Income Inequality In India Research Articles

The Mediating Role of Perception of Society Between Income Inequality and Life Satisfaction. Insights from the European Social Survey

The mechanisms between inequality and well-being are not fully known. There is a body of knowledge assuming personal information on the social environment can be important here. In this article, we consider this perception of society (POS) as a mediator between income inequality and life satisfaction. Our research questions are: 1) How are various measures of income inequality associated with life satisfaction, and 2) does the POS mediate the effect of inequality on life satisfaction? The individual-level data come from the European Social Survey 2008 (N = 56,752) and the macro-level data from OECD and World Bank. We use a comprehensive and psychometrically valid measure of the POS to capture individuals' full societal perceptions. The data is analysed with a multilevel linear regression and the mediation effect is tested with a Sobel test. The results reveal significant differences between indicators of income inequality in their ability to predict life satisfaction. Moreover, POS is strongly associated with life satisfaction and mediates the association of income inequality on life satisfaction. In addition, we observed the so-called ‘saturation effect.’ The effect of POS depends on objective conditions—the better the society, the smaller the effect.

Foreign Direct Investment and Income Inequality Nexus in Middle-Income Countries: Exploring the Role of Research and Development Expenditure

The study explored the role of Research and Development Expenditure in determining the linkages between foreign direct investment (FDI) and income inequality within middle-income countries. World development indicators were used as a source for panel secondary data from 1990-2023. Panel unit root analysis was employed for data stationarity. The Panel co-integration analysis using the Fully Modified Ordinary Least Square (FMOLS) technique was applied to obtain correlations among three core variables. The findings explain that co-integration exists between variables; all variables are stationary at the first difference level. The FMOLS model incorporates the impact of FDI on the income inequality index with control variables. The analysis suggests that FDI in middle-income countries may decrease income inequality. Increasing research and development expenditures can reduce income inequality by promoting innovation and reducing reliance on external funding.

Exploring the causes and consequences of income inequality in India

The unequal income distribution among people or households within a society is called income inequality. It is a crucial socioeconomic problem that has an impact on the foundation of all countries. With its wide diversity and intricate social structure, India is a country where economic inequality poses special difficulties and ramifications. This essay investigates the origins and effects of income disparity in India, looking at its historical development, relevance, and the urgent need for in-depth study in this area. The degree to which income is dispersed unevenly among a population is known as income inequality. Numerous income distribution ratios, the Lorenz curve, and the Gini coefficient are among the statistical methods frequently used to measure this inequality. Greater inequality is indicated by a higher Gini coefficient, and more equitable income distribution is shown by a lower coefficient. Income inequality can take many different forms in India, such as regional differences, urban-rural splits, and socioeconomic stratifications.

Income differentiation in Kazakhstan: an in-depth examination of its economic and social drivers

This study comprehensively identifies and quantitatively assesses the factors influencing income differentiation in Kazakhstan, demonstrating the multifaceted relationships between income inequality and various economic indicators. Utilizing quantitative research methodology, the investigation employs an Autoregressive Distributed Lag model to analyze the impact of GDP, real income, social aid, migration, and inflation on the Gini index of Kazakhstan from 2001 to 2022. Data was sourced from the Bureau of National Statistics, ensuring a robust and reliable foundation for the analysis. The investigation highlights the relevance of addressing income inequality in pursuing economic growth balanced with social justice, emphasizing global commitment to sustainable development goals. The results show that GDP growth and migration contribute to reducing income inequality, whereas increases in real income and, unexpectedly, social assistance are associated with higher inequality levels. Inflation's impact on income inequality was statistically insignificant, suggesting its effects may be ambiguous depending on other conditions. Overall, the findings advocate for developing multilevel strategies and policies aimed at reducing income inequality, encompassing economic measures, social investments, and improved labor market regulation to achieve more equitable and sustainable economic development in Kazakhstan.

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.

Unappreciated healthcare inequality against PM2.5-related mortality risk

Understanding the inequality of PM2.5-related health is crucial for promoting health, building a just society, and advancing multiple Sustainable Development Goals goals. However, previous research has predominantly concentrated on PM2.5 exposure inequality, neglecting varied prompt responses and protective behaviors against it. Here, we established the relationship between short-term healthcare expenditure and PM2.5 concentration using the number and amount of healthcare transactions across all healthcare categories based on the Union Pay data. We also assessed daily city-specific PM2.5-related mortality and healthcare expenditures and evaluated their inequalities among cities according to the income inequality index, the Gini coefficient. The results show that short-term exposure to PM2.5 leads to severe physiological and health-related economic burdens on Chinese residents. From 2017 to 2019, 77.8 (34.5–121.1) thousand deaths were attributed to daily PM2.5, with healthcare expenditures reaching 93.7 (69.1–118.3) billion Chinese Yuan. Additionally, there were significant inequalities in PM2.5-related mortality and healthcare expenditures among cities. The inequality index for PM2.5-related healthcare expenditures was 0.53, while the inequality index for PM2.5-related mortality was 0.13. The greater inequality in healthcare expenditures than in mortality, implying inadequate healthcare resources amplify the health inequality related to PM2.5 exposure. 28.6% of Chinese cities lacked affordable healthcare resources to address the high physiological burden attributable to PM2.5. Our multidimensional exploration is essential for formulating effective policies addressing environmental health inequality. Focusing on these cities with disproportionate challenges is crucial for creating a more equitable and sustainable society.

