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Therapeutic Equivalence and the Generic Competition Paradox

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  • Nabin Munirul Haque

    ()
    (Deakin University)

  • Mohan Vijay

    ()
    (Deakin University)

  • Nicholas Aaron

    ()
    (Deakin University)

  • Sgro Pasquale M.

    ()
    (Deakin University)

Abstract

Following the passage of the Waxman-Hatch Act (1984), FDA approval for a generic drug requires the establishment of bio-equivalence between the generic drug and an FDA approved branded drug. However, a large body of evidence in the medical community suggests that bio-equivalence does not guarantee therapeutic equivalence; in some instances the lack of therapeutic equivalence can lead to fatal consequences for patients switching to generic products. In this paper, we construct a simple model to analyze the implications of therapeutic non-equivalence between branded and generic drugs. We show, theoretically and empirically, that this distinction can provide a plausible explanation of the generic competition paradox.

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Bibliographic Info

Article provided by De Gruyter in its journal The B.E. Journal of Economic Analysis & Policy.

Volume (Year): 12 (2012)
Issue (Month): 1 (November)
Pages: 1-26

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Handle: RePEc:bpj:bejeap:v:12:y:2012:i:1:n:51

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  1. Paul Missios & Ida Ferrara, 2010. "Pricing of Drugs with Heterogeneous Health Insurance Coverage," Working Papers 026, Ryerson University, Department of Economics.
  2. Ferrara, Ida & Kong, Ying, 2008. "Can health insurance coverage explain the generic competition paradox?," Economics Letters, Elsevier, vol. 101(1), pages 48-52, October.
  3. Perloff, Jeffrey M. & Suslow, Valerie Y. & Seguin, Paul J., 1996. "Higher Prices from Entry: Pricing of Brand-Name Drugs," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt1sh175fc, Department of Agricultural & Resource Economics, UC Berkeley.
  4. F. M. Scherer, 1993. "Pricing, Profits, and Technological Progress in the Pharmaceutical Industry," Journal of Economic Perspectives, American Economic Association, vol. 7(3), pages 97-115, Summer.
  5. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
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