Impact Of Income Inequality Research Articles

Is information and communication technology a productivity drain or gain? Evidence from the health services sector in China

This contribution investigates the impact of information and communication technology (ICT) on health service performance and considers the issue of income inequality. It provides empirical evidence that the development of ICT helps to mitigate the negative impact of income inequality on health and thereby providing support for the vigorous development of ICT. Specifically, by using the Driscoll-Kraay standard error estimation, Generalized Method of Moments, and a panel threshold model, a nonlinear relationship is detected, and the results show that: (1) ICT can significantly promote the performance of the health service sector. As income inequality increases, the effects of ICT on health care performance become larger. (2) With the increase from a lower to a higher income inequality level, the positive impact of ICT development on health service enables productivity to increase significantly. Finally, policy recommendations for promoting health service productivity, based on our theoretical contribution and empirical results, are provided.

Impact of income inequality on carbon emissions: a matter of corruption governance.

Corruption is often linked with income inequality and its impact on carbon emissions. This study investigates the moderating effect of corruption governance on the relationship between income inequality and carbon emissions. Panel data for 62 countries from 2012 to 2020 were used. We employed a threshold panel regression approach, considering income inequality as the explanatory variable and carbon dioxide emissions as the dependent variable, with corruption governance as the threshold variable. Our findings suggest that enhancing the level of corruption governance can mitigate the CO2 emissions driven by income inequality. Specifically, we found a shift in the impact on CO2 emissions when corruption governance crosses a certain threshold. This study provides insights into how improving corruption governance can help in managing the environmental effects of income inequality.

Impact of income inequality on health and education in Africa: the long-run role of public spending with short-run dynamics

Impact of income inequality on health and education in Africa: the long-run role of public spending with short-run dynamics

Income inequality and socioeconomic differences in bullying perpetration among adolescents in post-communist countries of Europe: Findings from the HBSC study

BackgroundAdolescent bullying is a major public health concern in post-Communist countries of Europe (PCCE). We studied the impact of income inequality on the prevalence of and socioeconomic differences in bullying perpetration. MethodsNationally representative samples of adolescents aged 11–15 years from 14 PCCE participating in the Health Behavior in School-aged Children survey during 2017–18 years were included. Multilevel logistic regression models were fitted. ResultsOverall, 71,119 adolescents participated in the survey. About 27.7 % of country differences in bullying perpetration were attributable to high income inequality. Adolescents with low and high family socioeconomic status (SES) had a 10–15 % greater risk (P < 0.05) of bullying perpetration compared to middle-SES adolescents. In cross-level interaction, the risk of bullying perpetration was the highest among high-SES adolescents from countries with wider income inequality (P-interaction = 0.003). The odds ratios of bullying perpetration comparing high- vs. low-SES adolescents ranged from 0.67 in the least unequal to 1.59 in the most unequal countries. ConclusionsOur findings suggest that high income inequality might contribute to school bullying among adolescents in PCCE, particularly those from high-SES families. The necessary political and economic interventions should focus on improving the country socioeconomic environment in PCCE. Moving towards less neoliberal policies and creating a strong welfare state that promotes the population's economic and social well-being and reduces income inequality might be a necessary component of macro-level strategies aimed at preventing bullying among adolescents. Targeted public health interventions might be required for high-SES adolescents in countries with wide income inequality.

Impact Analysis of Education Program, Unemployment Rate, and Income Gap on Social Mobility in Jakarta

This research investigates the impact of education programs, unemployment rates, and income gaps on social mobility in Jakarta through a quantitative analysis employing Structural Equation Modeling with Partial Least Squares (SEM-PLS) and regression analysis. The study utilizes a sample of 150 respondents, providing a diverse representation of Jakarta's population across age groups, educational backgrounds, employment statuses, socio-economic strata, and geographical locations. The measurement model demonstrates strong reliability and validity, affirming the robustness of the chosen constructs. The structural model reveals a significant positive relationship between education programs and social mobility, indicating that improved access and quality of education positively influence upward mobility. Additionally, income gaps exhibit a negative association with social mobility, emphasizing the adverse impact of income inequality. Surprisingly, unemployment rates do not emerge as a significant predictor of social mobility within the model. The regression analysis further explores these relationships, providing nuanced insights. The study concludes with policy implications, highlighting the need for targeted interventions in education and income equality to foster social mobility in Jakarta. The findings also call for a deeper understanding of the complex dynamics influencing employment and social mobility in the region.

