| Abstract: |
We develop a dynamic structural model of patent screening incorporating
incentives, intrinsic motivation, and multi-round negotiation. We use natural
language processing to create a new 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 negotiation rounds significantly reduce
social costs. |