County-Scale Destination Migration Attractivity Measurement and Determinants Analysis: A Case Study of Guangdong Province, China

Abstract

Measuring destination attractivity and finding the determinants of attractivity at the county scale can finely reveal migration flows and explain what kinds of counties have higher attractivity. Such understanding can help local governors make better policies to enhance county attractivity and attract more migrants for regional development. In this study, the county-scale relative intrinsic attractivity (RIA) of Guangdong Province is computed using the number of migrants and the corresponding distances between origins and destinations. The results show that the RIA has a higher positive correlation with the flows of migrants to destination and demonstrates an obvious phenomenon of distance decay. The RIA decreases faster when the distance between origins and destinations increases. Spatially, the RIA reveals a core-periphery belt pattern in Guangdong Province. The center of the Pearl River Delta is the highest core of RIA and the outside areas of the delta represent the low-RIA belt. The highest RIA is 6811 in Dongguan City and the lowest RIA is 1 in Yangshan County. The core area includes Dongguan, Shenzhen City and the southern regions of Guangzhou, Foshan and Zhongshan City where the RIA value is higher than 1000. The second belt is mainly composed of the periphery districts of the Pearl River Delta, which include Shunde, Nanhai, Luohu, Tianhe Huicheng, Panyu, Haizhu, Huiyang, Huadu, Yuexiu, Xiangzhou and the Yuexiu, Huangpu and Boluo, where the RIA values are higher than 100 and lower than 1000. The third belt includes the western wing, eastern wing and northern area. Most of these RIA values range from 1 to 2. In this belt, there are three areas with relatively higher RIA attractivity scattered in the ring: the downtowns of Zhanjiang City, Chaozhou and Shantou Cities and Shaoguan City. The areas farther away from the core have a lower RIA score. Determinants analysis indicates that the RIA is positively determined by destination economic development level, social service and living standard level and destination population quality. A region will be more attractive if it has higher per capital GDP, tertiary industry level, investment and number of industrial enterprises involved in economic development. A region with a high annual average wage of employees and high social service and living standards will be more attractive, while a region with low destination population quality, including aspects such as the adult illiteracy rate, will be less attractive.

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