Measuring the spatial and temporal dispari-ties in China's regional economic development and identifying the underlying influencing factors are crucial for the precise im-plementation of regional coordinated development policies.Utili-zing methods such as inequality index,Kernel density estima-tion,Markov transition probability matrix,and geographical va-riance decomposition,this study measures the economic develop-ment disparities across spatial units including prefecture-level cities,provincial regions,and seven major regions in China from 1997 to 2021.Furthermore,the research uses the spatial econo-metric models to analyze the mechanisms influencing regional e-conomic development disparities.The study finds that economic development inequity in spatial units,including prefecture-lev-el cities,provincial regions,and the seven major regions,show a trend of first rising and then declining.Kernel density graphs indicate that the economic development levels across spatial units are continuously increasing,but the evolution trends of the seven major regions are more complex and diverse compared to those of prefecture-level cities and provincial regions.There are signifi-cant changes in the rank order of per capita real GDP among pre-fecture-level cities and provincial regions,highlighting a com-petitive effect.The change in the proportion of geographical vari-ance shows that the economic development inequality between prefecture-level cities is gradually exceeding the economic de-velopment inequality between provincial regions.The results of the spatial econometric model suggest that market economic re-forms,fiscal decentralization,and the level of openness to the world are the key factors to influence regional economic develop-ment disparities.The conclusions of this study provide valuable insights for formulating precise regional development policies and narrowing regional economic development disparities.
regional economic developmenttemporal and spatial disparitiescoordinated regional developmentinflu-ence factor
万方数据
维普
