Income Inequality In India Research Articles

The Effect of Sustainable Development on Economic Complexity in OECD Countries

Economic complexity showing a holistic measure of countries' economic productive power and characteristics has become a new tool for understanding the dynamics of the economy. Examining the relationship between sustainable development and this new tool is vital in determining new policies. By applying panel data of OECD countries covering different development levels from 1996 to 2017 to a data-driven dynamic econometric model, the research provides fresh insight between sustainable development and economic complexity. The results indicate that economic complexity is significantly affected by sustainable developments’ economic indicators such as GDP, FDI, R&D expenditure, social indicators such as human development, income inequality, and environmental indicators such as production-based CO2 emissions, renewable energy consumption, and greenhouse gas. The research, consequently, suggests that switching to technology and knowledge-based production processes, expanding qualified production factor capacity, raising social living standards, and making investments in the green economy will foster economic complexity while ensuring stable sustainability.

Parameterizing standard measures of income and health inequality using choice experiments.

When measuring inequality using conventional inequality measures, ethical assumptions about distributional preferences are often implicitly made. In this paper, we ask whether the ethical assumptions underlying the concentration index for income-related health inequality and the Gini index for income inequality are supported in a representative sample of the Swedish population using an internet-based survey. We find that the median subject has preferences regarding income-related health inequality that are in line with the ethical assumptions implied by the concentration index, but put higher weight on the poor than what is implied by the Gini index of income inequality. We find that women and individuals with a poorer health status put higher weight on the poor than men and healthier individuals. Ethically flexible inequality measures, such as the s-Gini index and the extended concentration index, imply that researchers have to choose from a toolbox of infinitely many inequality indices. The results of this paper are indicative of which indices (i.e. which parameter values) reflect the views of the population regarding how inequality should be defined.

Indicators of income and property inequality of citizens in the study and regulation of the country social development

The coronavirus pandemic has exacerbated the problems of poverty and socio-economic inequality and has increased the need to provide a comprehensive assessment of these phenomena in order to develop ways to reduce them. Currently, monetary and non-monetary methods are used to assess the level of inequality. Thus, in order to provide a more accurate and comprehensive assessment of inequality in the distribution of income and property security of the population, and with an emphasis on the qualitative side of the processes, according to the author, methods that are not related to monetary ones should also be used, including, in particular, indicators of deprivation, as well as subjective assessments.

Roots of Appearance and Persistence of Income Inequality: A case study of India

Income inequality among various forms of inequality, these days has attracted the serious attention of policymakers, rulers and thinkers. Each of these three groups has tried to identify the causes of occurrence and continuity through their views and, of course, provide solutions to mitigate it. The beginning of the third millennium was accompanied by an intensification of income inequalities within countries, so that the efforts of the international community, which had previously been able to reduce poverty and absolute hunger in the framework of documents such as the Millennium Development Goals, to reduce it, so far has failed to alleviate it. Identifying the causes of the emergence and perpetuation of income inequality in different economies is very significant at a time when the threats posed by income inequality are estimated in important documents such as the Global Threat Report as significant as terrorism. The subject of this article is to examine the textual, institutional and global causes of the continuing income inequality in India, which has recorded a remarkable economic growth rate these days. In India, a set of factors including the roots of social system deficiencies, economic growth, globalization and its tools such as privatization and trade liberalization are among the main causes of continuing inequality in Indian society today, which seems to be a continuous process due to the priority of economic growth against the reduction of income inequality for different governments in this country.

A longitudinal analysis of relationships between neighborhood context and underserved children's physical activity in a rapidly growing city.

