Economic geography of talent migration and agglomeration in China: A dual-driver framework

Hengyu Gu, Junhui Wang and Yingkai Ling

China Economic Review, 2024, vol. 86, issue C

Abstract: The long-standing debate on the role of economic factors and amenities on talent migration and redistribution foreshadows the importance of spatial economic theoretical thinking in resolving the effects of duality, a point yet to be conclusively addressed in the existing literature. Situated within the framework of new economic geography (NEG), this article introduces an innovative theoretical model – the Dual-Driver (DD) framework– aiming at comprehending the nuanced dual impact of economic and amenity factors on talent movements between regions. While the DD framework retains the mechanisms of increasing returns to scale, iceberg transportation cost, and talent agglomeration presented in the NEG models, it depicts, for the first time, the self-reinforcing mechanisms between non-traded goods (i.e., amenities) and talent agglomeration. The model describes a logic of talent movements influenced by the dual drivers of regional economic factors (nominal wage, the diversity of local manufacturing products) and amenities (the diversity and quality of amenities, transfer payment for talent), among which the economic effects play a predominant role versus the amenity effects. Empirical evidence has been given by the geographical analysis of China's internal talent migration between 2000 and 2015 and the corresponding econometric analysis using the Poisson pseudo-maximum likelihood (PPML) estimation. Our findings furnish a theoretical perspective for comprehending talent geography and offer policy insights into China's logic of talent migration.

Keywords: Talent migration and agglomeration; Amenities; The dual-driver (DD) framework; New economic geography (NEG); China (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chieco:v:86:y:2024:i:c:s1043951x24000695

DOI: 10.1016/j.chieco.2024.102180

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