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

• 成果类型: Article
• 署名作者: Ganglmair, Bernhard; Simcoe, Timothy; Tarantino, Emanuele
• 署名单位: University of Mannheim; Leibniz Association; Zentrum fur Europaische Wirtschaftsforschung (ZEW); Boston University; National Bureau of Economic Research; Luiss Guido Carli University
• 刊物名称: AMERICAN ECONOMIC JOURNAL-MICROECONOMICS
• ISSN/ISSBN: 1945-7669
• DOI: 10.1257/mic.20190321
• 发表日期: 2025
• 页码: 164-190
• 关键词: Strategic experimentation; patent citations; INNOVATION; COORDINATION; uncertainty; spillovers; committees; DYNAMICS; industry; prizes

摘要

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. (JEL D83, L86, O31, O38)