Document Type
Discussion Paper
Publication Date
1-1-2019
CFDP Number
2162R
CFDP Revision Date
February 1, 2019
CFDP Pages
33
Journal of Economic Literature (JEL) Code(s)
C72, D44, D82, D83
Abstract
We describe a methodology for making counterfactual predictions when the information held by strategic agents is a latent parameter. The analyst observes behavior which is rationalized by a Bayesian model in which agents maximize expected utility, given partial and differential information about payoff-relevant states of the world. A counterfactual prediction is desired about behavior in another strategic setting, under the hypothesis that the distribution of and agents’ information about the state are held fixed. When the data and the desired counterfactual prediction pertain to environments with finitely many states, players, and actions, there is a finite dimensional description of the sharp counterfactual prediction, even though the latent parameter, the type space, is infinite dimensional.
Recommended Citation
Bergemann, Dirk; Brooks, Benjamin; and Morris, Stephen, "Counterfactuals with Latent Information" (2019). Cowles Foundation Discussion Papers. 99.
https://elischolar.library.yale.edu/cowles-discussion-paper-series/99