Neighborhood context, which may be impacted by urban growth or residential mobility, is associated with childhood physical activity. This secondary analysis examined associations of objectively measured neighborhood characteristics with young children’s moderate-to-vigorous physical activity (MVPA) and sedentary/rest time (SRT) over a period of rapid infrastructure change.Underserved preschoolers (n = 426) from a 36-month obesity prevention intervention were included in a secondary analysis (2019–2020). Based on household addresses, participants were coded as movers or non-movers and linked to four neighborhood variables: 1) distance to recreation sites, 2) annual crimes, 3) annual stray dogs, and 4) Gini index of income inequality. Accelerometry captured MVPA and SRT at baseline and 36 months. Baseline-to-follow-up neighborhood variables within moved and non-moved groups were compared. Multivariable regression assessed associations between follow-up MVPA/SRT and neighborhood variables.45.3% of participants (n = 193) moved. Distance to the closest recreation site decreased significantly for non-movers (0.75 to 0.72 mi, p < 0.001). Nearby crimes significantly decreased for both groups (movers: 90 to 80, p < 0.001; non-movers: 77 to 74, p < 0.001) as did stray dogs (movers: 36 to 15, p < 0.001; non-movers: 36 to 18, p < 0.001). Neighborhood income inequality decreased significantly for movers (0.41 to 0.38, p = 0.03). Child MVPA minutes/day significantly decreased over time from median = 84.7 [Q1 = 64.1, Q3 = 103.9] to median = 73.6 [Q1 = 56.1, Q3 = 96.0], p < 0.001). No significant associations were detected between neighborhood variables and child physical activity.In a rapidly growing county, neighborhood context generally improved over time regardless of move status. Within this context, no associations between neighborhood characteristics and MVPA/SRT were detected in children.

Public funding of social protection: Impact on social indicators in Eurozone countries

Social protection has long been a relevant subject of scientific debate. Its development is interrelated with the study of fiscal factors (collection of social contributions), establishment of major social protection vectors, and confirmation of hypotheses about the link between social protection policy and the resulting socio-economic indicators.The purpose of the paper is to study the impact of public funding of social protectionon social indicatorsusing the example of Eurozone countries. To this end, a number of economic and mathematical methods of analysis were applied to process panel data of seventeen countries for the last fifteen years, including the calculation of the relative rate of variation, regression dependence statistics, and cluster analysis.The study established the irrelevance between the scope of the fundingof spending on social protection and social contributions (coefficient of determination R2=0.255). As illustrated, social indicators are determined not only by the amount of funding of social spending, but also by the structure of the social protection system, in particular, the focus on assistance to families with children and disability compensation (coefficient of determination R2&amp;amp;gt;0.3). The general level of public funding for social spending items results in the 69% income inequality index andis behind 58% of non-economic parameters affecting life quality. The information outlined in the papercan serve as a basis for the formation of social and budgetary policy, as well as the revision of the structure and scope of social protection funding toensure an efficient impact on the quality of life of the population.

The Impact of Income Inequality on the Level of Community Health and Economic Development in Iran

Purpose Given that health is one of the categories that is directly and indirectly affected by income inequality in the country. In this study, the effect of income inequality and economic development on the level of life expectancy as a health indicator is examined. Methodology: This article is an analytical and ecological correlation type using the time series data of 2002-2019 to study the variables of Gini coefficient, per capita income, GDP and life expectancy in Iran. For this purpose, the regression test approach has been used. SPSS software was used to analyze the data. Findings: According to the results, the significant value of regression is less than 0.05, so regression is significant. The standard beta value for the Gini coefficient is negative 0.367 and the significant value is 0.005, so the Gini coefficient at the 95% confidence level has a negative and significant effect on life expectancy. The standard beta coefficient for national per capita income is 0.783 and a significant value is 0.001. Therefore, national per capita income at the 95% confidence level has a positive and significant effect on life expectancy. In the variable Gini coefficient and national per capita income, more than 81% explain the changes in life expectancy. Originality/Value: The results show that health is more affected by income inequality than any other variable. There is also a significant relationship between income inequality and health indicators and reducing inequality and increasing economic development has a positive relationship with health. In this regard, one of the key ways Achieving this is improving the components of human capital, including health. Therefore, adopting appropriate policies to improve income distribution can be effective in promoting the health of people in society and consequently in developing societies such as Iran, simultaneous attention to economic development and income distribution is the best strategy to ensure and promote health.