Income inequality and depressive symptoms among Chinese adults: a quasi-experimental study

ObjectiveThere is a lack of causal evidence on the impact of income inequality on depressive symptoms. The impact of China's Targeted Poverty Alleviation (TPA) policy on depressive symptoms is also unclear. Using a quasi-experimental design, this study aims to investigate the causal effects of TPA and income inequality on depressive symptoms among Chinese adults. Study designThis is a population-based study. MethodsThree waves (2012, 2016, and 2018) of the China Family Panel Studies (CFPS), a nationally representative sample of China, were included in this study. We performed difference-in-difference (DID) models to assess the effect of TPA and income inequality on depressive symptoms. We further conducted the mixed effect models to examine the impact of income inequality on depressive symptoms. The study considered a range of spatial factors and spatial splines to address spatial autocorrelations. ResultsThis study included valid measures of depressive symptoms (Center for Epidemiologic Studies Depression Scale [CES-D-8] score) from 14,442 adults of CFPS. The DID results indicated that at the provincial level, the CES-D-8 score of the TPA treatment group was on average 0.570 (95% confidence interval [CI]: 0.358–0.783) less than the control group. Furthermore, a 0.1 increase in Gini index would lead to a 0.256 (95% CI: 0.064–0.448) increase in CES-D-8 score. The mixed effect model showed that income inequality was a risk factor for depressive symptoms at the provincial level (excess risk = 5.602% [95% CI: 3.047%–8.219%]). ConclusionsOur findings suggest that income inequality adversely affects mental health, but China's Targeted Poverty Alleviation improves the mental health of the Chinese population.

The impact of income inequality on household indebtedness in euro area countries

This paper explores the impact of income inequality on household indebtedness at the household level. Using the first wave of the Eurosystem Household Finance and Consumption Survey data, the analysis sheds light on heterogeneous effects across euro area countries. The results suggest that there is weak evidence that income inequality has affected households’ indebtedness in continental European countries. The countries that show an impact are characterised by positive effects that operate across the income distribution and tend to be robust for consumption-related and housing-related debts. The effects, however, vary much less across the distribution for consumption-related debts as compared to housing-related debts. Households at the top of the income distribution seem to react more than lower-income households when it comes to housing-related debts.

Does income inequality have a heterogeneous effect on carbon emissions between developed and developing countries? Evidence from simultaneous quantile regression

The sustainable development process faces two major challenges: income inequality and carbon emissions. However, there is no definitive conclusion regarding the relationship between income inequality and carbon emissions. In addition, for developed and developing countries, the impact might vary. From an international perspective, the present study examines the correlation between income inequality and carbon emissions utilizing panel data from 65 countries (32 developed and 33 developing countries) spanning from 1990 to 2019. The simultaneous quantile regression (SQR) results show that the impact of income inequality on carbon emissions varies slightly between countries with various income levels. The positive impact of income inequality on carbon emissions is significant for both developed and developing countries, indicating that an uneven income distribution can worsen environmental quality, but the impact is more significant for developed countries. Therefore, it is integral for the global world to take measures to alleviate the income gap to achieve Sustainable Development Goals (SDGs). In addition to income growth, developed countries also need to focus on income equity to reach green development.

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.

Objective Relative Income Impacts Life Satisfaction and Positive Affect Only When Subjective Absolute Income is High.

Given the crucial role of money in individuals' daily life and the potential societal impact of income inequality, it is not surprising that the income-subjective well-being (SWB) link has been a topic of great research interest. The present study extends past research by examining the independent and interactive effects of three personal income factors. An experiment was conducted where subjective income (both absolute and relative) were manipulated and objective relative income was measured. Subjective relative income impacted perceived deprivation, negative affect, and state hostility, whereas the other two income factors showed a main effect on perceived deprivation only. Regarding interaction effects, objective relative income impacted life satisfaction and positive affect only for individuals in the high (vs. low) subjective absolute income condition, i.e., those who perceived their income as adequate for needs/wants. We proposed that the relative deprivation theory (Smith et al., 2012), which primarily focuses on the impact of low relative income (or income inequality), should be expanded to account for both perceived deprivation "relative to others" and perceived deprivation "relative to one's own needs/wants."

