Income inequality in today's China.
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ABSTRACT:
SUBMITTER: Xie Y
PROVIDER: S-EPMC4024912 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:This study aims to reveal short-run and long-run asymmetries among human capital, educational inequality, and income inequality in China over the period 1975-2020 using a nonlinear autoregressive distributed lag (NARDL) model. The estimated long-run asymmetry parameters reflect that positive shocks to secondary education (SSE) and higher education (HE) are negatively correlated with income Gini coefficient. The adverse shocks of secondary education (SSE) and higher education (HE) stimulate the Gini coefficient of income, but the effect of secondary education (SSE) on the Gini coefficient of income is not significant, while that of higher education (HE) is significant. The results also highlight that, in the long run, there is a significant asymptotic effect of the education Gini coefficient (educational inequality) and economic growth on the income Gini coefficient (income inequality). However, physical capital stock has a significant adverse effect on income inequality in the long run. Higher education significantly promotes educational inequality, while the square of higher education significantly reduces educational inequality, thus verifying the inverted U-shaped Kuznets curve hypothesis between higher education and educational inequality. Strategically, this study suggests higher education as a powerful tool for mitigating income inequality by emphasizing educational equity.
| S-EPMC10403140 | biostudies-literature
Project description:Background In China, income levels and living standards have improved significantly, but many Chinese citizens still do not feel any happier. This phenomenon may be attributed to increased income inequality. Methods Using data from the 2013 Chinese General Social Survey (CGSS), we employed multilevel structural equation modeling (MSEM) to investigate the impact of county-level income inequality on individual-level happiness in China and multilevel mediation analysis with structural equation modeling (MMSEM) to explore the mechanisms through which income inequality impacted happiness. Results A negative relationship between income inequality and happiness was found. The negative association between them was explained by two psychological mechanisms, i.e., fairness and trust. The findings explained a "Chinese puzzle," i.e., why people do not feel happier despite improved income and living standards. Conclusions Our findings may provide a reference for policy makers to implement policies designed to improve individual happiness. What is important now is to reduce income inequality, and to potentially improve perceptions of fairness and trust in China.
| S-EPMC6313330 | biostudies-literature
Project description:BackgroundHealth inequality has been recognized as a problem all over the world. In China, the poor usually have less access to healthcare than the better-off, despite having higher levels of need. Since the proportion of the Chinese population living in urban areas increased tremendously with the urbanization movements, attention has been paid to the association between urban/rural residence and population health. It is important to understand the variation in health across income groups, and in particular to take into account the effects of urban/rural residence on the degree of income-related health inequalities.MethodsThis paper empirically assesses the magnitude of rural/urban disparities in income-related adult health status, i.e., self-assessed health (SAH) and physical activity limitation, using Concentration Indices. It then uses decomposition methods to unravel the causes of inequalities and their variations across urban and rural populations. Data from the China Health and Nutrition Survey (CHNS) 2006 are used.ResultsThe study finds that the poor are less likely to report their health status as "excellent or good" and are more likely to have physical activity limitation. Such inequality is more pronounced for the urban population than for the rural population. Results from the decomposition analysis suggest that, for the urban population, 76.47 per cent to 79.07 per cent of inequalities are driven by non-demographic/socioeconomic-related factors, among which income, job status and educational level are the most important factors. For the rural population, 48.19 per cent to 77.78 per cent of inequalities are driven by non-demographic factors. Income and educational attainment appear to have a prominent influence on inequality.ConclusionThe findings suggest that policy targeting the poor, especially the urban poor, is needed in order to reduce health inequality.
