inequality measures. It is recommended that government in African countries should strengthen their institutions to promote policy frameworks that will increase income levels and the human capital capacity, while steps should be taken to control the ever-increasing population and age dependency ratio.

The Impact of Education on Income Inequality in China: Measurement and Decomposition

In recent years, while maintaining steady and rapid economic development, the government has also achieved some results in adjusting the income distribution gap, but income distribution equity is still one of the focus issues of public concern. Since education is one of the important channels to obtain human capital and has an important impact on residents’ income level, this paper attempts to explore the impact of education on income inequality in China from the perspective of opportunity equality. Firstly, this paper uses the instrumental variable method to measure the contribution share of education in the income distribution inequality of Chinese residents, and further decomposes the proportion of reasonable and unreasonable components under the framework of opportunity equality theory. The measurement results based on the Chinese General Social Survey (CGSS) data in 2017 show that: (1) The income inequality caused by education accounts for 50.87% of the total income inequality, and the proportion coefficient has significant age heterogeneity, indicating that the difference in education level is one of the important reasons for the uneven income distribution of Chinese residents. (2) Among the income inequality caused by education in China, the unreasonable component accounts for about 44%. This part of inequality is mainly determined by environmental factors for which individuals should not bear responsibility, such as family background, social environment and individual characteristics. In the lower age group, the proportion of income inequality caused by education attributed to environmental factors is higher. (3) The decomposition results based on the Shapley value method show that among all environmental factors, the contribution share of family cultural factors is as high as 42.94%, followed by family economic factors and social environmental factors (23.50% and 23.36% respectively), and the remaining 10.20% is attributed to individual characteristic factors. There are some differences in the contribution share of various environmental factors in different age groups. In addition, the longitudinal comparison of the measurement results based on CGSS data in different years shows that the above main indicators fluctuate irregularly in a small range, and the basic conclusions of this paper are robust. This study examines the important role of education in the income distribution of Chinese residents from the perspective of equity, and further explores the causes of unreasonable and unfair parts of income inequality caused by education, which provides further theoretical support and factual basis for the implementation of relevant policies to promote income distribution equity.

Emerging Challenges in Rural Non-Farm Sector and Inequality in Rural India

Purpose: This paper highlights the changing patterns of income diversification and the effects of various socio-economic factors influencing the non-farm (NF) income of rural households in India. The study also explores the inequality effects of the non-farm earnings of the households by using the Fields inequality decomposition. 
 Method: The study compares and evaluates the determinants and trends of inequality in 2004-2005 and 2011-2012 in the NF sector. It uses nationally representative data from two rounds of the Indian Household Development Survey (IHDS), which includes a panel of 36,278 households at all levels in India. The Censored Least Absolute Deviation (CLAD) model is used to estimate household determinants for non-farm income. The Fields decomposition decomposes total income inequality by considering the socio-economic factors.
 Results: The study finds that variations in non-farm earnings have increased. Field's Income Inequality Decomposition estimates show that income inequalities between households are significantly high due to factors such as education, level of the household head, land ownership, and population density, but also appear to be declining in 2011-12. Also, the earning gaps based on gender, age, and geographical zones have increased. 
 Implications: Overall, the non-farm income during the studied period was observed to be biased towards the better-off households. However, it opened up opportunities for underprivileged households as well. The non-farm sector has huge potential in augmenting incomes for unprivileged rural households. Therefore, the government should pay attention to this sector as a means of reducing income inequality and alleviating poverty.

THE RELATIONSHIP OF SOCIAL TRANSFER EXPENDITURES-INCOME INEQUALITY: A COMPARATIVE PANEL CAUSALITY ANALYSIS

Pek çok gelişmiş ve gelişmekte olan ülke açısından gelir eşitsizliği seviyelerinde meydana gelen 
 artışlar; kamunun vergiler, transfer ödemeleri ile kamusal mal ve hizmet sunumu aracılığıyla ekonomiye 
 müdahalesinin yetersiz ve etkinsiz gerçekleşmesi nedeniyle kaçınılmaz olarak ortaya çıkmaktadır. 
 Özellikle, kamu harcamaları çerçevesinden bakıldığında düşük gelir gruplarına yapılan transfer 
 ödemelerinin gelir eşitsizliğini azaltmakta kilit bir rol oynadığı öne sürülebilmektedir. Zira, birçok 
 çalışmada toplam gelir eşitsizliğinin analiz edilmesinde en yaygın kullanılan ölçüt olan Gini katsayısının 
 kamunun yeniden dağıtım politikaları içerisinde en fazla transfer harcamalarına duyarlı olduğu sonucuna 
 ulaşılmıştır. Bu çalışmanın amacı, sosyal transfer harcamaları ve gelir eşitsizliği ilişkisinin ülkelerin gelir 
 düzeyindeki farklılıkların analize dâhil edilerek ortaya koyulmasıdır. Bu çerçevede, analize konu edilen 60 
 adet ülke Dünya Bankası’nın sınıflandırmasına göre ayrıştırılmış ve 1996-2018 yıllarını kapsayan 
 dönemde sosyal transfer harcamaları-gelir eşitsizliği ilişkisinin tespiti için Dumitrescu-Hurlin panel 
 nedensellik analizi kullanılmıştır. Elde edilen bulgular, hem yüksek gelir grubuna dâhil ülkelerde hem de 
 yüksek-orta ve düşük-orta gelir grubuna dâhil ülkelerde sosyal transfer harcamaları ve gelir eşitsizliği 
 arasında çift yönlü nedensellik ilişkisi bulunduğuna işaret etmektedir. Ancak, yüksek gelir grubuna dâhil 
 ülkelerde bu ilişki göreli olarak daha güçlü ortaya çıkmaktadır.

