Probability Feedback in a Recursive System of Probability Models
- Creators
- Vuong, Quang H.
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).
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.Attached Files
Submitted - sswp443.pdf
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Additional details
- Eprint ID
- 81956
- Resolver ID
- CaltechAUTHORS:20171002-134801734
- Created
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2017-10-04Created from EPrint's datestamp field
- Updated
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2019-10-03Created from EPrint's last_modified field
- Caltech groups
- Social Science Working Papers
- Series Name
- Social Science Working Paper
- Series Volume or Issue Number
- 443