Does income inequality worsen pollution? The GEMS air pollution data revisited

Research on the effect of income inequality on pollution shows mixed results. This paper takes a new look at the urban air pollution data set of the U.N.‘s Global Environmental Monitoring System (GEMS). We investigate the impact of income inequality on urban air pollution and relate the results to a median-voter model. In this model, more income inequality decreases the median income, reduces pollution controls, and increases output and pollution when the median income is above a threshold. We find that income inequality, measured by the Gini coefficient, increases SO2 concentration in the rich democracies. The estimated effects are non-negligible in size. For the poor non-democracies, we find no evidence that the Gini coefficient impacts SO2 concentration. The Gini coefficient is estimated to increase the smoke concentration at the five- or ten-percent significance level in most specifications in a pooled sample. We find no evidence that the Gini coefficient impacts the concentration of particulates in a pooled sample. We conclude that the empirical results largely are consistent with the median-voter model.

Income inequality and systemic banking crises: A nonlinear nexus

Motivated by Rajan’s work, we propose that income inequality and systemic banking crises have a nonlinear nexus. In addition to examining the linear “Rajan effect,” we propose a “Kuznets effect” based on an assumption that income inequality has a nonlinear impact on growth, conditional on the stage of economic development, and thus plays a nonlinear role in modeling crises. We test the existence of this nexus using a sample covering 172 economies for a period of fifty years. We confirm that the relationship is U-shaped and identify the threshold level of income inequality that is beneficial for financial stability. Additionally, the U-test and area under the receiver operating characteristic (AUROC) statistics confirm that nonlinearity, and our model has good predictive performance of forecasting. Furthermore, the results of our panel regressions are consistent and are robust to several tests. We then identify the Rajan and Kuznets effects using a two-step test. We conclude that the impact of income inequality on the occurrence of systemic banking crises is U-shaped.

Impact of income inequality on climate change in Asia: the role of human capital

Applying different regression estimators on balanced panel data, this article examines the impact of human capital and income inequality on climate change in Asian countries during the period 2007–2020. Results by the GMM estimator confirm that increases in income inequality and investments in human capital exacerbate environmental degradation in Asian countries. However, among the three variables that represent human capital, only HC3 (Gross enrollment ratio for tertiary school) plays a role in reducing the impact of income inequality on emissions of carbon dioxide. In addition, the study also provides evidence on the impact of other factors on CO2 emissions such as renewable energy, economic growth, population, output in the agricultural and services sectors, trade openness, government expenditure and total investment in the economy. Besides, some important policy implications have been suggested to aim at securing sustained economic growth in Asia.

Impact of income inequality on carbon-intensive extractivism

Impact of income inequality on carbon-intensive extractivism

INCOME INEQUALITY AND DOMESTIC VIOLENCE: AN EMPIRICAL ANALYSIS FROM MICS SURVEY DATA

The aim of this paper is to estimate domestic violence in Punjab (Pakistan) and to empirically investigate the impact of income inequality on domestic violence in Punjab (Pakistan) by using the Multiple Indicators Cluster Survey (MICS) microdata. Domestic violence is a human right violation and is a worldwide issue. Over the world, about one in three (35%) of women experience domestic violence. The present study uses domestic violence as dependent variables and the Gini coefficient as independent variable and other control variables at the district level in Punjab (Pakistan). Results of this study show that the Gini coefficient has a positive and significant relationship with domestic violence. The outcome of this study shows that the higher the unequal distribution of income, the higher the violence. In this study, northern and eastern districts in Punjab are more developed and have more equal distribution of income, while southern and western districts in Punjab have more unequal distribution of income and other resources. The government of Punjab should prioritize Southern and western districts, like Rajanpur, Bahawalnagar, Bahawalpur, DG Khan, Bhakkar and Khushab, Muzaffargarh and Layyah, for focused intervention for poverty eradication and equal opportunities for everyone. Keywords: Domestic Violence, Income Inequality, Punjab, Multiple Indicators Cluster Survey

A nexus of income inequality and natural resource utilization efficiency: Effect on the road to green economic recovery

While China possesses abundant natural resources, their utilization efficiency remains low. As economic and social development progress rapidly, promoting natural resource utilization efficiency is crucial for the construction of the country's ecological capacity. However, research investigating the effect of income inequality on natural resource utilization efficiency is insufficient. Using the panel data of 30 provinces in China from 2011 to 2019, this paper analyzes the impact of income inequality on natural resource utilization efficiency. The empirical results denote that income inequality has a significantly negative impact on natural resource utilization efficiency and presents a discernible influence on lower green innovation ability and natural resource endowment. In addition, green fiscal policy and industrial agglomeration can alleviate the negative impact of income inequality on natural resource utilization efficiency. Furthermore, the threshold effect reveals that, with technological progress, the negative impact of income inequality on natural resource utilization efficiency has transformed into a positive.

