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Competition and R&D Financing: Evidence From the Biopharmaceutical Industry

Published online by Cambridge University Press:  26 April 2021

Richard T. Thakor*
Affiliation:
University of Minnesota Carlson School of Management, Finance Department, and MIT LFE
Andrew W. Lo
Affiliation:
MIT Sloan School of Management, MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), MIT Laboratory for Financial Engineering, Santa Fe Institute, and NBER alo-admin@mit.edu
*
rthakor@umn.edu (corresponding author)
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Abstract

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The interaction between product market competition, R&D investment, and the financing choices of R&D-intensive firms on the development of innovative products is only partially understood. We hypothesize that as competition increases, R&D-intensive firms will: i) increase R&D investment relative to existing assets in place; ii) carry more cash; and iii) maintain less net debt. Using the Hatch–Waxman Act as an exogenous shock to competition, we provide causal evidence supporting these hypotheses through a differences-in-differences analysis that exploits differences between the biopharma industry and other industries, and heterogeneity within the biopharma industry. We also explore how these changes affect innovative output.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

We thank Jarrad Harford (the editor), Raj Iyer, Danmo Lin, Debbie Lucas, Andrey Malenko, Stew Myers, Dimitris Papanikolaou (the referee), Matt Rhodes–Kropf (discussant), and participants at the American Finance Association Meetings for helpful comments and discussions. We also thank Nicholas Anaya, Christian Vilanilam, and Yuwei Zhang for research assistance, and Jayna Cummings for editorial assistance. Research support from the MIT Laboratory for Financial Engineering is gratefully acknowledged. The views and opinions expressed in this article are those of the authors only and do not necessarily represent the views and opinions of any institution or agency, any of their affiliates or employees, or any of the individuals acknowledged above.

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