Spring Semester 2012
Instructor: Kenneth Train

Lecture Topics and Readings

Textbook for the course: Discrete Choice Methods with Simulation, 2nd edition

Topic Readings
January 23
Introduction &
Drawing from Densities
Textbook, Ch.1 and Sections 9.1-9.2
January 30
Properties of Discrete Choice Model; Logit
Start problem set 1
Textbook, Chs. 2 and 3

D. McFadden, "Conditional Logit Analysis of Qualitative Choice Behavior," in P. Zarembka (ed.), Frontiers of Econometrics, New York, NY, Academic Press, 1974

K. Train, "A Validation Test of a Disaggregate Mode Choice Model," Transportation Research, Vol. 12, pp. 167-174, 1978.

February 6
Numerical Maximization
Start problem set 2
Textbook, Ch. 8

P. Ruud, An Introduction to Classical Econometric Theory, New York, Oxford University Press, 2000, Chapter 16 and Section 14.7.

February 13
GEV/Nested Logit
Start problem set 3
Textbook, Ch. 4

D. McFadden, "Modeling the Choice of Residential Location," in A. Karlquist, et al. (eds.), Spatial Interaction Theory and Planning Models, Amsterdam, North-Holland Publishing Company, 1978.

K. Train, Qualitative Choice Analysis, Cambridge, MA, MIT Press, 1986, Ch. 8: Automobile Ownership and Use

K. Train, D. McFadden, and M. Ben-Akiva, "The Demand for Local Telephone Service: A Fully Discrete Model of Residential Calling Patterns and Service Choices," RAND Journal of Economics, Vol. 18, No. 1, pp. 109-123, 1987.

February 27
Mixed Logit
Start problem set 4
Textbook, Ch. 6

D. Revelt and K. Train, "Mixed Logit with Repeated Choices," Review of Economics and Statistics, Vol. LXXX, No. 4, pp. 647-657, 1998.

D. Brownstone and K. Train, "Forecasting New Product Penetration with Flexible Substitution Patterns," Journal of Econometrics, Vol. 89, No. 1-2, pp. 109-129, 1998/99.

D. McFadden and K. Train, "Mixed MNL Models of Discrete Response,"Journal of Applied Econometrics, Vol. 15, No. 5, pp. 447-470, 2000.

K. Train, "Recreation Demand Models with Taste Variation," Land Economics, Vol. 74, No. 2, pp. 230-239, 1998.

K. Train and M. Weeks, "Discrete Choice Models in Preference Space and Willingness-to-pay Space," in Applications of Simulation Methods in Environmental and Resource Economics, R. Scarpa and A Alberini, eds., Springer, Dordrecht, 2005.

J. Walker, M. Ben-Akiva, and D. Bolduc, "Identification of Parameters in Normal Error Component Logit Mixture (NECLM) Models," Journal of Applied Econometrics, Vol. 22, pp 1095-1025, 2007.

March 5
Individual-Level Coefficients
Textbook, Ch. 11

March 12
Start problem set 5
Textbook, Ch. 5

J. Hausman and D. Wise, "A Conditional Probit Model for Qualitative Choice: Discrete Decisions Recognizing Interdependence and Heterogenous Preferences," Econometrica, Vol. 48, No. 2, pp. 403-426, 1978.

S. Lerman and C. Manski, "On the Use of Simulated Frequencies to Approximate Choice Probabilities," in C. Manski and D. McFadden (eds.), Structural Analysis of Discrete Data with Econometric Applications, Cambridge, MA, MIT Press, 1981.

M. Ben-Akiva and D. Bolduc, "Multinomial Probit with a Logit Kernel and a General Parametric Specification of the Covariance Structure," working paper, 1996, Department d'Economique, Universite Laval, Quebec, Canada.

A. Boersch-Supan and V. Hajivassiliou, "Smooth Unbiased Multivariate Probability Simulators for Maximum Likelihood Estimation of Limited Dependent Variables," Journal of Econometrics, Vol. 58, pp. 347-368, 1993.

V. Hajivassiliou, D. McFadden, and P. Ruud, "Simulation of Multivariate Normal Rectangle Probabilities and Their Derivatives," Journal of Econometrics, Vol. 72, No. 1-2, pp. 85-134, 1996.

March 19
Variance Reduction and Simulation Assisted Classical Estimation: MSL, MSM, MSS
Textbook, Sect 9.3, Ch. 10

C. Bhat, "Quasi-Random Maxium Simulated Likelihood Estimation of the Mixed Multinomial Logit Model," Transportation Research, Part B, Vol. 35, pp. 677-693, 2001. Preprint version is viewable here, but not the published reprint.

K. Train, "Halton Sequences for Mixed Logit," working paper no. E00-278, Department of Economics, University of California, Berkeley, 2000.

