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

Using data from the Internet Engineering Task Force, a vol- untary organization that develops protocols for managing Inter- net 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.

Ganglmair, Bernhard, Timothy Simcoe and Emanuele Tarantino (2025), Learning When to Quit: An Empirical Model of Experimentation in Standards Development, American Economic Journal: Microeconomics 17(3) , 164-90