Journal of Happiness Studies
Volume 17, Issue 4, 2016, Pages 1635-1657

Social Insurance, Income and Subjective Well-Being of Rural Migrants in China—An Application of Unconditional Quantile Regression (Article)

Fang Z.* , Sakellariou C.
  • a Division of Economics, School of Humanities and Social Sciences, Nanyang Technological University, Singapore, 637332, Singapore
  • b Division of Economics, School of Humanities and Social Sciences, Nanyang Technological University, Singapore, 637332, Singapore

Abstract

This paper identifies determinants to positively influence the happiness level of rural-to-urban migrants at the bottom of the distribution of subjective well being (SWB) using an unconditional quantile regression rather than the conventional mean regression methodology. Using a basic regression specification, the positive effects of income and objective health status and the negative effect of work hours are found to be decreasing along the distribution of SWB, suggesting that standard factors are more relevant to the SWB of the subgroup of less happy migrants. Education seems to play a stabilizing role as it decreases the likelihood of extremes in well-being. From an examination of social insurance coverage and relative concerns, a positive relationship between pension and SWB is observed for the first time in happiness literature on Chinese migrants, suggesting interesting future research directions on the policy effects of the newly established New Rural Social Pension scheme on improving the SWB of people with rural hukou. Furthermore, the signal effect is found when migrants are compared with urban workers and the status effect is found when they are compared with other migrants. However, we find that only perceived, rather than objective income position matters. © 2015, Springer Science+Business Media Dordrecht.

Author Keywords

China migrant Insurance Income SWB Unconditional quantile

Index Keywords

[No Keywords available]

Link
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938099106&doi=10.1007%2fs10902-015-9663-3&partnerID=40&md5=7c90e0747640072dd3775aeccf17c2f8

DOI: 10.1007/s10902-015-9663-3
ISSN: 13894978
Cited by: 8
Original Language: English