NDLI: Covariance, identification, and finite-sample performance of the MSL and Bayes estimators of a logit model with latent attributes

Content Provider	Springer Nature Link
Author	Dazia, Ricardo A. Bolduc, Denis
Copyright Year	2012
Abstract	In this paper we discuss the specification, covariance structure, estimation, identification, and point-estimate analysis of a logit model with endogenous latent attributes that avoids problems of inconsistency. We show first that the total error term induced by the stochastic latent attributes is heteroskedastic and nonindependent. In addition, we show that the exact identification conditions support the two-stage analysis found in much current work. Second, we set up a Monte Carlo experiment where we compare the finite-sample performance of the point estimates of two alternative methods of estimation, namely frequentist full information maximum simulated likelihood and Bayesian Metropolis Hastings-within-Gibbs sampling. The Monte Carlo study represents a virtual case of travel mode choice. Even though the two estimation methods we analyze are based on different philosophies, both the frequentist and Bayesian methods provide estimators that are asymptotically equivalent. Our results show that both estimators are feasible and offer comparable results with a large enough sample size. However, the Bayesian point estimates outperform maximum likelihood in terms of accuracy, statistical significance, and efficiency when the sample size is low.
Starting Page	647
Ending Page	670
Page Count	24
File Format	PDF
ISSN	00494488
Journal	Transportation
Volume Number	40
Issue Number	3
e-ISSN	15729435
Language	English
Publisher	Springer US
Publisher Date	2012-07-14
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Discrete choice Bayesian econometrics Latent attributes Regional/Spatial Science Economic Geography Engineering Economics, Organization, Logistics, Marketing Innovation/Technology Management
Content Type	Text
Resource Type	Article
Subject	Development Transportation Civil and Structural Engineering

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