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Probability Feedback in a Recursive System of Probability Models

Vuong, Quang H. (1982) Probability Feedback in a Recursive System of Probability Models. Social Science Working Paper, 443. California Institute of Technology , Pasadena, CA. (Unpublished) http://resolver.caltech.edu/CaltechAUTHORS:20171002-134801734

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Abstract

This paper presents a general model for qualitative endogenous variables that is defined by a recursive system of conditional probability models in which the probabilities of some outcomes may depend on the probabilities of posterior outcomes. The model is related to, but conceptually different from C. D. Mallar's (1977) simultaneous probability model. It has as special cases the multivariate logit model (M. Nerlove and S. J. Press (1973, 1976)) and the constrained nested logit model (D. McFadden (1981)). The model can also be used to analyze outcomes of some game situations. Two examples are in particular considered: a game against Nature and a Stackelberg game under uncertainty. Identification of the structural parameters in the first example is seen to be related to the classical problem of stochastic revealed preference as studied by M. K. Richter and L. Shapiro (1978).


Item Type:Report or Paper (Working Paper)
Additional Information:I wish to thank David Grether; our conversations prompted much of the structure of the present model. I am also deeply indebted to Kim Border, Ed Green, John Link, and Marc Nerlove for helpful comments and suggestions.
Group:Social Science Working Papers
Record Number:CaltechAUTHORS:20171002-134801734
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20171002-134801734
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:81956
Collection:CaltechAUTHORS
Deposited By: Jacquelyn Bussone
Deposited On:04 Oct 2017 19:44
Last Modified:04 Oct 2017 19:44

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