arXiv 17 Mar 2024 · Theoretical Economics
arXiv:2403.11333 · PDF · DOI · OpenAlex · Extracted main text
To what extent can an external observer observing an equilibrium action distribution in an incomplete information game infer the underlying information structure? We investigate this issue in a general linear-quadratic-Gaussian framework. A simple class of canonical information structures is offered and proves rich enough to rationalize any possible equilibrium action distribution that can arise under an arbitrary information structure. We show that the class is parsimonious in the sense that the relevant parameters can be uniquely pinned down by an observed equilibrium outcome, up to some qualifications. Our result implies, for example, that the accuracy of each agent's signal about the state is identified, as measured by how much observing the signal reduces the state variance. Moreover, we show that a canonical information structure characterizes the lower bound on the amount by which each agent's signal can reduce the state variance, across all observationally equivalent information structures. The lower bound is tight, for example, when the actual information structure is uni-dimensional, or when there are no strategic interactions among agents, but in general, there is a gap since agents' strategic motives confound their private information about fundamental and strategic uncertainty.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | D. Bergemann and S. Morris (2013) Robust Predictions in Games with Incomplete Information | 1.000 | 10 | 4 | 100% |
| 2 | D. Bergemann, T. Heumann, and S. Morris (2015) Information and Volatility | 1.000 | 5 | 3 | 100% |
| 3 | G.-M. Angeletos and A. Pavan (2007) Efficient Use of Information and Social Value of Information | 0.928 | 4 | 4 | 100% |
| 4 | M. Miyashita and T. Ui (2024) On the Pettis Integral Approach to Large Population Games | 0.843 | 4 | 4 | 75% |
| 5 | D. Bergemann, T. Heumann, and S. Morris (2017) Information and Interaction | 0.843 | 3 | 3 | 100% |
| 6 | N. S. Lambert, M. Ostrovsky, and M. Panov (2018) Strategic Trading in Informationally Complex Environments | 0.737 | 3 | 2 | 100% |
| 7 | R. Radner (1962) Team Decision Problems | 0.737 | 3 | 2 | 100% |
| 8 | I. Arieli and M. Mueller-Frank (2017) Inferring Beliefs from Actions | 0.644 | 2 | 2 | 100% |
| 9 | D. Bergemann and S. Morris (2016) Bayes Correlated Equilibrium and the Comparison of Information Structures in Games | 0.644 | 2 | 2 | 100% |
| 10 | N. S. Lambert, G. Martini, and M. Ostrovsky (2018) Quadratic Games | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 54 scored citations.