Arbeitspapier

An instrumental variable model of multiple discrete choice

This paper studies identification of latent utility functions in multiple discrete choice models in which there may be endogenous explanatory variables, that is explanatory variables that are not restricted to be distributed independently of the unobserved determinants of latent utilities. The model does not employ large support, special regressor or control function restrictions, indeed it is silent about the process delivering values of endogenous explanatory variables and in this respect it is incomplete. Instead the model employs instrumental variable restrictions requiring the existence of instrumental variables which are excluded from latent utilities and distributed independently of the unobserved components of utilities. We show that the model delivers set identification of the latent utility functions and we characterize sharp bounds on those functions. We develop easy-to-compute outer regions which in parametric models require little more calculation than what is involved in a conventional maximum likelihood analysis. The results are illustrated using a model which is essentially the parametric conditional logit model of McFadden (1974) but with potentially endogenous explanatory variables and instrumental variable restrictions. The method employed has wide applicability and for the first time brings instrumental variable methods to bear on structural models in which there are multiple unobservables in a structural equation.

Language
Englisch

Bibliographic citation
Series: cemmap working paper ; No. CWP39/11

Classification
Wirtschaft
Subject
partial identification
random sets
multiple discrete choice
endogeneity
instrumental variables
incomplete models

Event
Geistige Schöpfung
(who)
Chesher, Andrew
Rosen, Adam
Smolinski, Konrad
Event
Veröffentlichung
(who)
Centre for Microdata Methods and Practice (cemmap)
(where)
London
(when)
2011

DOI
doi:10.1920/wp.cem.2011.3911
Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Chesher, Andrew
  • Rosen, Adam
  • Smolinski, Konrad
  • Centre for Microdata Methods and Practice (cemmap)

Time of origin

  • 2011

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