Determinants Of Income Inequality Research Articles

Determinants of Income Inequality in South Africa: A Vector Error Correction Model Approach

The issue of income disparity has long plagued South Africa because of the political environment that existed before the country’s 1994 democratic transition. Based on the widely used Gini index, which gauges global inequality, the nation routinely has some of the highest rates of income disparity in the world. Income inequality in South Africa keeps rising even after a number of frameworks and policies have been put in place, which has a big influence on society. Thus, it is essential to comprehend the causes of income disparity and put suitable policies in place to remedy it. The purpose of this study is to look into the relationship between South Africa’s income disparity and its determinants. Using the Vector Error Correction Model (VECM) approach, this study empirically examines the effects of government spending on social grants, gross savings, population growth, and economic growth on income inequality from 1975 to 2017. Data on the Gini index are sourced from the Standardized World Income Inequality Database (SWIID). Findings reveal a statistically significant negative correlation between government spending on social grants and income inequality. Moreover, income inequality demonstrates a negative relationship with both gross savings and economic growth. However, population growth exhibits a positive correlation with income inequality. This study highlights the significance of implementing a comprehensive strategy to address income inequality in South Africa. This strategy should involve augmenting government expenditure on social grants, cultivating a savings culture within households, and enacting policies that incentivize job creation, particularly in areas with rapid population growth. In addition to making a substantial contribution to the body of evidence already available on income disparity, this study offers insightful information to policymakers working to improve the socioeconomic climate in South Africa.

Digitalisation and income inequality in Central and Eastern European countries

The COVID-19 pandemic has highlighted the importance of digital technologies in business and daily life. The paper aims to explore the theoretical and empirical aspects of the relation between digitalisation and income inequality in Central and Eastern European (CEE) countries between the years 2000-2020. It contributes to existing research on determinants of income inequality, focussing on the potential negative role of digitalisation as an unnoticeable driver of income inequality in CEE countries. To investigate the potential impact of digitalisation on income inequality, empirical analysis was performed for the sample of 10 CEE countries, namely Bulgaria, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, the Slovak Republic and Slovenia. The results of canonical correlation analysis indicated that the sets of variables related to digitalisation and inequality as a group are significantly related to each other and a strong correlation exists between them. The relative contribution of each indicator to each standardised function showed that the highest values of significant standardised coefficients were observed for income inequality indicators such as the top 10% share, the Gini coefficient, and the top 1% share, while in digitalisation measures, the highest value was observed for Internet users and fixed and mobile broadband subscriptions.

Globalization — Inequality Nexus in the US and UK: A Multi-Dimensional Perspective

Equitable income distributions occupy a top spot on the list of the United Nations (UN) Sustainable Development Goals (SDG[Formula: see text]). Nonetheless, prior empirical inquiries noted several factors, including globalization as the determinant of income inequality, albeit divergent inferences. However, very little is known about the potential effects of other variants of globalization (economic, social, cultural and political) on income inequality. Hence, this study, through a multi-dimensional scale, provides a comprehensive empirical overview of the effects of globalization on income inequality in the United States and the United Kingdom between 1970 and 2018. The study adopts the Autoregressive Distributed Lag (ARDL) and Kernel Regularized Least Squares (KRLS) models for broad-based empirical narratives. The empirical estimates rectify that globalization and its variants influenced income distributions significantly more in the US than in the UK. Particularly, at the 25th and 50th quantiles, globalization produced significant inequality-reducing effects in the UK. This indicates varying outcomes across the distributions of income inequality. Hence, constant monitoring is critical to curtail the influence of globalization on income distributions. The study also revealed that the existing patterns of income distributions in both countries would not guarantee the attainment of SDG[Formula: see text]. However, if laborers are compensated adequately, the attainment of SDG[Formula: see text] is certain. Thus, relevant policy options that will ensure equitable prosperity in both countries are highlighted.