| S-EPMC3563496 | biostudies-literature
Project description:To examine the interaction between social income inequality, social integration, and health status among internal migrants (IMs) who migrate between regions in China.We used the data from the 2014 Internal Migrant Dynamic Monitoring Survey in China, which sampled 15,999 IMs in eight cities in China. The Gini coefficient at the city level was calculated to measure social income inequality and was categorized into low (0.2 < Gini <= 0.3), medium (0.3 < Gini <= 0.4), high (0.4 < x < = 0.5), and very high (Gini >0.5). Health status was measured based upon self-reported health, subjective well-being, and perceptions of stress and mental health. Social integration was measured from four perspectives (acculturation and integration willingness, social insurance, economy, social communication). Linear mixed models were used to examine the interaction effects between health statuses, social integration, and the Gini coefficient.Factors of social integration, such as economic integration and acculturation and integration willingness, were significantly related to health. Social income inequality had a negative relationship with the health status of IMs. For example, IMs in one city, Qingdao, with a medium income inequality level (Gini = 0.329), had the best health statuses and better social integration. On the other hand, IMs in another city, Shenzhen, who had a large income inequality (Gini = 0.447) were worst in health statues and had worse social integration.Policies or programs targeting IMs should support integration willingness, promote a sense of belonging, and improve economic equality. In the meantime, social activities to facilitate employment and create social trust should also be promoted. At the societal level, structural and policy changes are necessary to promote income equity to promote IMs' general health status.
| S-EPMC5545016 | biostudies-other
Project description:BackgroundIncome inequality is associated with numerous negative health outcomes. There is evidence that ecological-level socio-environmental factors may increase risk for schizophrenia.AimsThe aim was to investigate whether measures of income inequality are associated with incidence of schizophrenia at the country level.MethodWe conducted a systematic review of incidence rates for schizophrenia, reported between 1975 and 2011. For each country, national measures of income inequality (Gini coefficient) along with covariate risk factors for schizophrenia were obtained. Multi-level mixed-effects Poisson regression was performed to investigate the relationship between Gini coefficients and incidence rates of schizophrenia controlling for covariates.ResultsOne hundred and seven incidence rates (from 26 countries) were included. Mean incidence of schizophrenia was 18.50 per 100,000 (SD = 11.9; range = 1.7-67). There was a significant positive relationship between incidence rate of schizophrenia and Gini coefficient (β = 1.02; Z = 2.28; p = .02; 95% CI = 1.00, 1.03).ConclusionsCountries characterized by a large rich-poor gap may be at increased risk of schizophrenia. We suggest that income inequality impacts negatively on social cohesion, eroding social capital, and that chronic stress associated with living in highly disparate societies places individuals at risk of schizophrenia.
| S-EPMC4105302 | biostudies-literature
Project description:The novel coronavirus is part of a series of infectious disease outbreaks that include: Ebola, Avian influenza, Middle East respiratory syndrome coronavirus, and Influenza A. This paper addresses the question of how do these epidemics and pandemics affect income inequality in countries around the world during the first two decades of this century. To achieve its objective, the paper develops a model that indicates a positive association between these health crises and income inequality. To empirically test our theoretical predictions, the paper explores the effect on the Gini coefficient of a dummy variable that indicates the occurrence of an epidemic or a pandemic in a country in a given year and the number of deaths per 100,000. To properly address potential endogeneity, we implement a Three-Stage-Least Squares technique. The estimation shows that the number of deaths per 100,000 population variable has a statistically significant positive effect on the Gini coefficient, especially when we incorporate COVID-19 data. This suggests that not only the occurrence, but also the health consequences of COVID-19 have a significant and economically important effect on income inequality.BackgroundThe purpose of the study is to examine the effect of epidemics and pandemics on income inequality. This has important implications as the outcome of this study can guide policymakers into implementing policies that can mitigate the economic consequences of these health crises.MethodsThe study is a cross country analysis using fixed effects estimation. To address potential endogeneity and determine causality, the paper uses the Three-Stage-Least-Squares estimation.ResultsThe paper finds that the number of epidemic deaths per 100,000 population variable has a statistically significant positive effect on the Gini coefficient, especially when we incorporate COVID-19 data.ConclusionsThe paper finds that it is not only the occurrence of an epidemic, captured by the epidemics dummy variable, but also the health consequences, captured by the number of deaths per 100,000 population, that have a significant effect on income inequality. This is especially the case when we incorporate COVID-19 in our analysis.Trial registrationNot Applicable.
