The effects of capital and labour distortion on innovation

Factor misallocation has significant effects on productivity and innovation (Bento and Restuccia, 2017). In addition, aggregate total factor productivity could be lowered by factor misallocation across heterogeneous production units (Restuccia and Rogerson, 2013). Factor misallocation not only has important effects on productivity, but also plays a significant role in innovation (Bai and Bian, 2016). Innovation is widely regarded as the most important element for economic growth (Feldman and Link, 2001; Guellec and Potterie, 2004; Chen et al., 2015). The purpose of this thesis is to study how capital distortions and labour distortions influence innovation activities in China. Province-level data is manually collected from the China Statistical Yearbook and the China Statistical Yearbook on Science and Technology. This research applies the generalized least square (GLS) method with province and year fixed effects, the Generalized Method of Moments (GMM) model with introduced instrumental variables, and a natural experiment with an exogenous shock. The results indicate that the measurements for factor misallocation – capital distortion and labour distortion - are significantly negatively correlated to innovation. The findings have important implications for emerging countries to improve their innovation productivity.