Effects of income inequality on China’s economic growth

Qin, Duo; Cagas, Marie Anne; Ducanes, Geoffrey; He, Xinming; Li, Rui; Liu, Shiguo

doi:10.1016/j.jpolmod.2008.08.003

Cited by 39 publications

(25 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Fosu (2009) finds that initial inequality negatively affects the impact of GDP growth on poverty reduction for countries in sub-Saharan Africa [3]. Qin et al (2009) shows the negative consequences of inequality in China on GDP and sectoral growth [4]. Castelló-Climent (2010) also finds a negative effect of inequality (both income and human capital) on economic growth but only for low and middle-income economies [5].…”

Section: Introductionmentioning

confidence: 99%

Inequality and Growth Re-Examined

Assa¹

2012

View full text Add to dashboard Cite

This paper examines the relationship between income inequality and subsequent economic growth. It builds on the model suggested by Alesina and Rodrik (1994) in which inequality works through greater demands for redistribution to slow down growth, and the idea by Ray (1998) that inequality negatively affects savings, work capacity, economic incentives, and access to and efficiency of credit and financial markets. Using an updated dataset and seven model variants, both OLS and 2SLS regressions find a strong negative effect of income inequality on future growth. The effect is considerably stronger for developing countries, but the existence or absence of democracy has no effect on either the relationship between inequality and growth or on the rate of growth itself. There is also no support for Barro's (2008) claim that inequality impacts growth positively in developed countries.

show abstract

Section: Introductionmentioning

confidence: 99%

Inequality and Growth Re-Examined

Assa¹

2012

View full text Add to dashboard Cite

show abstract

“…It is necessary to evaluate regional disparities of regional socioeconomic status within China because of the important effects of inequality on national development and social stability [4]. The majority of studies on socioeconomic inequality in China have focused on several prominent economic indicators such as GDP, average income, and consumption expenditure in their analyses [5][6][7]. These studies applied several measurements to assess inequality such as the Coefficient of Variation (CV) and the Gini index.…”

Section: Introductionmentioning

confidence: 99%

Nighttime Light Derived Assessment of Regional Inequality of Socioeconomic Development in China

Zhou

et al. 2015

Remote Sensing

View full text Add to dashboard Cite

Satellite-derived nighttime light (NTL) data have been extensively used as an efficient proxy measure for monitoring urbanization dynamics and socioeconomic activity. This is because remotely sensed NTL signals can be quantitatively connected to demographic and socioeconomic variables at regional and global scales. The recently composited cloud-free NTL imagery derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite provides spatially detailed observations of human settlements. We quantitatively estimated socioeconomic development inequalities across 30 provinces and municipalities in mainland China using VIIRS NTL data associated with both regional gross domestic product (GDP) and population census data. We quantitatively investigated relations between NTL, GDP, and population using a linear regression model. Our results suggest that NTL radiances have significant positive correlations with GDP and population at different levels. Several inequality coefficients, commonly used in economics, were derived from VIIRS NTL data and statistical data at multiple spatial scales. Compared with the statistical data, NTL-derived inequality coefficients enabled us to elicit more detailed information on differences in regional development at multiple levels. Our study of provinces and municipalities revealed that county-level inequality was more significant OPEN ACCESSRemote Sens. 2015, 7 1243 than city-level inequality. The results of population-weighted NTL inequality indicate an obvious regional disparity with NTL distribution being more unequal in China's undeveloped western regions compared with more developed eastern regions. Our findings suggest that given the timely and spatially explicit advantages of VIIRS, NTL data are capable of providing comprehensive information regarding inequality at multiple levels, which is not possible through the use of traditional statistical sources.

show abstract

“…Income inequality interacts with economic development in positive or negative ways [10]. Moderate income inequality helps to break egalitarianism, arouse enthusiasm and promote economic Gini coefficient, Theil coefficient and Lorenz curve [42], and revealed the reasons causing poverty or income inequality through regression analysis or correlation analysis [43].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Income Inequality Based on Income Mobility for Poverty Alleviation in Rural China

Long

et al. 2015

Sustainability

View full text Add to dashboard Cite

Abstract:Since the reform and opening up, the Chinese economy has achieved sustained high-speed growth. However, the widening gaps in income, especially for rural China, seem to be a dark lining to these extraordinary achievements. Taking the duration of poverty into the consideration, this article analyzes the income inequality of rural per capita net income (RPCNI) based on income mobility in rural China. Analysis results showed that Gini coefficient of RPCNI declined, but that income mobility was mainly limited in the interior for low-and high-income groups. Income inequalities rose sharply within eastern and western China from 1990 to 2010. Benefiting from the developed economy, the upward mobility was universal in eastern China. The spillover effect on neighboring poor counties was feeble in western China, which directly caused long-term rich and poor. The Gini coefficient of RPCNI in central China was always at a low level, corresponding to the phenomenon of short-term rich and long-term poor. In northeastern China, the Gini coefficient sharply decreased and the large body of income mobility between non-neighboring groups was quite remarkable. The spatial pattern of intra-provincial Gini coefficient and income mobility of RPCNI has been divided by the "HU line", which is a "geo-demographic demarcation line" discovered by Chinese population geographer HU Huanyong in 1935. In southeastern China, the characteristics of income mobility of each county depended on the distance between the county and the capital city. The spatial pattern of income mobility of RPCNI in agricultural provinces was different from that in non-agricultural provinces. According to the income inequality and income mobility, appropriate welfare and development policies was proposed to combat rural poverty at both regional and provincial scales.

show abstract

Effects of income inequality on China’s economic growth

Cited by 39 publications

References 18 publications

Inequality and Growth Re-Examined

Inequality and Growth Re-Examined

Nighttime Light Derived Assessment of Regional Inequality of Socioeconomic Development in China

Analysis of Income Inequality Based on Income Mobility for Poverty Alleviation in Rural China

Contact Info

Product

Resources

About