Temperature and Migration Intention: Evidence from the Unified National Graduate Entrance Examination in China

Yan Chen; Xiaohong Chen; Hongshan Ai; Xiaoqing Tan

doi:10.3390/ijerph191610244

Temperature and Migration Intention: Evidence from the Unified National Graduate Entrance Examination in China

Int J Environ Res Public Health. 2022 Aug 18;19(16):10244. doi: 10.3390/ijerph191610244.

Authors

Yan Chen^{1

2}, Xiaohong Chen^{1

2}, Hongshan Ai³, Xiaoqing Tan³

Affiliations

¹ School of Business, Central South University, Changsha 410083, China.
² School of Frontier Crossover Studies, Hunan University of Technology and Business, Changsha 410205, China.
³ School of Economics and Trade, Hunan University, Changsha 410079, China.

Abstract

This paper estimates the impact of destination cities' temperature on the migration intentions of highly educated talents. Using a unique manually collected dataset of applicants for the Unified National Graduate Entrance Examination (UNGEE) of double first-class universities in China, we find that both hot (over 25 °C) and cold (below 5 °C) days in the previous 3 months before the registration date significantly decrease the number of applicants for the UNGEE of double first-class universities, relative to a moderate (20-25 °C) day. Heterogeneity analysis shows that such effects differ by destination universities' quality and climate regions. We also find that destination cities' income level can mitigate the negative effects of hot days and cold days on the number of applicants. These findings add to the existent literature by examining an understudied relationship between temperature and migration intention.

Keywords: climate change; highly educated talents; migration intention; temperature.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

China
Cities
Climate*
Cold Temperature*
Hot Temperature
Temperature

Grants and funding

This research was funded by National Natural Science Foundation of China, grant number 71991483, 71974054, 71971080; Science-Technology Innovation Platform and Talents Program of Hunan Province, China, grant number 2019TP1053; Technical Service Items of Economic and Technological Research Institute in Hunan Electric Power Company, grant number 5216A220000A.