The effects of trade unions on economic performance: evidence from Chinese provincial-level data

Abstract

Purpose

The purpose of this study is to investigate union effects on wages, employment, and productivity in China. The relationships between unionization and these three economic variables are first tested at the national level and then examined in the eastern, central, and western regions, respectively.

Design/methodology/approach

Provincial-level panel data from 1994 to 2014 are used in this study, compiled from various Chinese Statistics Year Books, and covering 29 provinces. The Ordinary Least Square is firstly employed to examine union impacts. Then, in view of the endogeneity of unionization, the Two-Stage Least Square estimation with instrument variables is adopted to reexamine union effects. Overidentification tests are conducted, verifying the validity of these instruments.

Findings

At the national level, Chinese unions have significantly positive effects on wages but no significant effect on employment and productivity. In the eastern region, unions are significantly related to increased employment. In the western region, union activity not only significantly promotes wages but also improves productivity. In the central region, unionization has no significant impact. These findings suggest that equipping Chinese unions with a collective and cooperative face can generally help them improve workers' interests. Their effectiveness varies across the three economic regions.

Originality/value

Compared with the survey data conducted in certain cities and industries, the provincial-level panel data used in this article have the advantage of capturing the overall effects of unionization. An instrument variable method is used to address the endogeneity issue. After exploring union effects at the national level, this paper focuses on observing the differences in union roles in three economic regions.

Citation

Guo, R. and Laroche, P. (2021), "The effects of trade unions on economic performance: evidence from Chinese provincial-level data", International Journal of Manpower, Vol. 42 No. 6, pp. 1084-1101. https://doi.org/10.1108/IJM-11-2018-0369