Does Income Equality of Export IPO Firms Hurt Their Market Returns in Korea?: Using Fama-French 5 Factor Model

Purpose - This study investigates the effects of income inequality across provinces of export firms on their initial and long-term stock returns in the Korean initial public offering (IPO) market. Design/Methodology/Approach - Using 520 IPO firms listed on the Korea Exchange (KRX) from 2002 to 2016 and financial and accounting, regional population data and IPO information, we study the effects of income inequality, measured in relative Gini coefficients over provinces of Korea, of export firms on initial returns (IR) and their long-term cumulative abnormal returns (CARs). Findings - The Gini income inequality index is found to have a positively significant effect on the IR of IPO for the whole and the export firm sample, but without statistical significance for the non-export firm sample. Second, the level of exports has a negative and significant effect on the initial returns of IPO for the pooled sample. Third, the income inequality not only affects IR, but also affects the long-term CARs. Fourth, the export ratio does not show any statistically significant effect on the long-term CARs for all the samples in the CAPM model. Fifth, the income inequality index also has a significant positive effect on all the three measures of CARs in the Fama-French 3, 4 and 5 factor models. Research Implications - We propose to allocate IPO shares based on income level, hopefully more shares to be assigned to lower income investors.

The association between tobacco control policy implementation and country-level socioeconomic factors in 31 European countries

European countries have made significant progress in implementing tobacco control policies to reduce tobacco use; however, whether socioeconomic status (SES) of a country may influence the implementation of such policies is unknown. The aim of this study is to assess the association between country-level SES and the implementation level of tobacco control policies in 31 European countries. An ecological study using data from Eurostat, Human Development Reports on several SES indicators and the Tobacco Control Scale (TCS) of 2016 was conducted to measure country-level tobacco control policies. We analysed the relationship between SES indicators and the TCS by means of scatter-plots and Spearman’s rank correlation coefficients (rsp) and multivariable linear regression analysis. In Europe, no statistically significant association was found between SES factors and the level of implementation of tobacco control policies. Only public spending on tobacco control was associated with all SES factors, except for Gini Index (an income inequality index). The strongest associations of TCS scores for this policy domain were found with the Human Development Index (rsp = 0.586; p < 0.001) and the Gross Domestic Product per capita (in Euros) (rsp = 0.562; p = 0.001). The adjusted linear regression model showed an association of tobacco control policy implementation with countries’ geographical location (Western Europe, β = − 15.7; p = 0.009, compared to Northern Europe). In conclusion, no association was found between SES factors and the level of implementation of tobacco control policies in 31 European countries; policymakers should be aware that tobacco control policies could be successfully implemented despite socioeconomic constraints, especially when these policies are of low cost and cost-effective (i.e., smoke-free bans and taxation).

Does Technological Progress, Trade, or Financial Globalization Stimulate Income Inequality in India?

Does Technological Progress, Trade, or Financial Globalization Stimulate Income Inequality in India?

Income inequality, human capital and terrorism in Africa: Beyond exploratory analytics

This study uncovers the effect of income inequality on terrorism, delineated with four distinct markers: domestic, transnational, uncertain, and total, respectively, intermediated with the role of human capital, on a panel of 34 African countries, over the period 1980–2012. Thus, rather than presenting correlation analyses implied by exploratory analytics among these key variables of interest, this study further employs a zero-inflated negative binomial regression estimator due to the preponderance of zero values of the terrorism data. The following findings are consistently established. First, income inequality remains a substantive predictor of terrorism across the model specifications, with the exception of transnational terrorism. Second, human capital variables exert a positive first-order effect on both domestic and total terrorism. Third, the marginal impacts of interactions between human capital measures and income inequality indicators are negative at the higher levels of educational attainment. These findings remain robust in the presence of endogeneity concerns, time and country-specific effects, alternative estimators, and regional effects, respectively. On the policy front, eliminating the gaps in income inequality remains an effective policy antidote to quell the ember of angers and frustration that may aggravate into arm taking by the aggrieved.

Who Becomes Unhappy when Income Inequality Increases?

Literature has established that, on a macroeconomic level, income inequality has a negative effect on average life satisfaction. An unresolved question is, however, which income groups are harmed by income inequality. In this paper we investigate this relationship at the microeconomic level combining national indicators of income inequality with individual data of life satisfaction from the World Values Survey for 39 countries over a period of 25 years. Tests on moderation by income category show that the Gini coefficient is most negatively related to life satisfaction of the lowest income groups, but the negative effects also extends to other income groups. For the income share of the top 1% we find a similar result. These findings show that income inequality is especially a concern for the lower income groups, but that the harmful effect of income inequality also spillovers to the life satisfaction of other income groups.

