Estimation of Multinomial Logit Models with Unobserved Heterogeneity Using Maximum Simulated Likelihood
In this paper we suggest a Stata routine for multinomial logit models with unobserved heterogeneity using maximum simulated likelihood based on Halton sequences. The purpose of this paper is twofold: First, we provide a description of the technical implementation of the estimation routine and discuss its properties. Further, we compare our estimation routine to the Stata program gllamm which solves integration using Gauss Hermite quadrature or Bayesian adaptive quadrature. For the analysis we draw on multilevel data about schooling. Our empirical findings show that the estimation techniques lead to approximately the same estimation results. The advantage of simulation over Gauss Hermite quadrature is a marked reduction in computational time for integrals with higher dimensions. Bayesian quadrature, however, leads to very stable results with only a few quadrature points, thus the computational advantage of Halton based simulation vanishes in our example with one and two dimensional integrals.
|Date of creation:||2006|
|Date of revision:|
|Contact details of provider:|| Postal: Mohrenstraße 58, D-10117 Berlin|
Web page: http://www.diw.de/en
More information through EDIRC
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.:
- Lorenzo Cappellari & Stephen P. Jenkins, 2003.
"Multivariate probit regression using simulated maximum likelihood,"
United Kingdom Stata Users' Group Meetings 2003
10, Stata Users Group.
- Lorenzo Cappellari & Stephen P. Jenkins, 2003. "Multivariate probit regression using simulated maximum likelihood," Stata Journal, StataCorp LP, vol. 3(3), pages 278-294, September.
- Train,Kenneth E., 2009.
"Discrete Choice Methods with Simulation,"
Cambridge University Press, number 9780521747387.
- Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
- Peter Haan, 2005. "State Dependence and Female Labor Supply in Germany: The Extensive and the Intensive Margin," Discussion Papers of DIW Berlin 538, DIW Berlin, German Institute for Economic Research.
- William W. Gould & Jeffrey Pitblado & Brian Poi, 2010. "Maximum Likelihood Estimation with Stata," Stata Press books, StataCorp LP, edition 4, number ml4.
- Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2002. "Reliable estimation of generalized linear mixed models using adaptive quadrature," Stata Journal, StataCorp LP, vol. 2(1), pages 1-21, February.
- Kenneth Train, 2001.
"Halton Sequences for Mixed Logit,"
- Train, Kenneth, 2000. "Halton Sequences for Mixed Logit," Department of Economics, Working Paper Series qt6zs694tp, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
- Kenneth Train ., 2000. "Halton Sequences for Mixed Logit," Economics Working Papers E00-278, University of California at Berkeley.
- Sophia Rabe-Hesketh & Anders Skrondal, 2012. "Multilevel and Longitudinal Modeling Using Stata, 3rd Edition," Stata Press books, StataCorp LP, edition 3, number mimus2.
- repec:tsj:spbook:mimus is not listed on IDEAS
- Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053.
When requesting a correction, please mention this item's handle: RePEc:diw:diwwpp:dp573. 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: (Bibliothek)
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.