Symmetry of evidence without evidence of symmetry

The de Finetti Theorem is a cornerstone of the Bayesian approach. Bernardo (1996) writes that its "message is very clear: if a sequence of observations is judged to be exchangeable, then any subset of them must be regarded as a random sample from some model, and there exists a prior distribution on the parameter of such model, hence requiring a Bayesian approach." We argue that while exchangeability, interpreted as symmetry of evidence, is a weak assumption, when combined with subjective expected utility theory, it implies also complete confidence that experiments are identical. When evidence is sparse, and there is little evidence of symmetry, this implication of de Finetti's hypotheses is not intuitive. This motivates our adoption of multiple-priors utility as the benchmark model of preference. We provide two alternative generalizations of the de Finetti Theorem for this framework. A model of updating is also provided.Ambiguity, exchangeability, symmetry, updating, learning, multiple-priors

Coarse contingencies and ambiguity

The paper considers an agent who must choose an action today under uncertainty about the consequence of any chosen action but without having in mind a complete list of all the contingencies that could influence outcomes. She conceives of some relevant (subjective) contingencies but she is aware that these contingencies are coarse---they leave out some details that may affect outcomes. Though she may not be able to describe these finer details, she is aware that they exist and this may affect her behavior.Uncertainty, states of the world, ambiguity, coarse contingencies

Coarse Contingencies

The paper considers an agent who must choose an action today under uncertainty about the consequence of any chosen action but without having in mind a complete list of all the contingencies that could influence outcomes. She conceives of some relevant (subjective) contingencies but she is aware that these contingencies are coarse - they leave out some details that may affect outcomes. Though she may not be able to describe these finer details, she is aware that they exist and this may affect her behavior.Unforeseen Contingencies, Ambiguity, Menu Choices

Robust confidence regions for incomplete models

Call an economic model incomplete if it does not generate a probabilistic prediction even given knowledge of all parameter values. We propose a method of inference about unknown parameters for such models that is robust to heterogeneity and dependence of unknown form. The key is a Central Limit Theorem for belief functions; robust con.dence regions are then constructed in a fashion paralleling the classical approach. Monte Carlo simulations support tractability of the method and demonstrate its enhanced robustness relative to existing methods

Symmetry of evidence without evidence of symmetry

[This item is a preserved copy. To view the original, visit http://econtheory.org/] The de Finetti Theorem is a cornerstone of the Bayesian approach. Bernardo (1996) writes that its "message is very clear: if a sequence of observations is judged to be exchangeable, then any subset of them must be regarded as a random sample from some model, and there exists a prior distribution on the parameter of such model, hence requiring a Bayesian approach." We argue that while exchangeability, interpreted as symmetry of evidence, is a weak assumption, when combined with subjective expected utility theory, it implies also complete confidence that experiments are identical. When evidence is sparse, and there is little evidence of symmetry, this implication of de Finetti's hypotheses is not intuitive. This motivates our adoption of multiple-priors utility as the benchmark model of preference. We provide two alternative generalizations of the de Finetti Theorem for this framework. A model of updating is also provided

Bundling, information aggregation and entry deterrence

This paper provides an explanation for bundling based on its information aggregation effect. Using bundling, the monopolist can hide the information of each monopoly market by aggregating information. We show that the monopolist chooses bundling in an early period because bundling removes potential competition in the following period.Bundling Entry deterrence Information aggregation Information asymmetry

Subjective states: a more robust model

Following Kreps [11], Nehring [15, 16] and Dekel, Lipman and Rustichini [5], we study the demand for ‡exibility and what it reveals about subjective uncertainty. As in the cited papers, the latter is represented by a subjective state space consisting of possible future preferences over actions to be chosen ex post. One contribution is to provide axiomatic foundations for a range of alternative hypotheses about the nature of these ex post preferences. Secondly, we establish a sense in which the subjective state space is uniquely pinned down by the agent’s ex ante ranking of (random) menus. For both purposes, we show that it is advantageous to assume that the agent ranks random menus, and to think of ex post upper contour sets rather than ex post preferences. Finally, we demonstrate the tractability of our representation by showing that it can model the two comparative notions “2 desires more ‡exibility than 1”and “2 is more averse to ‡exibility-risk than is 1.

De Finetti Meets Ellsberg

The paper outlines an exchangeable non-Bayesian model of preference generalizing the Savage/de Finetti classic model of subjective expected utility preference with an exchangeable prior. The treatment is informal, and the emphasis is on motivation and potential applications rather than on axiomatic foundations and technical details. The objective is to provide a widely accessible introduction to research that is reported in detail elsewhere