Ethnic fractionalization and income inequality: the case of Kazakhstan

Ethnic diversity has an impact on many areas of social life, which has led to an extensive layer of research on relationships in this area. Many authors have studied in detail the impact of ethnic diversity on conflicts, instability, domestic politics, other various social and cultural aspects. At the same time, the relationship between ethnic fractionalization and economic parameters remains insufficiently studied, which leaves a wide field for relevant research, especially at the level of individual countries, since most of the work is devoted to cross-country comparative analysis of the relevant parameters. One of the most actual problems in the context of ethnic heterogeneity is its relationship with income inequality. This article presents the results of a study of the relationship between ethnic diversity, estimated on the basis of the ethno-linguistic fractionalization (ELF) index, and two indicators of income inequality — the Gini coefficient and the inter-decile income share ratio (S90/S10). The analysis of this relationship was carried out on the example of one country — Kazakhstan — by comparing the corresponding indicators for seventeen regions. The results of the analysis showed the presence of a stable and noticeable relationship, expressed in the growth of income inequality as ethnic diversity grows in the regions of the country. It was revealed that in the most ethnically homogeneous regions, income inequality indicators are minimal, while in the most ethnically diverse regions they are much higher. A significant correlation was also found between ethnic fractionalization and indicators of income inequality. The results obtained are generally correspond to the results of a number of cross-country studies, but in the case of Kazakhstan they are more distinct, which can be interpreted as confirmation of the relationship between ethnic diversity and income inequality in general.

Measuring income inequality via percentile relativities

The adage “the rich are getting richer” refers to increasingly skewed and heavily-tailed income distributions. For such distributions, the mean is not the best measure of the center, but the classical indices of income inequality, including the celebrated Gini index, are mean based. In view of this, it has been proposed in the literature to incorporate the median into the definition of the Gini index. In the present paper we make a further step in this direction and, to acknowledge the possibility of differing viewpoints, investigate three median-based indices of inequality. These indices overcome past limitations, such as: (1) they do not rely on the mean as the center of, or a reference point for, income distributions, which are skewed, and are getting even more heavily skewed; (2) they are suitable for populations of any degree of tail heaviness, and income distributions are becoming increasingly such; and (3) they are unchanged by, and even discourage, transfers among the rich persons, but they encourage transfers from the rich to the poor, as well as among the poor to alleviate their hardship. We study these indices analytically and numerically using various income distribution models. Real-world applications are showcased using capital incomes from 2001 and 2018 surveys from fifteen European countries.

Towards Achieving the Sustainable Development Goals (SDGs): The Impact of Debts on Income Inequality in Africa

The Agenda for Sustainable Development provides a framework for the creation of a better and sustainable future for all. The Sustainable Development Goals (SDGs) focus on addressing global challenges, including income inequality. Among others, the SDGs also commit countries to work towards reducing income inequality and as such, lowering income inequality is one of the key issues in Africa. However, given the high levels of debt on the continent, reducing income inequality could be a challenge. Majority of the literature examines the link between debts and economic growth with little attention paid to the impact of debts on income inequality. Moreover, not much is known on whether the relationship between debt and income inequality is non–linear. This study therefore contributes to the existing research efforts by investigating the threshold effects of debts using data from 24 African countries by relying on the sample splitting and threshold estimation approach. The results reveal that, while debts generally dampen income inequality, unbridled debt accumulation above the estimated thresholds does not decrease income inequality, indicating that the income inequality–reducing impact holds at lower levels of debt–to–GDP ratio. This evidence is insensitive to different indicators of income inequality and debts. Findings from this study show how increasing indebtedness contributes to widening income inequality in Africa.

New approach to measuring income inequality

We show that the conventional income inequality indexes assess income inequality incorrectly because of three problems. The unequally distributed (UD) income-based approach solves the problems, decomposes income inequality into two kinds of departure from equality, and provides two indexes. The comprehensive assessment of income inequality requires the integration of two kinds of departure. This paper proposes the relative UD (RUD) income-based approach. The RUD income-based approach combines the cumulative distribution function and quantile function of the RUD income and produces a new index integrating two kinds of departure. We investigate the properties of the new index and demonstrate its applicability through example income distributions.

