Abstract
Empirical research on the relationship between innovation and firm level productivity offers conflicting results. We investigate the impact of innovation on labour productivity through the construction of a unique panel data-set that merges information on roughly 5,000 publicly traded U.S. manufacturing firms from 1980-2003 with patent filings over the same time period. The large number of firms and long time span of the data allow us to control for the potentially confounding effects of unobservable firm and/or time specific shocks. While OLS estimates of citation-weighted patent stocks with respect to firm specific labour productivity are positive and statistically significant, corresponding results from instrumental variables (IV) and structural models are larger in magnitude, demonstrating the importance for accounting for potential simultaneity and sample selection bias. We also find that mergers are significantly correlated with a rise in citation weighted patent stocks and research and development (R&D) spending. Our interpretation is that larger firms spend more on research and development (R&D), which results in higher quality patents, and increased labour productivity.
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