The combination of digital technology and finance has brought about a new development model for financial inclusion. What impact will it have on the current imbalance in the distribution of financial resources and the urban-rural income gap in China? To answer this question, this paper uses relevant data from 2014–2018 to study the impact of digital inclusive finance on the urban-rural income gap from the theory of financial exclusion, and analyzes the transmission of digital inclusive finance through alleviating financial exclusion, widening financing channels and helping residents with entrepreneurial spirit to start their own businesses, thus increasing jobs, raising the income of rural residents and reducing the urban-rural income gap. The conclusions are as follows: (1) digital inclusive finance can significantly converge the urban-rural income gap; (2) among the dimensions of digital inclusive finance, only the breadth of coverage can significantly reduce the urban-rural income gap, while the effects of depth of use and digitalization are not significant; (3) digital inclusive finance can alleviate the urban-rural income gap through the transmission mechanism of promoting residents’ entrepreneurship; (4) the worse the regional economic development and education, the better the effect of digital inclusive finance on the urban-rural income gap. This paper combines the above results to propose corresponding policy recommendations.

https://www.mdpi.com/2071-1050/13/15/8292/pdf

Has Digital Financial Inclusion Narrowed the Urban-Rural Income Gap: The Role of Entrepreneurship in China

Urban-biased land development policy and the urban-rural income gap: Evidence from Hubei Province, China

The influences of aging population and economic growth on Chinese rural poverty

Household consumption carbon footprint and inequality reductions are vital for a sustainable society, especially for rural areas. This study, focusing on rural China, one of the fastest growing economies with a massive population, explored the carbon footprint and inequality of household consumption using the latest micro household survey data of 2018 linked to environmental extended input--output analysis. The results show that in 2018 in rural China, the average household carbon footprint is 2.46 tons CO2-eq per capita, which is around one-third of China's average footprint, indicating the large potential for further growth. Housing (45.32%), transportation (20.45%), and food (19.62%) are the dominant contributors to the carbon footprint. Meanwhile, great inequality, with a Gini coefficient of 0.488, among rural households is observed, which is largely due to differences in type of house built or purchased (explaining 24.44% of the variation), heating (18.10%), car purchase (12.44%), and petrol consumption (12.44%). Provinces, average education, and nonfarm income are among the important factors influencing the inequality. In the process of urbanization and rural revitalization, there is a high possibility that the household carbon footprint continues to increase, maintaining high levels of inequality. The current energy transition toward less carbon-intensive fuels in rural China is likely to dampen the growth rates of carbon footprints and potentially decrease inequality. Carbon intensity decrease could significantly reduce carbon footprints, but increase inequality. More comprehensive measures to reduce carbon footprint and inequality are needed, including transitioning to clean energy, poverty alleviation, reduction of income inequality, and better health care coverage.

Reducing Carbon Footprint Inequality of Household Consumption in Rural Areas: Analysis from Five Representative Provinces in China.

By 2013, several regions in China had introduced health insurance integration policies. However, few studies addressed the impact of medical insurance integration in China. This study investigates the catastrophic health expenditure and equity in the incidence of catastrophic health expenditure by addressing its potential determinants in both integrated and non-integrated areas in China in 2013. The primary data are drawn from the fifth China National Health Services Survey in 2013. The final sample comprises 19,788 households (38.4%) from integrated areas and 31,797 households (61.6%) from non-integrated areas. A probit model is employed to decompose inequality in the incidence of catastrophic health expenditure in line with the methodology used for decomposing the concentration index. The incidence of catastrophic health expenditure in integrated areas is higher than in non-integrated areas (13.87% vs. 13.68%, respectively). The concentration index in integrated areas and non-integrated areas is − 0.071 and − 0.073, respectively. Average household out-of-pocket health expenditure and average capacity to pay in integrated areas are higher than those in non-integrated areas. However, households in integrated areas have lower share of out-of-pocket expenditures in the capacity to pay than households in non-integrated areas. The majority of the observed inequalities in catastrophic health expenditure can be explained by differences in the health insurance and householders’ educational attainment both in integrated areas and non-integrated areas. The medical insurance integration system in China is still at the exploratory stage; hence, its effects are of limited significance, even though the positive impact of this system on low-income residents is confirmed. Moreover, catastrophic health expenditure is associated with pro-poor inequality. Medical insurance, urban-rural disparities, the elderly population, and use of health services significantly affect the equity of catastrophic health expenditure incidence and are key issues in the implementation of future insurance integration policies.

/pdf/catastrophic-health-expenditure-incidence-and-its-equity-in-kejtz1k192.pdf

Catastrophic health expenditure incidence and its equity in China: a study on the initial implementation of the medical insurance integration system

Data insufficiency has become the primary factor affecting research on income disparity in China. To resolve this issue, this paper explores Chinese income distribution and income inequality using distribution functions. First, it examines 20 sets of grouped data on family income between 2005 and 2012 by the China Yearbook of Household Surveys, 2013, and compares the fitting effects of eight distribution functions. The results show that the generalized beta distribution of the second kind has a high fitting to the income distribution of urban and rural residents in China. Next, these results are used to calculate the Chinese Gini ratio, which is then compared with the findings of relevant studies. Finally, this paper discusses the influence of urbanization on income inequality in China and suggests that accelerating urbanization can play an important role in narrowing the income gap of Chinese residents.

/pdf/chinese-gini-coefficient-from-2005-to-2012-based-on-20-bm6jnf2hph.pdf

Chinese Gini Coefficient from 2005 to 2012, Based on 20 Grouped Income Data Sets of Urban and Rural Residents

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Chinese Gini Coefficient from 2005 to 2012, Based on 20 Grouped Income Data Sets of Urban and Rural Residents

Chinese Gini Coefficient from 2005 to 2012, Based on 20 Grouped Income Data Sets of Urban and Rural Residents