Identification of “Valuable” Technologies via Patent Statistics in India: An Analysis Based on Renewal Information
Mohd Shadab Danish, Pritam Ranjan and Ruchi Sharma
BASE University Working Paper Series 13/2021
This study assesses the degree to which the patent attributes can capture the value of patents across discrete and complex innovations. We use the patents applied between 1995 to 2002 and granted on or before December 2018 from the Indian Patent Office. Here the patent renewal information is utilized as a proxy for the patent value. We have used generalized logistic regression model for the impact assessment analysis. The results reveal that the technology classification (i.e., discrete versus complex innovations) play an important role in patent value assessment, and some technologies are significantly different than the others even within the two broader classifications. Moreover, the non-resident patents in India are more likely to have a higher value than the resident patents. The significance pattern among the technological fields suggests that the patenting laws need to be revisited to enhance the efficiency.