Working Paper: CEPR ID: DP12805
Authors: Ran Spiegler
Abstract: I enrich the typology of players in the standard model of games with incomplete information, by allowing them to have incomplete "archival information" - namely, piecemeal knowledge of correlations among relevant variables. A player is characterized by the conventional Harsanyi type (a.k.a "news-information") as well as the novel "archive-information", formalized as a collection of subsets of variables. The player can only learn the marginal distributions over these subsets of variables. The player extrapolates a well-specified probabilistic belief according to the maximum-entropy criterion. This formalism expands our ability to capture strategic situations with "boundedly rational expectations." I demonstrate the expressive power and use of this formalism with some examples.
Keywords: non-rational expectations; archival information; maximum entropy; causal models; high-order beliefs
JEL Codes: C70; D01
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| archival information (L86) | players' beliefs about the distribution of outcomes (D80) |
| players' beliefs about the distribution of outcomes (D80) | actions in the game (C72) |
| archival information (L86) | subjective belief based on archival data (D80) |
| subjective belief based on archival data (D80) | conditioned belief through news information (D83) |
| players' beliefs about opponents' actions (C73) | strategic choices (L21) |