Transfers, Income Increments and Leaky Bucket Comparisons for the Gini Index of Income Inequality

Transfers, Income Increments and Leaky Bucket Comparisons for the Gini Index of Income Inequality

Responses to the Covid-19: A Political Economic Analysis

The Covid-19 pandemic posed serious threats to the national and international communities. Worldwide responses to combat its effects seemed weak and controversial. It led individual countries to exercise responses that varied depending upon their tradition, institutions, and leadership. What worked? And what did not? And why is still not comprehended. In this background, this study examines correlation between market economy frameworks such as liberal market economies (LMEs), coordinated market economies (CMEs), state-led market economies (SMEs)and Covid-19 caused deaths. More so, the death cases have been analyzed and interpreted based on published data from worldometer.com as well as national and institutional sources of 23 countries representing three distinct market economy frameworks. The data is juxtaposed with the acts of right-wing populism that determined decision making and institutional mobilization against Covid-19. The approach is dichotomized with a country's human development index and income inequality index (Gini Index). This study found that a country’s market economy framework has had a correlation with the Covid-19 caused deaths The impact, however, was associated with the acts of right-wing populism within different market economies. The 5 selected countries with LMEs have highest; another 5 selected countries with CMEs have higher and 13 selected countries with SMEs have lowest number of deaths. The findings also proves that rate of human development does not appear to be a valid framework for explaining differing death rates between the countries.

Эластичность производительности труда по факторам производства в регионах России

On the basis of models of production functions with an explanation level of 80-90%, built using cross-sectional data for the regions of the country, partial values of the coefficients of elasticity of labor productivity by production factors were obtained. Partial (regional) values of the coefficients of elasticity of labor productivity are calculated using the particular regression equations of models of production functions. The factors included the capital-labor ratio, wages, the price index of industrial goods, the coefficient of funds (an indicator of income inequality), the share of exports in the gross regional product. The regions are identified in which these factors have the maximum and minimum impact on labor productivity.

India’s Inequality Trap: The Role Played by Taxation Policies and Automation

Abstract Recent increases in automation and unemployment have aggravated income inequality in India. Thus, it is imperative for policy-makers to cut down on inequality and unemployment while promoting planned automation. This paper proposes a joint solution to reform India’s taxation framework to fight income inequality while promoting planned automation. The paper finds that the current tax policies are severely increasing income inequality in India, and this, in turn, has lead to alarming consumption and economic slowdown in key industries. Unable to encourage the demand side, industries have responded by cutting down labour costs. This has created an inequality trap. To bring India out of this trap, it is imperative that India moves ahead with taxing concentrated capital and invests in re-skilling. Further, India also must give effect to Baumol’s cost disease insight and create new job opportunities for the rural youth, which is at the highest risk of unemployment.

Public family spending, labour productivity, income inequality and poverty gap in the group of seven countries

Purpose. Comparable data on distribution of family income provide reference point for determining economic performance of any country, opportunity to assess effects of income inequality and poverty drivers that are either country- or region-specific. This study analysed the effectiveness of composite indices of public spending on family benefits, labour productivity, macroeconomic performance indicators and moderating factors in reducing income inequality and poverty gap in the Group of Seven (G7) countries from 1980 to 2019. Methodology. The study employed fixed effects Least Squares regression model in panel environment within the framework of empirical econometric methodologies. The composite indices comprised public spending on family benefits in cash and kind, unemployment allowance payments, tax on personal income, labour productivity, harmonised unemployment rate, consumer price index, real GDP growth rate, GDP per capita and per hour worked, fertility rate and trade. After graphical analysis of the data, order of integration was via unit root tests. Hausman test was carried out to choose between fixed and random effects models. Subsequently, parameters of the models were estimated and evaluated for significance at the 0.05 critical level. Findings. The results showed that percentage changes in income inequality and poverty gap indices differed for same percentage change in components of the composite indices. Some variable-specific percentage changes in income inequality and poverty gap were statistically significant, while others were not. However, the overall percentage changes was statistically significant. The paper concluded that while some specific effectiveness of the explanatory variables in reducing income inequality and poverty gap was not significant, their joint effectiveness significantly reduced poverty. Therefore, it is pertinent that family-oriented fiscal policy thrusts should be strengthened and sustained so as to continually reduce income inequality and, ultimately, narrow poverty gap in the countries. Limitations. The study considered the G7 countries for a period of 40 years. The limitations were that the variables considered to influence income inequality and poverty gap in the countries were both exhaustive. Also, the results were conditioned to the method used, and different methods can alternatively be used by other researchers and the results compared with this. Originality. The study is original research paper. It has neither been published in any other peer-reviewed journal not under consideration for publication by any other journal.

