Technological change and unemployment: evidence from China

Abstract

This study investigates the impact of technological change on unemployment in China’s labour market based on a recent panel data of 283 prefectural-level cities from 2010 to 2017. The results obtained by the system Generalized Method of Moments (GMM-SYS) estimation show that massive adoption of robots is a significant driving force raising unemployment rate while there is a reverse change in the longer period; the insignificant estimates of utility patent and its lagged terms indicate the weak and non-persistent relationship between unemployment and patent-related innovation.