Effects of human capital difference on migration destination preference of rural floating population in China

Abstract

This paper first constructs a theoretical framework to investigate rural migrants’ preference for large cities or small and medium-sized cities as migration destinations. Then, we employ a nested logit model to empirically examine the effects of migration cost and benefit on the probability of migration to different types of cities. Our results suggest that since large cities provide more job opportunities and higher net migration benefit compared with small- and medium-sized cities, rural migrants with relatively high skills are more likely to move to large cities. Although the effects of migration cost and benefit on migration destination decisions are both significant, the effect of migration benefit outweighs that of migration cost. Hence, gaining net migration benefit is the main reason that rural migrants prefer to move to cities, especially to large cities.

Keywords:

• Human capital
• migration probability
• migration cost
• migration benefit

Acknowledgement

This paper has been presented at the 2018 International Workshop on ‘China’s Development Experience and Enlightenment’. We thank all participants for their useful comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 According to “State Council Notification on Adjusting Dividing Standards of Urban Scale”, megalopolis is a city with more than 10 million urban resident population (e.g. Shanghai, Beijing, Guangzhou, Shenzhen, Tianjin and Chongqing); metropolis is a city with 5–10 million urban resident population (e.g. Hangzhou, Nanjing, Wuhan, Chengdu, Shenyang, Xi’an, Jinan, Kunming, Harbin, Dalian, Qingdao, Suzhou, Ningbo and Wuxi).

2 We also include information of whether the migrants have met discrimination in the migration destination. Although it is not favorable, we count it as a pull variable. We assume that without migration, rural floating population are willing to move to cities.

3 We have also classified the rural floating population by the average education of 7.7 years. That is, rural floating population with more than 7.7 years’ education are considered as high skilled while those receive less than 7.7 years’ education are considered as low skilled. The results are robust. We may further classify the rural floating population by graduate or undergraduate students. However, our sample contains only 88 respondents who have bachelor degree or above. Another concern is that on average, the respondents receive less than 8 years’ education. Therefore, classifying the rural floating population according to the standard of undergraduate/graduate students may be not applicable.

Additional information

Funding

The study has received support from Shanghai Planning Office of Philosophy and Social Science Project (No.2017EJB006) and National Natural Science Foundation of China (No.71803130).

Notes on contributors

Haitao Zhao

Haitao Zhao is a lecturer at College of Law and Politics, Shanghai Normal University, China. His research interest includes Chinese immigrants, labor market segmentation and employment. He has published around 10 academic papers at journals like Chinese Journal of Population Science, China Economic Quarterly, World Economic Papers and Economic Management Journal.

Naiquan Liu

Naiquan Liu is a Professor of Economics at Shanghai University of Finance and Economics, China. His research includes Asian economy, regional economy and industrial economy. He has published more than 70 academic papers at journals like Economic Research Journal, The Study of Finance and Economics, China Industrial Economics, Economic Perspectives and many academic books.

Jinxian Wang

Jinxian Wang is a lecturer at the Central South University, China. Her research interest includes social assistance and minimum income protection, poverty and income inequality. Her papers has published at journals like Cambridge Journal of Economics, Comparative European Politics, Eastern European Economics and so on.