The random coefficients logit model is identified
The random coefficients multinomial choice logit model, also known as the mixed logit, has been widely used in empirical choice analysis for the last thirty years. We prove that the distribution of random coefficients in the multinomial logit model is nonparametrically identified. Our approach requires variation in product characteristics only locally and does not rely on the special regressors with large supports used in related papers. One of our two identification arguments is constructive. Both approaches may be applied to other choice models with random coefficients.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Magnac, Thierry & Maurin, Eric, 2003.
"Identification and Information in Monotone Binary Models,"
IDEI Working Papers
180, Institut d'Économie Industrielle (IDEI), Toulouse, revised Oct 2004.
- Magnac, Thierry & Maurin, Eric, 2007. "Identification and information in monotone binary models," Journal of Econometrics, Elsevier, vol. 139(1), pages 76-104, July.
- Thierry Magnac & Eric Maurin, 2007. "Identification and Information in Monotone Binary Models," Post-Print halshs-00754218, HAL.
- Ichimura, H. & Thompson, S., 1993.
"Maximum Likelihood Estimation of a Binary Choice Model with Random Coefficients of Unknown Distributions,"
268, Minnesota - Center for Economic Research.
- Ichimura, Hidehiko & Thompson, T. Scott, 1998. "Maximum likelihood estimation of a binary choice model with random coefficients of unknown distribution," Journal of Econometrics, Elsevier, vol. 86(2), pages 269-295, June.
- Arthur Lewbel, 1999.
"Semiparametric Qualitative Response Model Estimation with Unknown Heteroskedasticity or Instrumental Variables,"
Boston College Working Papers in Economics
454, Boston College Department of Economics.
- Lewbel, Arthur, 2000. "Semiparametric qualitative response model estimation with unknown heteroscedasticity or instrumental variables," Journal of Econometrics, Elsevier, vol. 97(1), pages 145-177, July.
- Eric Gautier & Yuichi Kitamura, 2008.
"Nonparametric Estimation in Random Coefficients Binary Choice Models,"
2008-15, Centre de Recherche en Economie et Statistique.
- Eric Gautier & Yuichi Kitamura, 2013. "Nonparametric Estimation in Random Coefficients Binary Choice Models," Econometrica, Econometric Society, vol. 81(2), pages 581-607, 03.
- Eric Gautier & Yuichi Kitamura, 2009. "Nonparametric Estimation in Random Coefficients Binary Choice Models," Cowles Foundation Discussion Papers 1721, Cowles Foundation for Research in Economics, Yale University.
- Eric Gautier & Yuichi Kitamura, 2011. "Nonparametric estimation in random coefficients binary choice models," Working Papers hal-00403939, HAL.
- Stinchcombe, Maxwell B. & White, Halbert, 1998. "Consistent Specification Testing With Nuisance Parameters Present Only Under The Alternative," Econometric Theory, Cambridge University Press, vol. 14(03), pages 295-325, June.
- Shakeeb Khan & Elie Tamer, 2010. "Irregular Identification, Support Conditions, and Inverse Weight Estimation," Econometrica, Econometric Society, vol. 78(6), pages 2021-2042, November.
- Briesch, Richard A. & Chintagunta, Pradeep K. & Matzkin, Rosa L., 2010. "Nonparametric Discrete Choice Models With Unobserved Heterogeneity," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 291-307.
- Jeremy T. Fox & Amit Gandhi, 2009. "Identifying Heterogeneity in Economic Choice Models," NBER Working Papers 15147, National Bureau of Economic Research, Inc.
- Fox, Jeremy T. & Kim, Kyoo il & Yang, Chenyu, 2016.
"A simple nonparametric approach to estimating the distribution of random coefficients in structural models,"
Journal of Econometrics,
Elsevier, vol. 195(2), pages 236-254.
- Jeremy T. Fox & Kyoo il Kim, 2011. "A Simple Nonparametric Approach to Estimating the Distribution of Random Coefficients in Structural Models," NBER Working Papers 17283, National Bureau of Economic Research, Inc.
- Patrick Bajari & Jeremy T. Fox & Kyoo il Kim & Stephen P. Ryan, 2009. "A Simple Nonparametric Estimator for the Distribution of Random Coefficients," NBER Working Papers 15210, National Bureau of Economic Research, Inc.
- Amit Gandhi & Jeremy T. Fox, 2009. "Identifying Heterogeneity in Economic Choice and Selection Models Using Mixtures," 2009 Meeting Papers 165, Society for Economic Dynamics.
- Donald W. K. Andrews & Marcia M. A. Schafgans, 1998. "Semiparametric Estimation of the Intercept of a Sample Selection Model," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 497-517.
- Steven T. Berry & Philip A. Haile, 2009.
"Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers,"
Cowles Foundation Discussion Papers
1718, Cowles Foundation for Research in Economics, Yale University, revised Mar 2010.
- Steven T. Berry & Philip A. Haile, 2009. "Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers," NBER Working Papers 15276, National Bureau of Economic Research, Inc.
- Hausman, Jerry A & Wise, David A, 1978.
"A Conditional Probit Model for Qualitative Choice: Discrete Decisions Recognizing Interdependence and Heterogeneous Preferences,"
Econometric Society, vol. 46(2), pages 403-426, March.
- J. A. Hausman & D. A. Wise, 1976. "A Conditional Profit Model for Qualitative Choice: Discrete Decisions Recognizing Interdependence and Heterogeneous Preferences," Working papers 173, Massachusetts Institute of Technology (MIT), Department of Economics.
- repec:cdl:compol:217 is not listed on IDEAS
- Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
- Heckman, James J & Willis, Robert J, 1977.
"A Beta-logistic Model for the Analysis of Sequential Labor Force Participation by Married Women,"
Journal of Political Economy,
University of Chicago Press, vol. 85(1), pages 27-58, February.
- James J. Heckman & Robert J. Willis, 1975. "A Beta-Logistic Model for the Analysis of Sequential Labor Force Participation by Married Women," NBER Working Papers 0112, National Bureau of Economic Research, Inc.
- Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
When requesting a correction, please mention this item's handle: RePEc:eee:econom:v:166:y:2012:i:2:p:204-212. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.