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Estimating nonparametric mixed Logit Models via EM algorithm

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  • Daniele Pacifico

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Abstract

The aim of this paper is to describe a Stata routine for the nonparametric estimation of mixed logit models with an Expectation-Maximisation algorithm proposed in Train (2008). We also show how to use the Stata command lclogit, which performs the estimation automaticall

Suggested Citation

  • Daniele Pacifico, 2011. "Estimating nonparametric mixed Logit Models via EM algorithm," Department of Economics 0663, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
  • Handle: RePEc:mod:depeco:0663
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    File URL: http://www.dep.unimore.it/materiali_discussione/0663.pdf
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    References listed on IDEAS

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    1. Joel Huber and Kenneth Train., 2000. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Economics Working Papers E00-289, University of California at Berkeley.
    2. Marina Murat & Barbara Pistoresi, 2009. "Emigrant and immigrant networks in FDI," Applied Economics Letters, Taylor & Francis Journals, vol. 16(12), pages 1261-1264.
    3. Giuseppe Marotta, 1997. "Does trade credit redistribution thwart monetary policy? Evidence from Italy," Applied Economics, Taylor & Francis Journals, vol. 29(12), pages 1619-1629.
    4. 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.
    5. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    6. Emanuele Ciani & Donatella Fresu, 2011. "From SHIW to IT-SILC: construction and representativeness of the new CAPP_DYN first-year population," Center for the Analysis of Public Policies (CAPP) 0092, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    7. Arne Risa Hole, 2007. "Fitting mixed logit models by using maximum simulated likelihood," Stata Journal, StataCorp LP, vol. 7(3), pages 388-401, September.
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    Citations

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    Cited by:

    1. Daniele Pacifico & Hong il Yoo, 2012. "A Stata module for estimating latent class conditional logit models via the Expectation-Maximization algorithm," Discussion Papers 2012-49, School of Economics, The University of New South Wales.
    2. Daniele Pacifico, 2013. "On the role of unobserved preference heterogeneity in discrete choice models of labour supply," Empirical Economics, Springer, vol. 45(2), pages 929-963, October.
    3. Kabatek, J., 2013. "Iteration Capping For Discrete Choice Models Using the EM Algorithm," Discussion Paper 2013-019, Tilburg University, Center for Economic Research.
    4. Paola Bertolini & Enrico Giovanetti & Francesco Pagliacci, 2011. "Regional Patterns in the Achievement of the Lisbon Strategy: a Comparison Between Polycentric Regions and Monocentric Ones," Department of Economics 0664, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    5. Daniele Pacifico, 2014. "On the role of unobserved preference Heterogeneity in discrete choice Models of labour supply," Working Papers 6, Department of the Treasury, Ministry of the Economy and of Finance.
    6. Sitienei, Isaac & Gillespie, Jeffrey & Harrison, Robert & Scaglia, Guillermo, 2015. "Estimating Desirable Cattle Traits Using Latent Class and Mixed Logit Models: A Choice Modeling Application to the U.S. Grass-Fed Beef Industry," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196706, Southern Agricultural Economics Association.

    More about this item

    Keywords

    st0001; lclogit; latent classes; EM algorithm; mixed logit;

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