TITLE:
Study on the Level of Talent Attractiveness of the Yangtze River Delta Urban Agglomerations Using Bayesian Quantile Regression Method
AUTHORS:
Yu Zhang, Haomin Zhang, Lingfang Wei
KEYWORDS:
Talent Attraction, Evaluation Index, Yangtze River Delta Urban Agglomerations, Quantile Regression
JOURNAL NAME:
Theoretical Economics Letters,
Vol.11 No.6,
December
9,
2021
ABSTRACT: Innovation is the first driving force to lead
development, and the carrier of innovation drive is talent, and talent has been
an important strategic resource to lead social development in the 21st century. And different levels of cities should focus on the strategy of
attracting talents. In this paper, based on the index data of the Yangtze River
Delta Urban Agglomerations in 2019, we construct the evaluation talent
attractiveness level score and use it to build a Bayesian quantile regression
model to map the focus that cities of different levels should focus on talent
attraction policies. The results show that the marginal gain of talent
attraction is different for different level cities in different dimensions. By
quantifying the level of talent attractiveness of different cities through the
objective assignment method, we find the differences in the spatial distribution
of talent attractiveness of different cities in the Yangtze River Delta region
and provide theoretical guidance for the integration of the Yangtze River
Delta. At the same time, by exploring the differences in the talent
attractiveness of cities of different levels that should be focused on, we find
the general rules and provide reference and guidance for other cities.