Wage gap between the State and non-State sectors in China: a study from the perspective of the Housing Provident Fund Scheme

ABSTRACT

As an important component of China’s social security system, the housing provident fund (HPF) scheme has seen its fairness called into question. Based on the data from the China Household Finance Survey in 2017, this paper uses the least squares method and the unconditional quantile regression and decomposition method to study the wage gap between the state and non-state sectors from the perspective of the HPF. Its findings suggest that the HPF is an important component of the state-sector wage premium. That is, whether wages include the HPF affects the direction and significance of the sectoral wage gap. A closer look reveals that in the state sector, low-income workers benefit less from the HPF scheme than middle- and high-income workers. The breakdown of the wage gap within the state sector indicates that the wage premium for the middle- and high-income bracket and for the high-income bracket are mainly credited to the differences in individual characteristics of state-sector workers, while the wage premium obtained by the middle- and low-income bracket takes the form of the sectoral wage level, which benefits from the HPF system to some extent.

KEYWORDS:

• State sector
• Non-state sector
• Wage gap
• Housing provident fund

Acknowledgments

We are grateful to Yanan Li, Xuejing Lyu for helpful discussions on the topic of this paper, and to Labor history editor and reviewers for comments on an Manuscript. These suggestions are essential for the publication of this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. See the 2019 Annual Report for National Housing Provident Fund by the Ministry of Housing and Urban-Rural Development; for data on employees and GDP, see China Statistical Yearbook.

2. Distribution decomposition based on the classical linear regression, including JMP1993 decomposition and FL1998 decomposition; distribution decomposition based on semiparametric models, including DEL decomposition and Lemieux decomposition; distribution decomposition based on conditional quantile regression, including MM2005 decomposition and Q-JMP decomposition; and distribution decomposition based on RIF regression, i.e. FFL decomposition.

3. Subscript ‘s’ denotes the state sector, subscript ‘n’ denotes the non-state sector, and $Y_c$ denotes the counterfactual wage.

Additional information

Funding

This work was supported by the Beijing Municipal Social Science Fund and the Beijing Municipal Education Commission under grant SZ202010038022; the Fujian Provincial Social Science Fund under grant FJ2022B161; the start-up funds of Fujian University of Technology under grant GY-S21009.

Notes on contributors

Zimian He

Zimian He is a lecturer from the School of Internet Economics and Business at Fujian University of Technology. Her research focuses on labor and social security, employment and income inequality.

Hua Jiang

Hua Jiang is an associate professor and doctoral supervisor from the Department of Labor and Social Security, School of Labor Economics, Capital University of Economics and Business. He examines China’s social security system through the lens of equity and has published numerous works on the topic, including his book The Unbalanced Development of Social Security Economic Equity (Social Sciences Academic Press(China), 2020).

Panpan Gao

Panpan Gao is a lecturer from School of Labor Economics and Management, Beijing Vocational College of Labor and Social Security. Her main research interests lie within the sections of labour, gender, and wage gap.