Patent citations and knowledge spillovers: an empirical analysis of Indian patents

Abstract

ABSTRACT This study uses patent citations data to measure knowledge spillovers at three levels: inventor, firm, and technology. We have collected Indian patents data granted by the United States Patent and Trademark Office (USPTO) and their backward citations from 1990 to 2019. To conduct our empirical analysis, we apply the Negative Binomial (NB) and Generalised Negative Binomial Model (GNBM). To account for other factors influencing knowledge spillovers, we control for patent inventor size, applicant size, patent scope, and claims. Our findings show that US-origin inventors outperform Indian and European inventors in terms of knowledge spillover from patent citations. Similarly, US firms show better knowledge spillover performance than Indian firms, foreign firms, Indian research centres, and other ownership categories. Lastly, the knowledge spillovers in chemistry technology patents are high compared to mechanical engineering, electrical engineering, and other technology categories from existing patent stock. The emperical finding of our study suggests that the government can promote knowledge spillovers from patent citations and advance India towards a knowledge-based economy by attracting foreign inventors and firms in the country, investing in domestic R&D, and developing human capital.