Rise in income inequality due to pandemic in developing economies

AbstractThe outbreak of coronavirus pandemic (COVID‐19) has severely affected global economies and Pakistan. The core focus of this study is to analyse income inequality before and after the pandemic in developing economies and other urbanised areas of Pakistan. Gini coefficient has been employed to estimate income inequality for developing economies and Pakistan, whereas the Theil index is assessed across the regions, provinces and other urban areas of Pakistan. For that purpose, the study has worked on ‘special survey evaluating the Socio‐economic Impact of COVID‐19 on the well‐being of people’ published by the Pakistan Bureau of Statistics. This study focuses on seeing the consequences of COVID‐19, especially in the context of income inequality caused by the lockdown imposed in the countries in hand. Further, determinants of income inequality are estimated before and after the pandemic. This study anticipates that fair income distribution is the only solution to decrease disparities. Moreover, to achieve goal 10 of Sustainable Development Goal, it is significant to work on provision of opportunities that help in increasing the income opportunities for the underprivileged segment of society. This solution is achievable only if the provision of education and employment increases, eventually reducing the ever‐increasing wage gap in the long run. So far no study has empirically evaluated the impact of income inequality caused by the pandemic in Pakistan on the district level. The novelty of the study is that it has assessed the impact of income inequality before and after the pandemic in developing economics and than evaluated the urbanized areas of Pakistan on the basis of income inequality post and pre‐pandemic situation, hence fill the research gap as no study so far has been done on it.

Determinant of Income Inequality in Central Java Province

Determinant of Income Inequality in Central Java Province

Exploring the effect of industrial agglomeration on income inequality in China.

Income inequality is a good indicator reflecting the quality of people's livelihood. There are many studies on the determinants of income inequality. However, few studies have been conducted on the impacts of industrial agglomeration on income inequality and their spatial correlation. The goal of this paper is to investigate the impact of China's industrial agglomeration on income inequality from a spatial perspective. Using data on China's 31 provinces from 2003 to 2020 and the spatial panel Durbin model, our results show that industrial agglomeration and income inequality present an inverted "U-shape" relationship, proving that they are the non-linear change. As the degree of industrial agglomeration increases, income inequality will rise, after it reaches a certain value, income inequality will drop. Therefore, Chinese government and enterprises had better pay attention to the spatial distribution of industrial agglomeration, thereby reducing China's regional income inequality.

Determinants of Income Inequality in a Time Perspective in Indonesia

The development orientation which is more dominant on growth, has been impaled to widen the inequality gap. The purpose of this study is to analyze the short-term and long-term effects of several determinants of income in Indonesia during 1998-2021. Data sourced from the World Bank in a time series format. The study method uses descriptive quantitative analysis with the Error Correction Model approach. The Gini index is used as the dependent variable, while the independent variables include the ratio of the work force graduates above senior high school, urban population growth, the agricultural sector, haunting, and fisheries, and per capita GDP growth. The stationarity test results show that stationarity occurs in the first derivative data. Cointegration test results using the Engle-Granger method show that the model built has cointegration. The results of the long-term regression show that two variables have a significant effect on the Gini index, namely the ratio of the work force graduates above senior high school which has a positive effect, and the urban population growth rate which has a negative effect. In the short term, the ratio of the work force graduates above senior high school contributes significantly to the increase in the Gini index. Meanwhile, other predictor variables have no significant effect on the Gini index in Indonesia. The lack of support from the agricultural sector in pushing the Gini index down, and the positive role of the highly educated work force, reflects the ongoing development process which still seems exclusive.

The Kuznets Curve, Information and Communication Technology, and Income Inequality in Malaysia

This study re-investigates the presence of the Kuznets curve in the context of Malaysia, by employing an autoregressive distributed lag (ARDL) approach. We seek to examine the non-linear impacts of economic growth on income inequality by investigating the existence of a second turning point to the relationship. Furthermore, we also assess the impacts of information and communication technology (ICT) (through internet, mobile, and broadband usage) on income inequality, besides the determinants of income inequality which have been extensively studied within the framework. This endeavour leveraged a time series analysis whereby the data was employed from the time period of 1970–2018. Our estimation results support the S-curve hypothesis that relates economic growth to inequality starting from the back portion of the inverted U-shaped curve. Our results confirm that ICT can actually be part of an active economic policy aiming to reduce existing income inequalities.

The Kuznets Curve, Information and Communication Technology, and Income Inequality in Malaysia

This study re-investigates the presence of the Kuznets curve in the context of Malaysia, by employing an autoregressive distributed lag (ARDL) approach. We seek to examine the non-linear impacts of economic growth on income inequality by investigating the existence of a second turning point to the relationship. Furthermore, we also assess the impacts of information and communication technology (ICT) (through internet, mobile, and broadband usage) on income inequality, besides the determinants of income inequality which have been extensively studied within the framework. This endeavour leveraged a time series analysis whereby the data was employed from the time period of 1970–2018. Our estimation results support the S-curve hypothesis that relates economic growth to inequality starting from the back portion of the inverted U-shaped curve. Our results confirm that ICT can actually be part of an active economic policy aiming to reduce existing income inequalities.

