The Income Gap Between Urban and Rural Residents in China: Since 1978

Ma, Xiao; Wang, Feiran; Chen, Jiandong; Zhang, Yang

doi:10.1007/s10614-017-9759-4

Cited by 53 publications

(37 citation statements)

References 20 publications

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“…Even at the lowest Gini coefficients of around 0.25, as for example in the case of Sweden, the top 10% income earners of the population may hold ∼23% of total income and the bottom 10% only ∼3% (World Bank, 2020d). National income inequality is also correlated with various other inequality dimensions, for instance the rural-urban divide, gender inequality and racial inequality (Ma et al, 2018;Ortiz-Ospina & Roser, 2018).…”

Section: Global Inequalitiesmentioning

confidence: 99%

Global redistribution of income and household energy footprints: a computational thought experiment

et al. 2021

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Non-technical summary Global income inequality and energy consumption inequality are related. High-income households consume more energy than low-income ones, and for different purposes. Here, we explore the global household energy consumption implications of global income redistribution. We show that global income inequality shapes not only inequalities of energy consumption but the quantity and composition of overall energy demand. Our results call for the inclusion of income distribution into energy system models, as well as into energy and climate policy. Technical summary Despite a rapidly growing number of studies on the relationship between inequality and energy, there is little research estimating the effect of income redistribution on energy demand. We contribute to this debate by proposing a simple but granular and data-driven model of the global income distribution and of global household energy consumption. We isolate the effect of income distribution on household energy consumption and move beyond the assumption of aggregate income–energy elasticities. First, we model expenditure as a function of income. Second, we determine budget shares of expenditure for a variety of products and services by employing product-granular income elasticities of demand. Subsequently, we apply consumption-based final energy intensities to product and services to obtain energy footprint accounts. Testing variants of the global income distribution, we find that the ‘energy costs’ of equity are small. Equitable and inequitable distributions of income, however, entail distinct structural change in energy system terms. In an equitable world, fewer people live in energy poverty and more energy is consumed for subsistence and necessities, instead of luxury and transport. Social media summary Equality in global income shifts household energy footprints towards subsistence, while inequality shifts them towards transport and luxury.

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Section: Global Inequalitiesmentioning

confidence: 99%

Global redistribution of income and household energy footprints: a computational thought experiment

et al. 2021

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“…On one hand, because the urbanization process decreased the rural population and increased the urban population, the marginal productivity of rural labor will increase, while that of urban labor will decrease. This scenario will lead to a higher average accumulated income for rural residents and a lower average accumulated income for urban residents, thereby prompting a reduction in the accumulated income gap between these two groups (Ma et al, 2017). On the other hand, under the strong constraints of the household registration system, only the economically strong groups among rural residents can be transformed into urban residents, while the economically weak groups cannot attain this privilege.…”

Section: Panel Data Modelmentioning

confidence: 99%

“…Income gaps have long been the focus of research (Alderman et al, 1997;Ma et al, 2017), particularly in developing countries (Carter, 1997;Molero-Simarro, 2017). Additional study on this topic is urgently needed for the following reasons.…”

Section: Introductionmentioning

confidence: 99%

Urban and Rural Income Gap: Does Urban Spatial Form Matter in China?

Liu

Long

2021

SAGE Open

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This research uses satellite remote sensing data to measure the urban spatial form and analyzes the impact of changes to urban spatial structure on the income gap between urban and rural residents. The results indicate that the compactness of the urban spatial form is positively correlated with the income gap between urban and rural residents. However, there is no statistically significant relationship between the urban spatial extension rate and the urban–rural income gap. A subsequent analysis of the control variables shows that fiscal policy is positively correlated while urbanization is negatively correlated with the income gap between urban and rural residents. These conclusions provide the basis for formulating policies to narrow the urban–rural income gap. Appropriately reducing the spatial compactness of cities can narrow the income gap. In addition, changing excessive preferences for urban fiscal policy and increasing the level of urbanization can also promote a reduction in the income gap between urban and rural residents.

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“…The results indicate that coping appraisal and risk attitudes are important variables in terms of risk mitigation behavior. Ma et al (2017) investigate income inequality between Chinese rural and urban residents during 1978-2014, based on rural/urban flow and accumulated income Gini coefficients. The authors also compare the general changes in trends in these Gini coefficients in terms of urbanization and, by decomposing the Gini ratios, the ratio of urban to rural average income.…”

Section: Empirical Researchmentioning

confidence: 99%

How to Apply Advanced Statistical Analysis to Computational Economics: Methods and Insights

Song

Fisher

2018

Comput Econ

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The theme of this special volume concerns advanced statistical analysis. By mining meaningful and important information, advanced statistical analysis can bring new insights to many areas, such as the development of hospitals, the environment, biology, markets, industries, and general economic systems. The contribution of this special volume is to adopt an advanced parametric and nonparametric statistical approach for the exploration of environmental and health care issues in the context of computational economics. The authors have proposed varied methods of advanced statistical analysis combined with practical applications. In terms of theory, the authors suggest designs for advanced theoretical methods. With regard to the application of professional calculation methods to everyday life, the authors have offered useful guidance for future research. The authors have also conducted empirical research by using data from Chinese regions and analyzing specific conditions. In addition, they have conducted empirical analyses of particular issues such as those related to the environment. Although this special volume has provided some methods of advanced scientific analysis for existing problems, other techniques must be applied to everyday life in order to solve the severe difficulties that human beings face.

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The Income Gap Between Urban and Rural Residents in China: Since 1978

Cited by 53 publications

References 20 publications

Global redistribution of income and household energy footprints: a computational thought experiment

Global redistribution of income and household energy footprints: a computational thought experiment

Urban and Rural Income Gap: Does Urban Spatial Form Matter in China?

How to Apply Advanced Statistical Analysis to Computational Economics: Methods and Insights

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