The flow direction selection of the new generation of highly educated floating population and the influence mechanism of the selection
【Abstract】In recent years, with the rapid development of economy and the advancement of urbanization, the composition of floating population tends to be diversified. The new-generation highly educated floating population represented by the post-80s and the post-90s keeps increasing, compared with ordinary floating population. This group has stronger competitiveness and higher level of human capital in the labor market. In the context of competition for talents in the new era, the new-generation highly educated group has gradually become the foundation and fundamental driving force for regional development. As a young creative class, this group’s choice of future flow direction has an important impact on promoting the rapid development of urban economy, improving the level of national income, and optimizing the rational allocation of human resources and other aspects. This paper uses the data of dynamic monitoring survey of floating population in 2017 collected by the National Health and Family Planning Commission of the People’s Republic of China to analyze the migration choice of the highly educated migrants. The study found that this group mainly gathered in the five regions of Beijing-Tianjin-Hebei, Jiangsu-Zhejiang-Shanghai, Guangdong-Fujian-Guangxi, Sichuan-Chongqing-Guizhou, and Shanxi-Anhui-Henan. Based on the dual economy theory, human capital theory, and new labor migration theory, this paper uses multiple Logistic regression model to analyze and summarize the multi-dimensional characteristics of this group and the influence of various factors which have an effect on the flow direction selection of the highly educated floating population from the perspective of individual, migration and economy.The results show that individual factors, flow factors and economic factors have significant influence on their choice of flow direction. The number of the family members has the highest influence on the flow direction of the selected area, followed by the nature of household registration. Gender has a significant but weak influence on the flow choice of the new generation of highly educated floating population. The flow range has the most significant influence on the choice of flow direction in Beijing-Tianjin-Hebei region and Jiangsu-Zhejiang-Shanghai region. Economic factors have a particularly significant impact on the flow choice of the new generation of highly educated floating population. In regions with developed economy and high monthly income, the effect of talent aggregation is more obvious.
【Keywords】 highly educated; new generation of migrant population; migration choice; multiple Logistic regression model;
(Translated by ZHU Jie)
 Du, B. & Miao, F. Population Research (人口研究), 36(6): 71–86 (2012).
 Li, H. & Yang, J. Population and Society (人口与社会), 33(3): 3–12 (2017).
 Liu, S., Hu, Z. & Deng, Y. Geographical Research (地理研究), 30(4): 676–686 (2011).
 Xiao, X. Population and Society (人口与社会), 30(4): 33–38 (2014).
 Zhu, P. Rural Economy and Science-Technology (农村经济与科技), 23(7): 52–54 (2012).
 Zhang, X. master’s thesis, Huazhong Agricultural University, (2006).
 Guo, X. & Xing, C. Academic Journal of Zhongzhou (中州学刊), (6): 103–108 (2009).
 Yao, H., Xu, X. & Xue, D. Urban Problems (城市问题), (6): 69–76 (2008).
 Lewis W A. Economic Development with Unlimited Supplies of Labour. Manchester School, 1954, 22: 139–191.
 Narasimhan. Labour Out-migration to Cities: Search for an Appropriate Theory. Man-and-Development, 1995, 17(1): 78–88.
 R Herberle. The Cause of Rural-Urban Migration a Survey of German Theories. The American Journal of Sociology, 1938, (43): 932–950.
 Galor, Stark. The Probability of Return Migration, Migrants’ Work Effort, and Migrants’ Performance. Journal of Development Economics, 1991, 35(2): 399–405.
 Lucas R E B. Emigration to South Africa’s Mines. The American Economic Review, 1987, 77(3): 313–330.
 Taylor J E, Wyatt T J. The Shadow Value of Migrant Remittances, Income and Inequality in a Household-farm Economy. Journal of Development Studies, 1996, 32(6): 899–912.
 Portes A,Sensenbrenner J. Embeddedness and Immigration:Notes on the Social Determinants of Economic Action.American Journal of Sociology,1993,98(6):1320–1350.
 Carrington W J, Detragiache E, Vishwanath T. Migration with Endogenous Moving Costs. American Economic Review, 1996, 86(4): 909–930.
 Xiong, L., Xie, M. & Zhou, W. Urban Insight (城市观察), (3): 170–176 (2011).
 Massey D S. Understanding Mexican Migration to the United States. American Journal of Sociology, 1987, 92(6): 1372–1403.
 Yu, Y. & Li, C. Commercial Research (商业研究), (8): 161–166 (2018).
 Zhang, Y. & Cen, Q. Population Research (人口研究), 38(5): 54–71 (2014).
 Gao, Y. & Dong, Z. Journal of Beijing Union University (Humanities and Social Sciences) (北京联合大学学报(人文社会科学版)), 16(1): 107–119 (2018).
 Zhao Y. Labor Migration and Earnings Differences: The Case of Rural China. Economic Development&Cultural Change, 2015, 47(4): 767–782.
 Yan, S. Management World (管理世界), (8): 8–17, 171 (2006).
 Duan, C. Population Research (人口研究), (4): 14–22 (2000).
 Ritchey P N. Explanations of Migration. Annual Review of Sociology, 1976, 2(2): 363–404.
 Xu, A. & Wu, G. West Forum (西部论坛), 25(6): 10–17 (2015).
 Wang, X., Chen, H. & Fang, X. Journal of Harbin University of Commerce (Social Science Edition) (哈尔滨商业大学学报(社会科学版)), (3): 118–128 (2017).
 Bai, Y. & Gan, X. Enterprise Economy (企业经济), (7): 132–133 (2005).
 Li, X., Huang, Y. & Xu, X. China Population, Resources and Environment (中国人口·资源与环境), 25(9): 70–80 (2015).
 Wu, X., Lin, J. & Liu, W. Chinese Rural Economy (中国农村经济), (4): 27–33 (2005).
 Perz S G, Leite F, Simmons C, et al. Intraregional Migration, Direct Action Land Reform,and New Land Settlements in the Brazilian Amazon. Bulletin of Latin American Research, 2010, 29(4): 459–476.
 Meng, Z. & Wu, R. Population and Development (人口与发展), 17(3): 11–18 (2011).