Income inequality in Pakistan

PurposeIn most developing countries like Pakistan, the gap between rich and poor has widened over time. This polarization in the society hinders economic growth and acts as a barrier for development and well-being. The proportion of income distribution varies across the population sub-groups in Pakistan. Therefore, it is important to study the income distribution effects across the four provinces of Pakistan.Design/methodology/approachThis study attempts to explore the root causes of income inequality and its changes in a dynamic context across the four provinces of Pakistan over a decade (2005–2006 to 2015–2016) by using a regression-based inequality decomposition method.FindingsAge, gender and higher education are the most prominent factors explaining the level of inequality across the four provinces of Pakistan. Higher education enhances the level of inequality in all provinces but contributes negatively to its changes except for Balochistan. Skilled agricultural and fishery workers in Balochistan have contributed significantly to reducing the level of inequality over the decade but not to its changes. Healthy contribution of the unpaid family workers in economic activities has reduced the level of inequality in Punjab and Balochistan and contributed positively to the change in income inequality. Employer or self-employed workers enhance the level of income inequality but contribute negatively to its changes for Punjab and Balochistan.Originality/valueTo date, inequality literature on Pakistan focuses on economic growth and poverty. A handful studies focus on the determinants of income inequality in a static context. This study goes beyond the static decomposition tools and attempts to explore the determinants of inequality in a dynamic context.Peer reviewThe peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-09-2021-0573.

Role of Age and Education as the Determinant of Income Inequality in Poland: Decomposition of the Mean Logarithmic Deviation.

Measures of inequality can be used to illustrate inequality between and within groups, but the choice of the appropriate measure can have different implications. This study focused on the Mean Logarithmic Deviation, the measure proposed by Theil and based on the techniques of statistical information theory. The MLD was selected because of its attractive properties: fulfillment of the principle of monotonicity and the possibility of additive decomposition. The following study objectives were formulated: (1) to assess the degree of inequality in the population and in the distinguished subgroups, (2) to determine the extent to which education and age influence the level of inequality, and (3) to ascertain what factors contribute to changes in the level of inequality in Poland. The study confirmed an association between the level of education and the average income of the groups distinguished on this basis. The education level of the household head remains an important determinant of household income inequality in Poland, despite the decline in the “educational bonus”. The study also found that differences in the age of the household head had a smaller effect on income inequality than the level of education. However, it can be concluded that the higher share of older people may contribute to an increase in income inequality between groups, as the income from pension in Poland is more homogeneous than the income from work in younger groups. Moreover, the current paper seeks to situate Theil’s approach in the context of scholarly writings since 1967.

Determinants of Income Inequality in Ethiopia

Determinants of Income Inequality in Ethiopia

Determinants of Income Inequality in Europe

본 연구는 유럽지역의 1980년부터 2019년의 40년 동안 경제성장과 분배의 변화가 소득계층별 평균소득에 미치는 영향에 대한 실증적 연구이다. 주요 분석결과는 다음과 같다. 첫째, 경제성장은 소득계층별 평균소득에 양(+)의 영향을 주는 것으로 나타났으며, 분배의 악화는 소득계층별 평균소득에 음(-)의 영향을 주는 것으로 나타났다. 이는 경제성장을 통한 계층별 소득의 증가가 발생할 수 있으며 분배의 악화를 통한 계층별 소득의 감소를 경험할 수 있음을 의미한다. 둘째, 평균적인 의미에서의 영향이 아닌 소득계층별로 차별적인 영향의 존재 여부를 검정하기 위해 소득분위별로 구분하여 추정한 결과는 경제성장에 의한 영향은 소득계층별 차이가 뚜렷하지 않거나 크지 않았지만, 분배의 변화에 대한 영향은 소득분위별로 차이가 크게 나타났다. 대부분의 저소득층에서는 불평등의 증가로 인해 소득의 감소를 경험했으며, 최상위 계층에서는 오히려 불평등의 증가가 소득의 증가를 가져오는 것으로 분석되었다. 이는 저소득층의 경우 성장과 분배는 상호 대체재(substitutes)적인 성격으로서 분배의 악화가 발생하는 경우 저소득층의 평균소득의 유지를 위해서 충분한 경제성장이 이루어져야 하는 trade-off 관계에 있음을 의미한다.