Analysis on Economic Inequality in India

The paper examines income inequality in India from 1951 to 2022, highlighting trends and nonlinear patterns in the top 10% and bottom 50% income shares of national income, as well as the gap between these shares. The analysis employs semi-log and double log regression models, the HP filter model, the Hamilton regression filter model, and the ARIMA (p, d, q) forecast model. The findings indicate that the top 10% income share increased steadily, while the bottom 50% share decreased monotonically. The gap between these shares narrowed until the 1980s, after which it widened. All trends are cyclical, with identifiable peaks and troughs. GDP has less influence than GDP per capita on the top 10% income share increase, while the reverse is true for the bottom 50%. The nature of the gap is U-shaped, with a 1% annual increase in GDP and GDP per capita leading to a 0.33% and 0.45% increase in the gap, respectively. The ARIMA (2,1,2) forecast model for the income share gap in 2050 suggests a convergence towards equilibrium in a stable manner, although it remains nonstationary due to an insignificant Moving Average process. This implies that inequality will not completely disappear by 2050. Policy recommendations are proposed for future discussions.

Growth and inequality trade-offs to eradicate absolute poverty

The relationship between growth, inequality and poverty remains elusive, despite considerable scholarship. To what extent can governments rely on growth to eradicate poverty without reducing inequality? We derive a closed-form relationship between a minimum income threshold, changes in the Gini index of income inequality and average national income required to meet this target, independent of the form of income distribution. We develop a generalized form of redistribution and validate it against historical changes in inequality. We use this formulation to illustrate feasible growth-redistribution strategies to raise entire populations above the International Poverty Line ($1.90/day) by 2030, the Sustainable Development Goal 1, in two selective countries: India and Rwanda. We show that meeting this target would require unprecedented rates of both growth and inequality reduction in Rwanda. India could not eradicate acute poverty by 2030 with growth alone, but it could with only a modest reduction in inequality.

Non-linear dynamics in finance–inequality nexus: time series evidence from the Indian economy

PurposeThe principal aim of this study is to examine the relationship between financial development and income inequality in India using the financial Kuznets curve (FKC) hypothesis.Design/methodology/approachThis study uses the autoregressive distributed lag (ARDL) model and the Toda–-Yamamoto causality test to investigate the long-run and short-run relationship and causality between financial development and income inequality. In addition, this study employs a principal component analysis (PCA) to construct a comprehensive financial development index.FindingsThe study found a long-run relationship between financial development and income inequality in India for the period under consideration. Trade is found to improve the income distribution, while inflation worsens income distribution. Moreover, the empirical results revealed a feedback causality between financial development and income inequality. The study results confirm an inverted U-shaped relationship between financial sector development indicators and income inequality, thus validating the FKC hypothesis for the Indian economy.Research limitations/implicationsThe study draws attention of the government and policymakers, urging them to focus on building a strong financial sector by improving its efficiency. This, in turn, will lead to enhanced financial stability and a reduction in income inequality. They should prioritise the development of high-quality and sustainable financial products and services to ensure the robust growth of the financial sector.Originality/valueTo the best of our knowledge, this study is the latest of its kind to empirically test the financial development on income inequality and the FKC hypothesis simultaneously for the Indian economy using financial proxy variables from financial institutions (FIs) and financial markets (FMs) for the measurement of financial depth.

Income Inequality in India: An Empirical Analysis of Changing Paradigms

Income Inequality in India: An Empirical Analysis of Changing Paradigms

비동거 가구원 보정이 소득불평등지표 변화에 미치는 영향에 관한 연구

Since 2017, income inequality in South Korea has been measured using the Survey of Household Finances and Living Conditions. This survey combines income information gathered through surveys with highly reliable administrative data which include tax data from the National Tax Service and health insurance payment data from the National Health Insurance Service. Based on the Survey of Household Finances and Living Conditions, income inequality in South Korea has steadily decreased from 2017 to 2019. However, there are some who contend that income distribution has actually become more unequal during this same period. In light of these differing viewpoints, the purpose of this study is to examine whether the measure of income inequality derived from the Survey of Household Finances and Living Conditions accurately portrays the current income inequality situation in South Korea. The technical reports indicate that the survey considers a family of origin to include one-person households who move out for work or study. The issue here is that a relatively high percentage of these one-person households, especially young single adults, tend to have lower incomes and poorer living conditions. Therefore, this study aims to examine how the separation of these young one-person household members who live independently for work or study from their original households impacts the trends in income inequality from 2017 to 2019 as reported in the Survey of Household Finances and Living Conditions. The results reveal that when adjustments are made for one-person households, there are discernible differences in income inequality indices such as the Income quintile share ratio, Gini coefficient, and Palma ratio between the adjusted data and the original data. Further analysis of income inequality trends by age groups suggests that, after adjusting for non-cohabiting household members, the worsening income inequality among young adults in their twenties contributes to the differences observed in income inequality trends from 2017 to 2019 between the original data and the adjusted data.

