ABSTRACT
In 2015, the Chinese government issued the Decision on Poverty Alleviation(DPA), requiring poverty-stricken areas to develop local characteristic industries based on their resource endowments, to promote industrial structure diversification and industrial structure upgrading through industry-driven poverty alleviation. However, existing research lacks empirical analysis to evaluate it. Therefore, this paper takes poor counties in the Qinba Mountain contiguous poverty-stricken areas(QMCPA) as an example, using the difference in difference model and boundary effect model to evaluate whether DPA has promoted industrial structure upgrading and industrial structure diversification in poor counties. The results show that the DPA has promoted industrial structure upgrading and improved industrial structure diversification in the QMCPA. However, the effectiveness of it is not sufficient. Poor counties have failed to maintain the policy requirement of developing characteristic industries based on local natural resource endowments, leading to a decline in the degree of industrial structure diversification in the later period of the policy. This study indicates that local governments should strive to develop advantageous industries and form a division of labor and cooperation with neighboring areas, strengthen inter-regional cooperation and contact, and enhance anti-risk capabilities to avoid homogenized competition. Studying the changes in industrial structure in the QMCPA has important significance for the long-term stable development and poverty elimination of various poor areas.
ABSTRACT
Rapid urbanization has gradually strengthened the spatial links between cities, which greatly aggravates the possibility of the spread of an epidemic. Traditional methods lack the early and accurate detection of epidemics. This study took the Hubei province as the study area and used Tencent's location big data to study the spread of COVID-19. Using ArcGIS as a platform, the urban relation intensity, urban centrality, overlay analysis, and correlation analysis were used to measure and analyze the population mobility data of 17 cities in Hubei province. The results showed that there was high similarity in the spatial distribution of urban relation intensity, urban centrality, and the number of infected people, all indicating the spatial distribution characteristics of "one large and two small" distributions with Wuhan as the core and Huanggang and Xiaogan as the two wings. The urban centrality of Wuhan was four times higher than that of Huanggang and Xiaogan, and the urban relation intensity of Wuhan with Huanggang and Xiaogan was also the second highest in the Hubei province. Meanwhile, in the analysis of the number of infected persons, it was found that the number of infected persons in Wuhan was approximately two times that of these two cities. Through correlation analysis of the urban relation intensity, urban centrality, and the number of infected people, it was found that there was an extremely significant positive correlation among the urban relation intensity, urban centrality, and the number of infected people, with an R2 of 0.976 and 0.938, respectively. Based on Tencent's location big data, this study conducted the epidemic spread research for "epidemic spatial risk classification and prevention and control level selection" to make up for the shortcomings in epidemic risk analysis and judgment. This could provide a reference for city managers to effectively coordinate existing resources, formulate policy, and control the epidemic.
