Year-end Sale % OFF 
Abstract
The urban–rural income gap is a principal indicator for evaluating the sustainable development of a region, and even the comprehensive strength of a country. The study of the urban–rural income gap and its changing spatial patterns and influence factors is an important basis for the formulation of integrated urban–rural development planning. In this paper, we conduct an empirical study on 84 county-level cities in Gansu Province by using various analysis tools, such as GIS, GeoDetector and Boston Consulting Group Matrix. The findings show that: (1) The urban–rural income gap in Gansu province is at a high level in spatial correlation and agglomeration, leading to the formation of a stepped and solidified spatial pattern. (2) Different factors vary greatly in influence, for example, per capita Gross Domestic Product, alleviating poverty policy and urbanization rate are the most prominent, followed by those such as floating population, added value of secondary industry and number of Internet users. (3) The driving mechanism becomes increasingly complex, with the factor interaction effect of residents’ income dominated by bifactor enhancement, and that of the urban–rural income gap dominated by non-linear enhancement. (4) The 84 county-level cities in Gansu Province are classified into four types of early warning zones, and differentiated policy suggestions are made in this paper.
Highlights
This paper focuses on the following questions: (1) What are the regular characteristics of the spatial pattern and spatial effects of the urban–rural income gap in small cities, including the analysis and pattern identification of spatial heterogeneity and correlation characteristics of urban residents’ income, rural residents’ income and the urban–rural income gap? (2) What are the driving mechanisms of spatial variation in the urban–rural income gap in small cities, including the composition of influence factors, the size of direct effect and the interaction effect of multiple factors together? (3) How to create an early warning analysis model of urban–rural income gap in small cities and propose targeted response policies, including space governance risk classification and policy zoning?
The spatial heterogeneity of rural residents’ income and its changes is at the highest level, followed by the spatial heterogeneity of urban residents’ income and its changes, with the spatial heterogeneity of urban–rural income gap and its changes at the bottom
The spatial patterns of residents’ income and its changes, as well as urban–rural income gap and its changes, are multidimensional in nature, and different conclusions or new findings can be reached from different dimensions, such as economy, society, culture, geography and planning
Summary
Urban and rural areas are interrelated and interdependent, and together they contribute to the sustainable development of the regional economy. The urban–rural income gap is an important basis for measuring the capacity and level of comprehensive economic development of a country or region, as well as a crucial prerequisite for comprehensive and integrated urban–rural development. A large urban–rural income gap may have a negative impact on economic and social development. Young [1] found that national income inequality is largely caused by the urban–rural income gap, accounting for about. 40% of the total, according to an empirical analysis of 65 countries.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
