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Partial Identification Of Counterfactual Choice Probabilities

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Charles F. Manski

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Abstract

This article shows how to predict counterfactual discrete choice behavior when the presumed behavioral model partially identifies choice probabilities. The simple, general approach uses observable choice probabilities to partially infer the distribution of types in the population and then applies the results to predict behavior in unrealized choice settings. Two illustrative applications are given. One assumes only that persons have strict preferences. The other assumes strict preferences and utility functions that are linear in attribute bundles, with no restrictions on the shape of the distribution of preference parameters. Copyright 2007 by the Economics Department Of The University Of Pennsylvania And Osaka University Institute Of Social And Economic Research Association.

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File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1468-2354.2007.00467.x
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Article provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.

Volume (Year): 48 (2007)
Issue (Month): 4 (November)
Pages: 1393-1410
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Handle: RePEc:ier:iecrev:v:48:y:2007:i:4:p:1393-1410

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  1. Asher A. Blass & Saul Lach & Charles F. Manski, 2008. "Using Elicited Choice Probabilities to Estimate Random Utility Models: Preferences for Electricity Reliability," NBER Working Papers 14451, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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