C. Bhat, "Simulation Estimation of Discrete Choice Models Using Randomized and Scrambled Halton Sequences Transportation Research, Part B, Vol. 37, No. 9, pp. 837-855, 2003.

S. Hess, K. Train, and J. Polak, "On the Use of a Modified Latin Hypercube Sampling (MLHS) Method in the Estimation of a Mixed Logit Model for Vehicle Choice," Transportation Research, Part B, Vol. 40, No. 2, pp. 147-167, 2006.

Z. Sandor and K. Train, "Quasi-random Simulation of Discrete Choice Models," Transportation Research, Part B, Vol. 38, pp. 313-327, 2004.

D. McFadden, "Lectures on Simulation-Assisted Statistical Inference," presented at EC2 Conference, Florence, Italy, 1996.

D. McFadden, "A Method of Simulated Moments for Estimation of Discrete Choice Models without Numerical Integration," Econometrica, Vol. 57, No. 5, pp. 995-1026, 1989.

A. Pakes and D. Pollard,"Simulation and the Asymptotics of Optimization Estimators," Econometrica, Vol. 57, No. 5, pp. 1027-1057, 1989.

L.-F. Lee, "On the Efficiency of Methods of Simulated Moments and Simulated Likelihood Estimation of Discrete Response Models," Econometric Theory, Vol. 8, No. 4, pp. 518-552, 1992.

V. Hajivassiliou and D. McFadden, "The Method of Simulated Scores with Application to Models of External Debt Crises," Econometrica, Vol. 66, No. 4, pp. 863-896, 1998.

M. Keane, "A Computationally Practical Simulation Estimator for Panel Data,"Econometrica, Vol. 62, No. 1, pp. 95-116, 1994.

V. Hajivassiliou and P. Ruud, "Classical Estimation Methods for LDV Models using Simulation," in Handbook of Econometrics, R. Engle and D. McFadden (eds.), New York, NY, Elsevier Science, 1994.

April 2
Bayesian Estimation
Textbook, Sections 12.1-12.5

S. Chib and E. Greenberg, "Understanding the Metropolis-Hastings Algorithm," The American Statistician, Vol. 49, pp. 327-335, 1995. Reproduced with permission from The American Statistician. Copyright 1995 by the American Statistical Association. All rights reserved

April 9
Hierarchical Bayes Estimation of Mixed Logit
Start problem set 6
Textbook, Sections 12.6-12.7

Sawtooth Software, "The CBC/HB System for Hierarchical Bayes Estimation,".

J. Huber and K. Train, "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Marketing Letters, Vol. 12, No. 3, pp. 257-267, 2001.

J. Albert and S. Chib, "Bayesian Analysis of Binary and Polychomotomous Response Data," Journal of the American Statistical Association, Vol. 88, No. 422, pp.669-679, 1993.

R. McCulloch and P. Rossi, "An Exact Likelihood Analysis of the Multinomial Probit Model," Journal of Econometrics, Vol. 64, No. 1-2, pp. 207-240, 1994.

G. Allenby and P. Rossi, "Marketing Models of Consumer Heterogeneity," Journal of Econometrics, Vol. 89, No. 1-2, pp. 57-78, 1998/99.

April 16
Endogeneity: BLP, Control functions, Latent instruments
Textbook, Ch. 13

S. Berry, "Estimating Discrete Choice Models of Product Differentiation," The Rand Journal of Economics, Vol. 25, No. 2, pp. 242-262, 1994.

S. Berry, A. Pakes, and J. Levinsohn, "Automobile Prices in Equilibrium," Econometrica,Vol. 63, No. 4, pp. 841-890, 1995.

S. Berry, A. Pakes, and J. Levinsohn, "Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Vehicle Market," Journal of Political Economy, Vol. 112, No. 1, pp. 68-105, 2004.

K. Train and C. Winston, "Vehicle Choice Behavior and the Declining Market of US Automakers," Internatinal Economic Review, Vol. 48, No. 4, pp. 1469-1496, 2007

A. Petrin and K. Train, "A Control Function Approach to Endogeneity in Consumer Choice Models," Journal of Marketing Research,Vol. 47, No. 1, pp. 3-13, 2010.

S. Park and S. Gupta, "A Simulated Maximum Likelihood Estimator for the Random Coefficient Logit Model Using Aggregate Data," Journal of Marketing Research,Vol. 46, No. 4, pp. 531-42, 2009.

April 23
EM algorithms
Textbook, Ch. 14

K. Train, , EM Algorithms for Nonparametric Estimation of Mixing Distributions," Journal of Choice Modeling, Vol.1, No. 1, pp 40-69.

K. Train, A Recursive Estimator for Random Coefficient Models, working paper.