Patents, misallocation and spillovers

This article studies the relationship between patent protection, knowledge diffusion and aggregate productivity. Motivated by the strengthening of U.S. patent enforcement associated with the creation of the Court of Appeals for the Federal Circuit in 1982, we combine patent and firm-level data for 1976–2006 to construct firm-specific exposure to patents granted to technologically related firms. Greater patent exposure is associated with a smaller measured spillover pool. This association remains negative and statistically significant after including industry-year fixed effects and technology-class-year controls, using alternative measures of technological proximity and patent timing, weighting patents by citations and excluding patent-thicket industries. Dynamic specifications show that future patent exposure does not predict current spillovers. We use these micro estimates to discipline a general equilibrium model with heterogeneous firms, endogenous R&D and knowledge spillovers. The estimated decline in spillovers maps into a reduction in the spillover elasticity from 0.45 to approximately 0.10, lowering aggregate TFP by 8.3%; eliminating spillovers lowers TFP by 10.8%. Weaker diffusion also reduces participation in R&D and concentrates innovation among larger firms. The results imply that patent regimes that hinder knowledge diffusion may entail substantial aggregate productivity costs by constraining follow-on innovation and narrowing participation in R&D.

Authors

Institutions

Publication Details

Journal
Applied Economics
Published
2026-09-11
DOI
https://doi.org/10.1080/00036846.2026.2731165
Primary Topic
Intellectual Property and Patents
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Patents, misallocation and spillovers

Juan A. Correa, Francisco Parro
Applied Economics
Intellectual Property and Patents
article

Patents, misallocation and spillovers

Juan A. Correa, Francisco Parro
article en

Abstract

This article studies the relationship between patent protection, knowledge diffusion and aggregate productivity. Motivated by the strengthening of U.S. patent enforcement associated with the creation of the Court of Appeals for the Federal Circuit in 1982, we combine patent and firm-level data for 1976–2006 to construct firm-specific exposure to patents granted to technologically related firms. Greater patent exposure is associated with a smaller measured spillover pool. This association remains negative and statistically significant after including industry-year fixed effects and technology-class-year controls, using alternative measures of technological proximity and patent timing, weighting patents by citations and excluding patent-thicket industries. Dynamic specifications show that future patent exposure does not predict current spillovers. We use these micro estimates to discipline a general equilibrium model with heterogeneous firms, endogenous R&D and knowledge spillovers. The estimated decline in spillovers maps into a reduction in the spillover elasticity from 0.45 to approximately 0.10, lowering aggregate TFP by 8.3%; eliminating spillovers lowers TFP by 10.8%. Weaker diffusion also reduces participation in R&D and concentrates innovation among larger firms. The results imply that patent regimes that hinder knowledge diffusion may entail substantial aggregate productivity costs by constraining follow-on innovation and narrowing participation in R&D.

Applied Economics
Universidad Andrés Bello (CL), Adolfo Ibáñez University (CL)
Industry, innovation and infrastructure
Openalex Percentile: Top 5%
Intellectual Property and Patents
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.