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Harmonizing regulatory market approval of products with high safety requirements: Evidence from the European pharmaceutical market

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  • Fabian Grünwald
  • Tom Stargardt

Abstract

We causally analyzed whether being a member of the European Union (EU) and having access to a centralized marketing authorization procedure (centralized procedure [CP]) affects availability and time to launch of new pharmaceuticals. We employed multiple difference‐in‐differences models, exploiting the eastern enlargement of the EU as well as changes in the indications that fall within the compulsory or voluntary scope of the CP. Results showed that countries experienced a mean decrease in launch delay of 10.9 months (p = 0.004) after joining the EU. Effects were higher among pharmaceuticals that belong to indications that might voluntarily participate in the CP but are not obliged to. These are often financially less attractive to manufacturers than pharmaceuticals within the compulsory scope. Availability of new pharmaceuticals launched remained unaffected. We found signs that the magnitude of the country‐specific effect of centralized marketing authorization on launch delay may be influenced by strategic decisions of manufacturers at the national level (e.g., parallel trade or reference pricing).

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  • Fabian Grünwald & Tom Stargardt, 2024. "Harmonizing regulatory market approval of products with high safety requirements: Evidence from the European pharmaceutical market," Health Economics, John Wiley & Sons, Ltd., vol. 33(7), pages 1546-1564, July.
  • Handle: RePEc:wly:hlthec:v:33:y:2024:i:7:p:1546-1564
    DOI: 10.1002/hec.4819
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    1. Ashesh Rambachan & Jonathan Roth, 2023. "A More Credible Approach to Parallel Trends," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(5), pages 2555-2591.
    2. Djogbenou, Antoine A. & MacKinnon, James G. & Nielsen, Morten Ørregaard, 2019. "Asymptotic theory and wild bootstrap inference with clustered errors," Journal of Econometrics, Elsevier, vol. 212(2), pages 393-412.
    3. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    4. Brekke, Kurt R. & Holmas, Tor Helge & Straume, Odd Rune, 2011. "Reference pricing, competition, and pharmaceutical expenditures: Theory and evidence from a natural experiment," Journal of Public Economics, Elsevier, vol. 95(7), pages 624-638.
    5. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    6. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    7. David Roodman & James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2019. "Fast and wild: Bootstrap inference in Stata using boottest," Stata Journal, StataCorp LP, vol. 19(1), pages 4-60, March.
    8. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    9. Brekke, Kurt R. & Holmås, Tor Helge & Straume, Odd Rune, 2015. "Price regulation and parallel imports of pharmaceuticals," Journal of Public Economics, Elsevier, vol. 129(C), pages 92-105.
    10. Davide Fiaschi & Andrea Mario Lavezzi & Angela Parenti, 2018. "Does EU cohesion policy work? Theory and evidence," Journal of Regional Science, Wiley Blackwell, vol. 58(2), pages 386-423, March.
    11. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    12. John Bachtler & Grzegorz Gorzelak, 2007. "Reforming Eu Cohesion Policy," Policy Studies, Taylor & Francis Journals, vol. 28(4), pages 309-326.
    13. Verniers, Isabel & Stremersch, Stefan & Croux, Christophe, 2011. "The global entry of new pharmaceuticals: A joint investigation of launch window and price," International Journal of Research in Marketing, Elsevier, vol. 28(4), pages 295-308.
    14. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    15. Margaret K. Kyle, 2019. "The Single Market in Pharmaceuticals," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 55(1), pages 111-135, August.
    16. Stern, Ariel Dora, 2017. "Innovation under regulatory uncertainty: Evidence from medical technology," Journal of Public Economics, Elsevier, vol. 145(C), pages 181-200.
    17. Baker, Andrew C. & Larcker, David F. & Wang, Charles C.Y., 2022. "How much should we trust staggered difference-in-differences estimates?," Journal of Financial Economics, Elsevier, vol. 144(2), pages 370-395.
    18. Chi Lau & Ka Fung & Lee Pugalis, 2014. "Is health care expenditure across Europe converging? Findings from the application of a nonlinear panel unit root test," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 4(2), pages 137-156, December.
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