Spatio-temporal evolution mechanism of China's internal skilled migration

The migration of skilled individuals has become an important issue in promoting new-type urbanization in China and a key factor affecting China's regional innovation output and high-quality development. Considering the issues of zero inflation and network autocorrelation in skilled migration data, this paper combines the eigenvector space filtering (ESF) technique and the "two-stage" hurdle model into a comprehensive united framework to construct a longitudinal spatial hurdle gravity model. It then has been employed in the case study exploring the spatiotemporal patterns and influencing factors of interprovincial skilled migration in China during 2000-2015. The results are listed as follows: First, from 2000 to 2015, the mobility proportion of the skilled migration increased first and then decreased. The agglomeration pattern of skilled migration maintains the imbalance of its spatial distribution. With the elapse of time, the migration of skilled presents a dispersing trend and drives the decline of its spatial distribution and agglomeration. Talent migration presents a persistent and significant network autocorrelation, and its distribution presents a persistent and significant spatial autocorrelation. Second, China's interprovincial skilled migration during 2000-2015 was driven by gravity factors (population scales at origin and destination, distance), regional economic and scientific and technological development (average wage, spending on science & technology and education), natural amenities (average temperature difference, air quality), urban amenities (public health and education services, urban greening), and other factors (social networks, the cost of living, and population density). Third, the migration of skilled people can be regarded as a "two-stage" process, where factors affecting its migration probability and migration scale are different. Such differences are mostly reflected in factors of amenities versus economy. Fourth, the impact of economic growth, investment in science and education, natural amenities, and basic public services on skilled migration has increased over time, while the impact of wages and urban greening has weakened over time. The conclusion of this paper provides policy references for regional talent management and the balance of regional development. © 2022, Science Press. All right reserved.