Impact of income inequality on renewable energy demand in south Asian economies

The demand for renewable energy is growing worldwide due to environmental degradation. However, in poor countries, the use of renewable energy may be impeded by the level of poverty and income inequality. Therefore, this paper studies the income inequality impact on renewable energy demand in seven South Asian economies by using the balanced panel data from 1996 to 2018. The study employs generalized methods of moments (GMM) estimation technique followed by other econometric approaches to check the robustness of findings. The renewable energy demand function includes economic growth, carbon emissions, and government effectiveness as control variables. The study has found the adverse effects of income inequality, economic growth, and carbon emissions on renewable energy demand. Government effectiveness also drives renewable energy use. The findings are robust and reliable concerning panel data methods used in the analysis. These findings bear important policies for a sustainable environment in South Asian economies.

Intergenerational Mobility and the Growth–Inequality–Poverty Nexus in Africa

AbstractThis paper examines to what extent intergenerational mobility shapes both the impact of income inequality on growth as well as the effect that growth has on poverty and on income inequality in Africa. Thanks to newly available and internationally comparable data on intergenerational elasticities of income and education, we confirm the detrimental role played by higher inequality of opportunity as measured by intergenerational mobility. The study concludes that neglecting to address the root causes of inequality of opportunity can be socially and economically very costly.

The interaction of income inequality and urbanization in affecting environmental quality: International evidence

ABSTRACT This research examines how income inequality interacts with urbanization in its influence on carbon dioxide emissions. We analyze national level data of 95 countries between 1961 and 2015 using the system generalized method of moments to explore the nature of interactions. The results indicate that the environmental impact of income inequality varies with the rise of urbanization. Environmental performance of developing communities improves initially, but when the urbanization ratio is above 35.2 per cent, inequality suppresses progress in environmental performance until the urbanization ratio is greater than 55.7 per cent. This inverted U shape relationship adds further evidence on the conflicting views on the interactions between the two social justice and environmental quality goals of development. While aggregate data often masks within-country variations, these analyses provide valuable insights for policymakers about the forces influencing these aggregate measures and the importance of local context in tackling environmental issues of development.

Income inequality, shadow economy and environmental degradation in Africa: quantile regression via moment’s approach

PurposeThe purpose of this examine the impact of income inequality and shadow economy on environmental degradation given the growing income inequality, shadow economy and ecological degradation in developing countries. Thus, this study is motivated to offer empirical insight into how income inequality and shadow economy influence the environment in African countries.Design/methodology/approachData from 29 countries in Africa between 2000 and 2017 were used, while the novel method of moments quantile regression of Machado and Silva (2019) and Dumitrescu and Hurlin (D-H) (2012) granger causality is used as the estimation techniques.FindingsThe results established the presence of cross-sectional dependence and slope heterogeneity in the panel, while Westerlund panel cointegration confirmed the long-run cointegration among the variables. The results from the quantile regression suggest that income inequality increases environmental degradation from the 5th to the 30th quantiles, while from the 70th quantiles, income inequality reduces ecological degradation. The shadow economy negatively influences environmental degradation across the quantiles, strengthening environmental quality. Per capita income (economic growth) and financial development positively impact environmental degradation throughout the quantiles. However, urbanization reduces environmental degradation from 60th to 95th quantiles. The D-H causality established a two-way relationship between income inequality and environmental degradation, while one-way from shadow economy, per capita income and urbanization to environmental degradation were established.Originality/valueThis study provides fresh insights into the nexus between shadow economy and environmental quality in the presence of higher levels of income inequality for the case of African region. The study applies quantile analysis via moment proposed by Machado and Silva (2019). This technique shows that the impact of income inequality and shadow economy on environmental degradation is heterogeneous across the quantiles of ecological footprints in Africa.