Economics at your fingertips  

Mixed MNL models for discrete response

Daniel McFadden and Kenneth Train ()

Journal of Applied Econometrics, 2000, vol. 15, issue 5, 447-470

Abstract: This paper considers mixed, or random coefficients, multinomial logit (MMNL) models for discrete response, and establishes the following results. Under mild regularity conditions, any discrete choice model derived from random utility maximization has choice probabilities that can be approximated as closely as one pleases by a MMNL model. Practical estimation of a parametric mixing family can be carried out by Maximum Simulated Likelihood Estimation or Method of Simulated Moments, and easily computed instruments are provided that make the latter procedure fairly efficient. The adequacy of a mixing specification can be tested simply as an omitted variable test with appropriately defined artificial variables. An application to a problem of demand for alternative vehicles shows that MMNL provides a flexible and computationally practical approach to discrete response analysis. Copyright © 2000 John Wiley & Sons, Ltd.

Date: 2000
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1005) Track citations by RSS feed

Downloads: (external link) Supporting data files and programs (text/html)

Related works:
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
http://www3.intersci ... e.jsp?issn=0883-7252

Access Statistics for this article

Journal of Applied Econometrics is currently edited by M. Hashem Pesaran

More articles in Journal of Applied Econometrics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing ().

Page updated 2019-03-31
Handle: RePEc:jae:japmet:v:15:y:2000:i:5:p:447-470