Beyond Piketty: A new perspective on poverty and inequality in India

The socio-economic literature has focused much on how overall inequality in income distribution (frequently measured by the Gini coefficient) undermines the “trickle down” effect. In other words, the higher the inequality in the income distribution, the lower is the growth elasticity of poverty. However, with the publication of Piketty’s magnum opus (2014), and a subsequent study by Chancel and Piketty (2017) of evolution of income inequality in India since 1922, the focus has shifted to the income disparity between the richest 1% (or 0.01%) and the bottom 50%. Their central argument is that the rapid growth of income at the top end of millionaires and billionaires is a by-product of growth. The present study extends this argument by linking it to poverty indices in India. Based on the India Human Development Survey 2005–12 – a nationwide panel survey-we examine the links between poverty and income inequality, especially in the upper tail relative to the bottom 50%, state affluence (measured in per capita income) and their interaction or their joint effect. Another feature of our research is that we analyse their effects on the FGT class of poverty indices. The results are similar in as much as direction of association is concerned but the elasticities vary with the poverty index. The growth elasticities are negative and significant for all poverty indices. In all three cases, the disparity between the income share of the top 1% and share of the bottom 50% is associated with greater poverty. These elasticities are much higher than the (absolute) income elasticities except in the case of the poverty gap. The largest increase occurs in the poverty gap squared – a 1% greater income disparity is associated with a 1.24% higher value of this index. Thus the consequences of even a small increase in the income disparity are alarming for the poorest.

THE IMPACT OF ECONOMIC, DEMOGRAPHIC, AND INFRASTRUCTURAL FACTORS ON INCOME INEQUALITY AND POVERTY IN RUSSIA

The prime objective of the research is to examine the factors influencing both the alteration in the income distribution and the relative change in the incidence of poverty in the regions of Russia. The list of the identified factors/determinants includes economic, demographic, and infrastructural factors. An econometric model, indicating the relationship between the explanatory variables with both the income inequality index and the relative poverty proportions in Russian regions has been provided in this article. The determinants that cause variations in the income inequality and poverty of a country such as social mobility, average life expectancy of urban women, life expectancy of rural men, the number of university graduates, etc. have also been specified in this study. The analysis was executed based on a dataset of 72 Russian regions for the period between 2012-2017.

The Impact of Financial Inclusion on Economic Growth, Poverty, Income Inequality, and Financial Stability in Asia

As an effort to achieve sustainable development and increase people's welfare, financial inclusion has become the policy agenda of many countries. Therefore, the effect of financial inclusion on economic growth, poverty, income inequality, and financial stability in several countries in Asia has become the goal and this is the subject of this study. Financial inclusion is measured by 3 dimensions, namely banking penetration, access to banking services, and use of banking services. Poverty ratio below the national poverty line and the Gini coefficient are used as indicators of poverty and income inequality. Financial stability is measured by Bank Z-Score and bank nonperforming loans. The results from the hypothesis test shows that all dimensions of financial stability simultaneously have significant influence on economic growth, poverty, income inequality, and financial stability. On the other hand, the partial impact of financial inclusion dimension on economic growth, poverty alleviation, income inequality, and financial stability in ten countries of Asia has not been optimal. The derived results of this study is required to be interpreted and considered by the Governments of each country in developing strategies for increasing financial inclusion, so that the policy to achieve sustainable development and enhancement of people's welfare can be achieved.