Income inequality among agricultural households in India: A regression‐based decomposition analysis

AbstractThis article assesses the nexus between land and income inequality among agricultural households in rural India based on a national survey of farmers. The study also assesses the contribution of other sources of income to this inequality. At the onset, we estimate the extent of land and income inequality using the Gini coefficient, Palma ratio, and quantile distribution. Further, we examine the effects of income components and sociodemographic, production theory‐related, and geographic variables on total income inequality among agricultural households at the national level using regression‐based inequality decomposition (RBID) analysis of income function. The evidence indicates that both land and income inequality are the maximum in the agriculturally developed states. The results of RBID show that land size explains the highest share of income inequality among agricultural households, followed by crop productivity at the household level. The analysis further statistically validates that the share of wage and livestock income has an inverse relationship with total inequality among agricultural households. These results provide firm empirical evidence to assess policies suggested to increase alternative sources of income among land‐poor petty producers.

COVID-19 and Income Inequality: Evidence from Monthly Population Registers

We measure the distributional impact of the COVID-19 pandemic using newly released population register data in Sweden. Monthly earnings inequality increased during the pandemic, and the key driver is income losses among low-paid individuals while middle- and high-income earners were almost unaffected. The pandemic had a larger negative impact on private-sector workers and on women. Using data on individual take-up of government COVID-19 support, we show that policy significantly dampened the inequality increase, but did not fully offset it. Annual total market income inequality, which also includes capital income and taxable transfers, shows similar patterns of increasing inequality during the pandemic.

Unveiling the Cosmic Race: Racial Inequalities in Latin America

This paper provides evidence of the welfare consequences of racial discrimination at the individual and racial inequality at the country levels in Latin America. Latin American countries built their national identities through a 'melting pot' ethnic figure: the 'Cosmic Race' or the mixed-race descendant from the European, Indigenous, and African populations. However, 'mestizaje' identity veiled income inequalities between racial groups. Using LAPOP AmericasBarometer data, I compile information on skin tone and proxies for income for nearly 100 thousand individuals across Latin American countries during the last decade. The purpose of the paper is twofold. In the first part, I use Spatial First Differences to provide causal estimates of the racial income gap: out of an eleven-color palette, every darker skin tone has at least 8 percent less monthly income per capita. I also use Oaxaca-Blinder decompositions to provide causal evidence that racial discrimination is the main mechanism driving the racial gap: two-thirds of the latter is due to racial discrimination, with substantial heterogeneity between countries. In the second part of the paper, I estimate newly racial inequality measures at the country level. Countries with higher income inequality between racial groups have worse economic development: a one percent increase in the ratio of racial over total income inequality correlates with a decrease of nearly 4 percent in GDP per capita. The results suggest that, besides justice or reparations, progressive policies on income or wealth can diminish racial inequalities and improve aggregate welfare.

The redistributive role of government social security transfers on inequality in China

The purpose of this paper is to evaluate the redistributive role of government social security transfers on inequality in China. We attempt to answer two questions. First, does inequality of after-transfer income narrow, compared to that of before-transfer income? Second, given the scale and distribution of existing government social security transfers, will a small percentage increase in the transfers narrow or widen the inequality of total income? By employing the methodologies of the Musgrave-Thin (MT) index and decomposition of the Gini coefficient of total income by its sources, we find a positive answer to the first question and a negative answer to the second question. Government social security transfers have a positive role on inequality in the sense that the Gini coefficient of after-transfer income is smaller than that of before-transfer income. However, government social security transfers have a negative role on inequality, as current inequality will go up if there is a universal increase in government social security transfers for all recipients. Of all the components of government social security transfers, formal sector pensions are most unequalizing, whereas dibao and rural pension benefits have equalizing effects on the income distribution in China.

Decomposing Income Inequality in the United States, 1962-2018

Income inequality in the United States has been on the rise. To understand why, we use several complementary techniques to decompose total income inequality into components attributable to five personal traits: sex, race, education, occupation, and industry of work. By examining how income differences along these traits add to net inequality, and how their contributions have changed over time, we vet competing hypothesis for the growing earnings gap. Our findings suggest that changes in human capital accumulation, in particular, the returns to education, drove much of the recently observed changes.