| S-EPMC8765494 | biostudies-literature
Project description:As payment for ecosystem services (PES) programs proliferate globally, assessing their impact upon households' income and livelihood patterns is critical. The Sloping Land Conversion Program (SLCP) is an exceptional PES program, in terms of its ambitious biophysical and socioeconomic objectives, large geographic scale, numbers of people directly affected, and duration of operation. The SLCP has now operated in the poor mountainous areas in China for 10 y and offers a unique opportunity for policy evaluation. Using survey data on rural households' livelihoods in the southern mountain area in Zhouzhi County, Shaanxi Province, we carry out a statistical analysis of the effects of PES and other factors on rural household income. We analyze the extent of income inequality and compare the socio-demographic features and household income of households participating in the SLCP with those that did not. Our statistical analysis shows that participation in SLCP has significant positive impacts upon household income, especially for low- and medium-income households; however, participation also has some negative impacts on the low- and medium-income households. Overall, income inequality is less among households participating in the SLCP than among those that do not after 7 y of the PES program. Different income sources have different effects on Gini statistics; in particular, wage income has opposite effects on income inequality for the participating and nonparticipating households. We find, however, that the SLCP has not increased the transfer of labor toward nonfarming activities in the survey site, as the government expected.
| S-EPMC3093530 | biostudies-literature
Project description:Is there a relationship between family income inequality and income mobility across generations in the United States? As family income inequality rose in the United States, parental resources available for improving children's health, education, and care diverged. The amount and rate of divergence also varied across US states. Researchers and policy analysts have expressed concern that relatively high inequality might be accompanied by relatively low mobility, tightening the connection between individuals' incomes during childhood and adulthood. Using data from the Panel Study of Income Dynamics, the National Longitudinal Survey of Youth, and various government sources, this paper exploits state and cohort variation to estimate the relationship between inequality and mobility. Results provide very little support for the hypothesis that inequality shapes mobility in the United States. The inequality children experienced during youth had no robust association with their economic mobility as adults. Formal analysis reveals that offsetting effects could underlie this result. In theory, mobility-enhancing forces may counterbalance mobility-reducing effects. In practice, the results suggest that in the US context, the intergenerational transmission of income may not be very responsive to changes in inequality.
| S-EPMC4569595 | biostudies-literature
Project description:This paper investigates the potential causal relationship(s) between China's urbanization and income inequality since the start of the economic reform. Based on the economic theory of urbanization and income distribution, we analyze the annual time series of China's urbanization rate and Gini index from 1978 to 2014. The results show that urbanization has an immediate alleviating effect on income inequality, as indicated by the negative relationship between the two time series at the same year (lag = 0). However, urbanization also seems to have a lagged aggravating effect on income inequality, as indicated by positive relationship between urbanization and the Gini index series at lag 1. Although the link between urbanization and income inequality is not surprising, the lagged aggravating effect of urbanization on the Gini index challenges the popular belief that urbanization in post-reform China generally helps reduce income inequality. At deeper levels, our results suggest an urgent need to focus on the social dimension of urbanization as China transitions to the next stage of modernization. Comprehensive social reforms must be prioritized to avoid a long-term economic dichotomy and permanent social segregation.
| S-EPMC4951071 | biostudies-literature
Project description:Mass shootings are becoming a more common occurrence in the United States. Data show that mass shootings increased steadily over the past nearly 50 years. Crucial is that the wide-ranging adverse effects of mass shootings generate negative mental health outcomes on millions of Americans, including fear, anxiety, and ailments related to such afflictions. This study extends previous research that finds a strong positive relationship between income inequality and mass shootings by examining the effect of household income as well as the interaction between inequality and income. To conduct our analyses, we compile a panel dataset with information across 3,144 counties during the years 1990 to 2015. Mass shootings was measured using a broad definition of three or more victim injuries. Income inequality was calculated using the post-tax version of the Gini coefficient. Our results suggest that while inequality and income alone are both predictors of mass shootings, their impacts on mass shootings are stronger when combined via interaction. Specifically, the results indicate areas with the highest number of mass shootings are those that combine both high levels of inequality and high levels of income. Additionally, robustness checks incorporating various measures of mass shootings and alternative regression techniques had analogous results. Our findings suggest that to address the mass shootings epidemic at its core, it is essential to understand how to stem rising income inequality and the unstable environments that we argue are created by such inequality.
| S-EPMC6199901 | biostudies-literature