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Learning When to Quit: An Empirical Model of Experimentation in Standards Development

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  • Bernhard Ganglmair
  • Timothy Simcoe
  • Emanuele Tarantino

Abstract

Using data from the Internet Engineering Task Force (IETF), a voluntary organization that develops protocols for managing internet infrastructure, we estimate a dynamic discrete choice model of the decision to continue or abandon a line of research. The model's key parameters measure the speed at which authors learn whether their project will become a technology standard. We use the model to simulate two innovation policies: an R&D subsidy and a publication prize. While subsidies have a larger impact on research output, the optimal policy depends on the level of R&D spillovers.

Suggested Citation

  • Bernhard Ganglmair & Timothy Simcoe & Emanuele Tarantino, 2025. "Learning When to Quit: An Empirical Model of Experimentation in Standards Development," American Economic Journal: Microeconomics, American Economic Association, vol. 17(3), pages 164-190, August.
    • Handle: RePEc:aea:aejmic:v:17:y:2025:i:3:p:164-90
    DOI: 10.1257/mic.20190321
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    References listed on IDEAS

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    1. Timothy Simcoe, 2012. "Standard Setting Committees: Consensus Governance for Shared Technology Platforms," American Economic Review, American Economic Association, vol. 102(1), pages 305-336, February.
    2. Michael Roach & Wesley M. Cohen, 2013. "Lens or Prism? Patent Citations as a Measure of Knowledge Flows from Public Research," Management Science, INFORMS, vol. 59(2), pages 504-525, October.
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    Cited by:

    1. Alessandra Allocca, 2023. "“No Man is an Island”: An Empirical Study on Team Formation and Performance," Rationality and Competition Discussion Paper Series 389, CRC TRR 190 Rationality and Competition.
    2. Baron, Justus, 2020. "Counting standard contributions to measure the value of patent portfolios - A tale of apples and oranges," Telecommunications Policy, Elsevier, vol. 44(3).
    3. Baron, Justus & Kanevskaia, Olia, 2023. "Wearing multiple hats—The role of working group chairs’ affiliation in standards development," Research Policy, Elsevier, vol. 52(9).

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    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

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