Economics at your fingertips  

Alternative Computational Approaches to Inference in the Multinomial Probit Model

John Geweke, Michael Keane () and David Runkle

The Review of Economics and Statistics, 1994, vol. 76, issue 4, 609-32

Abstract: This research compares several approaches to inference in the multinominal profit model, based on two Monte Carlo experiments for a seven choice model. The methods compared are the simulated maximum likelihood estimator using the GHK recursive probability simulator, the method of simulated moments estimator using the GHK recursive simulator and kernel-smoothed frequency simulators, and posterior means using a Gibbs sampling-data augmentation algorithm. Overall, the Gibbs sampling algorithm has a slight edge, with the relative performance of MSM and SML based on the GHK simulator being difficult to evaluate. The MSM estimator with the kernel-smoothed frequency simulator is clearly inferior. Copyright 1994 by MIT Press.

Date: 1994
References: Add references at CitEc
Citations: View citations in EconPapers (114) Track citations by RSS feed

Downloads: (external link) ... 0.CO%3B2-X&origin=bc full text (application/pdf)
Access to full text is restricted to JSTOR subscribers. See for details.

Related works:
Working Paper: Alternative computational approaches to inference in the multinomial probit model (1994) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from
https://mitpressjour ... rnal/?issn=0034-6535

Access Statistics for this article

The Review of Economics and Statistics is currently edited by Amitabh Chandra, Olivier Coibion, Bryan S. Graham, Shachar Kariv, Amit K. Khandelwal, Asim Ijaz Khwaja, Brigitte C. Madrian and Rohini Pande

More articles in The Review of Economics and Statistics from MIT Press
Bibliographic data for series maintained by Ann Olson ().

Page updated 2019-09-16
Handle: RePEc:tpr:restat:v:76:y:1994:i:4:p:609-32