Manufacturing and Regulatory Barriers to Generic Drug Competition: A Structural Model Approach

Yixin (Iris) Wang (), Jun Li () and Ravi Anupindi ()
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Yixin (Iris) Wang: Gies College of Business, University of Illinois Urbana–Champaign, Champaign, Illinois 61820
Jun Li: Ross School of Business, University of Michigan, Ann Arbor, Michigan 48109
Ravi Anupindi: Ross School of Business, University of Michigan, Ann Arbor, Michigan 48109

Management Science, 2023, vol. 69, issue 3, 1449-1467

Abstract: Understanding the drivers of market concentration in the generic pharmaceutical industry is essential to guaranteeing the availability of low-cost generics. In this paper, we develop a structural model to capture the multiple determinants governing manufacturers’ entry decisions; in particular, we focus on how manufacturing complexity and the regulatory environment for generics approval affect concentration in drug markets. We estimate the model using data collated from six disparate sources. We find that manufacturing complexity, as reflected in the number of active ingredients, for example, significantly reduces the likelihood of generics entry. Moreover, the delay in the review process for the generics applications significantly affects the number of firms entering a market. Our policy simulations suggest that a shortened drug approval review time significantly increases the average number of entrants per market and reduces the fraction of markets with no generics entry; however, a notable portion of markets would still lack any generic competition.

Keywords: government: regulations; structural modeling; market entry decision (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:69:y:2023:i:3:p:1449-1467

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