Interaction effects of government subsidies, R&D input and innovation performance of Chinese energy industry: a panel vector autoregressive (PVAR) analysis

Purpose : This article investigates the interaction effects among government subsidies, research and development (R&D) input and innovation performance of the Chinese energy industry.Methodology This article establishes a panel vector autoregressive (PVAR) model and uses the impulse response function (IRF) tool and variance decomposition of all variables to reveal the evolution process of variables' relationship in different time periods based on the data of 95 listed energy companies in China from 2010 to 2018.Findings : The results show that R&D input and innovation performance promote government subsidies; government subsidies and innovation performance promote R&D input; R&D input substantially promote innovation performance; and the dynamic interaction of the three variables differs for state-owned and non-state-owned companies.Originality : This article focuses on the Chinese energy industry and considers the ownership of companies. The PVAR model is used to establish a dynamic interactive system of variables, which considers the dynamic interaction relationship among government subsidies, R&D input and innovation performance in this specific industry.