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Discrete Choice Modeling for Transportation

  • Brownstone, David
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    This paper discusses important developments in discrete choice modeling for transportation applications. Since there have been a number of excellent recent surveys of the discrete choice literature aimed at transportation applications (see Bhat, 1997 and 2000a), this paper will concentrate on new developments and areas given less weight in recent surveys. Small and Winston (1999) give an excellent review of the transportation demand literature that includes many examples of how discrete choice models have been used in demand analysis.

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    Paper provided by University of California Transportation Center in its series University of California Transportation Center, Working Papers with number qt29v7d1pk.

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    Date of creation: 23 Jan 2001
    Date of revision:
    Handle: RePEc:cdl:uctcwp:qt29v7d1pk
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    1. Lee, Lung-Fei, 1992. "On Efficiency of Methods of Simulated Moments and Maximum Simulated Likelihood Estimation of Discrete Response Models," Econometric Theory, Cambridge University Press, vol. 8(04), pages 518-552, December.
    2. Calfee, John & Winston, Clifford, 1998. "The value of automobile travel time: implications for congestion policy," Journal of Public Economics, Elsevier, vol. 69(1), pages 83-102, July.
    3. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    4. Hajivassiliou, Vassilis & McFadden, Daniel & Ruud, Paul, 1996. "Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 85-134.
    5. Brownstone, David & Train, Kenneth, 1999. "Forecasting new product penetration with flexible substitution patterns," University of California Transportation Center, Working Papers qt1j6814b3, University of California Transportation Center.
    6. Donald W. K. Andrews, 1999. "Estimation When a Parameter Is on a Boundary," Econometrica, Econometric Society, vol. 67(6), pages 1341-1384, November.
    7. Lancaster, Tony, 1997. "Bayes WESML Posterior inference from choice-based samples," Journal of Econometrics, Elsevier, vol. 79(2), pages 291-303, August.
    8. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
    9. Small, Kenneth A, 1987. "A Discrete Choice Model for Ordered Alternatives," Econometrica, Econometric Society, vol. 55(2), pages 409-24, March.
    10. Koop, Gary & Poirier, Dale J., 1993. "Bayesian analysis of logit models using natural conjugate priors," Journal of Econometrics, Elsevier, vol. 56(3), pages 323-340, April.
    11. Bhat, Chandra R., 1998. "Accommodating variations in responsiveness to level-of-service measures in travel mode choice modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(7), pages 495-507, September.
    12. John F. Geweke & Michael P. Keane & David E. Runkle, 1994. "Statistical inference in the multinomial multiperiod probit model," Staff Report 177, Federal Reserve Bank of Minneapolis.
    13. Jeffrey M. Wooldridge, 1999. "Asymptotic Properties of Weighted M-Estimators for Variable Probability Samples," Econometrica, Econometric Society, vol. 67(6), pages 1385-1406, November.
    14. Imbens, G.W., 1990. "An Efficient Method of Moments Estimator for Discrete Choice Models with Choice-Based Sampling," Discussion Paper 1990-9, Tilburg University, Center for Economic Research.
    15. Brownston, David & Bunch, David S. & Train, Kenneth, 1999. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," University of California Transportation Center, Working Papers qt7rf7s3nx, University of California Transportation Center.
    16. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-57, September.
    17. Kenneth Train, . "Simulation Methods for Probit and Related Models Based on Convenient Error Partitioning," Working Papers _009, University of California at Berkeley, Econometrics Laboratory Software Archive.
    18. Poirier, Dale J., 1996. "A Bayesian analysis of nested logit models," Journal of Econometrics, Elsevier, vol. 75(1), pages 163-181, November.
    19. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
    20. John Calfee & Clifford Winston & Randolph Stempski, 2001. "Econometric Issues In Estimating Consumer Preferences From Stated Preference Data: A Case Study Of The Value Of Automobile Travel Time," The Review of Economics and Statistics, MIT Press, vol. 83(4), pages 699-707, November.
    21. Bunch, David S., 1988. "A comparison of algorithms for maximum likelihood estimation of choice models," Journal of Econometrics, Elsevier, vol. 38(1-2), pages 145-167.
    22. Poirier, Dale J, 1988. "Frequentist and Subjectivist Perspectives on the Problems of Model Building in Economics," Journal of Economic Perspectives, American Economic Association, vol. 2(1), pages 121-44, Winter.
    23. Brownstone, D. & Golob, T.F. & Kazimi, C., 1999. "Modeling Non-Ignorable Attrition and Measurement Error in Panel Surveys: An Application to Travel Demand Modeling," Papers 99-00-06, California Irvine - School of Social Sciences.
    24. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240.
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