Income inequality and pandemics: insights from HIV/AIDS and COVID-19—a multicountry observational study

ObjectivesAssess the relationship between income inequality and HIV incidence, AIDS mortality and COVID-19 mortality.DesignMulticountry observational study.Setting217 countries for HIV/AIDS analysis, 151 countries for COVID-19 analysis.ParticipantsUsed three samples of national-level data:...

LIWC Indicators of Cross-Country Income Inequality at the United Nations General Debate (1987-2020): An Elastic Net Analysis

Can a set of Linguistic Inquiry and Word Count (LIWC) indicators differentiate between the UN speeches from higher-income and lower-income countries? Based on 34 years of 6,095 speeches (14,300,539 words) and dynamic income grouping, an elastic net analysis selects 18 such categories. The hypothetical explanations are discussed with four theoretical perspectives: gender-neutral language, politeness, scarcity mindset, and expectation states theory. The findings on cross-group LIWC variation provide UN-setting linguistic evidence for the theories and insights into the language of global income inequality between countries.

Generalised Income Inequality Index

SummaryThis paper proposes a deep generalisation for income inequality indices. A generalised income inequality index that depends on two parameters and that involves a large set of income inequality indices in the same framework is proposed. The two parameters control the sensitivity of the generalised index to different levels of the income distribution. A thorough investigation of the generalised index paves the way for understanding the influence of the low, middle and high incomes on various income inequality indices and thereby facilitates the choice of multiple indices simultaneously for a better analysis of inequality as advocated by several recent studies. Moreover, two methods for estimating the generalised index in the case of finite populations are shown. A new method for estimating the inequality indices is proposed.

The association between income inequality and adolescent body mass index: findings from the COMPASS study (2016-2019).

Income inequality has been linked to high and unhealthy body mass index (BMI), though there is a dearth of evidence in adolescents. Therefore, this study examines the association between income inequality and BMI in a large sample of Canadian adolescents. A pooled cross-sectional design was used. Participants were adolescents (n = 101,901) from 157 Canadian secondary schools participating in the 2016-2017, 2017-2018, or 2018-2019 waves of the Cannabis, Obesity, Mental health, Physical activity, Alcohol, Smoking, and Sedentary behaviour (COMPASS) study. BMI was calculated from self-reported height and weight and converted to World Health Organization (WHO) z-BMI scores. Gini coefficients were calculated at the census division level (n = 49) using data from the 2016 Canadian Census. Multilevel modelling was performed to account for the clustering of students nested within schools, which were nested within census divisions. Interactions were included to determine whether associations were heterogeneous for males and females. Income inequality demonstrated a non-linear association with WHO z-BMI score (z-Gini: β= 0.05, 95%CI: 0.02, 0.08; z-Gini2: β = -0.02, 95% CI: -0.04, -0.01) among adolescents after adjusting for student-, school-, and census division-level covariates. This association was more pronounced among females. The association between income inequality and BMI, being overweight, or having obesity appears to be non-linear. Public health units and schools may benefit from incorporating upstream factors such as income inequality into their interventions attempting to promote healthy weights.

Revisiting the finance-growth nexus in sub-Saharan Africa: Does the level of income inequality matter?

In this paper, the modulating effect of income inequality in the finance–growth nexus using data from 29 sub-Saharan African (SSA) countries is examined. The study examines i) whether financial development still spurs economic growth in the studied countries, and ii) whether income inequality modulates the effect of financial development on economic growth. Three proxies of financial development and four income inequality indicators are used. The financial development indicators used include the financial development index, financial institutions index, and financial markets index, while income inequality is measured by the Palma ratio, the Gini coefficient, the Atkinson index, as well as the composite inequality (Comp) derived from the principal component analysis (PCA). The Generalised Method of Moments (GMM) has been used to examine this linkage. The study found that, on the whole, the beneficial effect of financial sector development on economic growth in the studied countries is weak, at best. This finding has been corroborated by the results of the interaction models, which show that income inequality interacts with financial development to yield a net negative effect on economic growth in four specifications, but a net positive effect in only two specifications. This finding is not surprising given the high level of income inequality that is currently ravaging some of the SSA countries. Policy implications are discussed.