States of inequality: Politics, labor, and rising income inequality in the U.S. States since 1950

This paper uses power resource theory to investigate the determinants of rising income inequality in the U.S. states from 1951–2018. Specifically, we analyze how political party control of national- and state-level government, presidential and gubernatorial election cycles, union strength and state right-to-work laws affect the Gini index and the Theil index—two measures that tap middle-class and upper-tail income inequality. A major contribution is to probe more deeply than previous research the historical and regional contingency of these processes by examining contrasting patterns between the Keynesian (1951–1980) and neoliberal (1981–2018) periods and between the Non- South and the South. We conduct three primary analyses. First, we explore the effects of these determinants over the entire period, net of other covariates. Second, we explore historical contingency by investigating how these effects differ during the Keynesian and neoliberal periods. Third, we explore regional contingency by examining differences in effects between the Non-Southern and Southern regions of the country. We find consistent evidence that political and labor power resources matter in the determination of income inequality; moreover, how they matter differs in substantively and theoretically important ways across period and region. We conclude with a discussion of what the results suggest for future developments in U.S. income inequality.

Determinants of Income Inequality Among Provinces: Panel Data Evidence from Indonesia

Determinants of Income Inequality Among Provinces: Panel Data Evidence from Indonesia

Financialization and income inequality: An extreme bounds analysis

Several theoretical hypotheses predict conflicting effects of financialization on income inequality, and the lack of consensus is reinforced by the mixed findings of related empirical studies. In this paper we address the model uncertainty issue by applying extreme bounds analysis (EBA) to examine the robustness of financialization variables as determinants of income inequality. The results suggest that financialization is a leading driver of income inequality and that the effects are larger when transmitted through financial markets. In addition, the results show that law and order, labour union density, population, globalization, remittances, education, and the agriculture sector share are also robust determinants of income inequality. Policy recommendations are put forward to reduce the power of the financial sector.

Determinants of income inequality among urban households in Ethiopia: a case of Nekemte Town

Determinants of income inequality among urban households in Ethiopia: a case of Nekemte Town

Redistribution and beliefs about the source of income inequality

Previous literature demonstrates that beliefs about the determinants of income inequality play a major role in individual support for income redistribution. This study investigates how people form beliefs regarding the extent to which work versus luck determines income inequality. Specifically, I examine whether people form self-serving beliefs to justify supporting personally advantageous redistributive policies. I use a laboratory experiment where I directly measure beliefs and manipulate the incentives to engage in self-deception. I first replicate earlier results demonstrating that (1) people attribute income inequality to work when they receive a high income and to luck when they receive a low income and (2) their beliefs about the source of income inequality influence their preferences over redistributive policies. However, I do not find that people’s beliefs about the causes of income inequality are further influenced by self-serving motivations based on a desire to justify favorable redistributive policies. I conclude that, in my experiment, self-serving beliefs about the causes of income inequality are driven primarily by overconfidence and self-image concerns and not to justify favorable redistributive policies.

Robust determinants of income distribution across and within countries.

Multicollinearity widely exists in empirical studies, which leads to imprecise estimation and even endogeneity when omitted variables are correlated with any regressors. We apply an innovative strategy, different from the usual tools (instrumental variable, ridge regression, and least absolute shrinkage and selection operator), to estimate the robust determinants of income distribution. We transform panel data into (quasi-) cross-sectional data by removing country and time effects from the data so that all variables become zero mean and orthogonal to the country dummies and time variable, and multicollinearity becomes very low or even disappears with the quasi-cross sectional data in any specifications regardless of country dummies and time variable being included or not. Our contribution is threefold. First, we build a general method to address the multicollinearity issue in panel data, which is to isolate the common contents of correlated variables and ensures robust estimates in different specifications (dynamic or static specifications) and estimators (within- or between-effects estimators). Second, we find no evidence for the Kuznets hypothesis within and across countries; investment is economically and statistically the most robust determinant of income inequality; meanwhile, labor income share shows robustly and consistently positive effects on income inequality, which challenges the related literature. Last, simulations with our estimates show that the total marginal effects of development (regarding GDP, capital stock and investment) on income inequality are very likely to be positive within and between countries except that the impacts on middle-60% and top-quintile income shares are not so likely to increase income inequality across countries.

Do tax and expenditure limitations exacerbate rising income inequality?

AbstractIn recent years, there has been a growing body of literature on the determinants of income inequality and a developing literature on tax and expenditure limitations (TELs). This study connects the two and asks the question—to what extent have state fiscal policies such as TELs impacted income equality? Using a panel of states from 1992 to 2010, we find consistent evidence that more restrictive tax and expenditure limitations exacerbate rising income inequality. Whether TELs are intentionally or unintentionally designed for such an effect is unclear, but what is clear is that these limitations placed on state governments limit their ability to implement policies that could have the potential to reduce income inequality.