Document Type
Discussion Paper
Publication Date
1-1-2019
CFDP Number
2164R4
CFDP Revision Date
10-1-2021
CFDP Pages
63
Journal of Economic Literature (JEL) Code(s)
C72, D44, D82, D83
Abstract
We describe a methodology for making counterfactual predictions in settings where the information held by strategic agents and the distribution of payoff-relevant states of the world are unknown. The analyst observes behavior assumed to be rationalized by a Bayesian model, in which agents maximize expected utility, given partial and differential information about the state. A counterfactual prediction is desired about behavior in another strategic setting, under the hypothesis that the distribution of the state 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, the counterfactual prediction is described by finitely many linear inequalities, even though the latent parameter, the information structure, is infinite dimensional.
Recommended Citation
Bergemann, Dirk; Brooks, Benjamin; and Morris, Stephen, "Counterfactuals with Latent Information" (2019). Cowles Foundation Discussion Papers. 2646.
https://elischolar.library.yale.edu/cowles-discussion-paper-series/2646