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Weighted Derivative Estimation of Quantal Response Models: Simulations and Applications to Choice of Truck Freight Carrier

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  • Erik Bergkvist

    (Ume University)

  • Per Johansson

    (IFAU-Office of Labour Market Policy Evaluation)

Abstract

Summary Under the assumption of a single-index model the weighted average density derivative (WAD) estimator, estimates regression parameters up to scale. The small sample performance of ratio estimators are studied. For spherical errors in a latent variable specification the WAD estimator, in terms of bias and mean square error (MSE), demonstrates performance similar to the logit maximum likelihood estimator. Under heteroskedastic errors the WAD estimator performs better. In an empirical application concerning choices of freight transports we find that the WAD estimator evidences improved performance in one of the two sectors studied compared with standard parametric models.

Suggested Citation

  • Erik Bergkvist & Per Johansson, 2000. "Weighted Derivative Estimation of Quantal Response Models: Simulations and Applications to Choice of Truck Freight Carrier," Computational Statistics, Springer, vol. 15(4), pages 485-510, December.
    • Handle: RePEc:spr:compst:v:15:y:2000:i:4:d:10.1007_pl00022716
    DOI: 10.1007/PL00022716
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    References listed on IDEAS

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    1. Bergkvist, Erik & Westin, Lars, 1998. "Regional valuation of infrastructure improvements. The case of Swedish road freight," Umeå Economic Studies 463, Umeå University, Department of Economics.
    2. W. Michael Hanemann, 1989. "Welfare Evaluations in Contingent Valuation Experiments with Discrete Response Data: Reply," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(4), pages 1057-1061.
    3. Chuan-Zhong Li, 1996. "Semiparametric Estimation of the Binary Choice Model for Contingent Valuation," Land Economics, University of Wisconsin Press, vol. 72(4), pages 462-473.
    4. Newey, Whitney K & Powell, James L & Walker, James R, 1990. "Semiparametric Estimation of Selection Models: Some Empirical Results," American Economic Review, American Economic Association, vol. 80(2), pages 324-328, May.
    5. Hardle, Wolfgang & Tsybakov, A. B., 1993. "How sensitive are average derivatives?," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 31-48, July.
    6. Amemiya, Takeshi, 1981. "Qualitative Response Models: A Survey," Journal of Economic Literature, American Economic Association, vol. 19(4), pages 1483-1536, December.
    7. Yatchew, Adonis & Griliches, Zvi, 1985. "Specification Error in Probit Models," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 134-139, February.
    8. Manski, Charles F., 1985. "Semiparametric analysis of discrete response : Asymptotic properties of the maximum score estimator," Journal of Econometrics, Elsevier, vol. 27(3), pages 313-333, March.
    9. Powell, James L. & Stoker, Thomas M., 1996. "Optimal bandwidth choice for density-weighted averages," Journal of Econometrics, Elsevier, vol. 75(2), pages 291-316, December.
    10. W. Michael Hanemann, 1984. "Welfare Evaluations in Contingent Valuation Experiments with Discrete Responses," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 66(3), pages 332-341.
    11. Powell, James L & Stock, James H & Stoker, Thomas M, 1989. "Semiparametric Estimation of Index Coefficients," Econometrica, Econometric Society, vol. 57(6), pages 1403-1430, November.
    12. Lee, Lung-Fei, 1982. "Specification error in multinomial logit models : Analysis of the omitted variable bias," Journal of Econometrics, Elsevier, vol. 20(2), pages 197-209, November.
    13. Hardle, Wolfgang & Tsybakov, A. B., 1993. "How sensitive are average derivatives?," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 31-48, July.
    14. Ruud, Paul A, 1983. "Sufficient Conditions for the Consistency of Maximum Likelihood Estimation Despite Misspecifications of Distribution in Multinomial Discrete Choice Models," Econometrica, Econometric Society, vol. 51(1), pages 225-228, January.
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