筛选创新产权

摘要

We develop a dynamic structural model of patent screening incorporating incentives, intrinsic motivation, and multiround negotiation. We use natural language processing to create a measure of patent distance, which together with detailed data on examiner decisions, enables us to estimate the model and study strategic decisions by applicants and examiners. Using the estimated model, we quantify the effectiveness of the U.S. Patent Office and evaluate counterfactual policy reforms. We find that patent screening is moderately effective, given the existing standards for patentability. Examiners exhibit substantial intrinsic motivation that strongly improves screening quality. We quantify the annual social costs of patent screening at $15.38bn, equivalent to 5% of total private sector R&D in the U.S. and show that reforms limiting the number of rounds of negotiation significantly reduce social costs.