Innovation performance of Chinese high-tech firms and its determinants: An empirical study based on quantile regression

Using panel data from enterprises in Shanghai Zhangjiang Hi-Tech Park and with quantile regression model, this paper empirically investigates various relevant factors that impact the innovation performance of high tech enterprises. Having compared these elements with OLS regression results, we have found the discriminate impact of factors such as enterprise scale, R&D expenditure, net assets debts ratio and technical efficiency at different quantile performance points. As the macro economy and industrial environment vary in different years, we add ownership structure as control variable, through which may get a better understanding what roles market mechanism can play in the innovation performance. Given that firms are heterogeneous and that performance rates distributions are heavy-tailed, it may be inappropriate to apply OLS regression method that focus on mean effect. To solve this problem, this paper uses quantile regression to establish an innovation performance model, aiming to investigate how different are the corresponding innovative output of firms, given a specification of the other conditioning factors, which would also enrich our comprehension of the elements effecting the performance of high tech firms. This paper also discusses policy implications of our result.