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Computational Statistics

, Volume 15, Issue 4, pp 485–510 | Cite as

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

  • Erik Bergkvist
  • Per Johansson
Article
  • 283 Downloads

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.

Keywords

Discrete choice Monte Carlo simulation Heteroskedasticity Bootstrap 

Notes

Acknowledgements

The authors acknowledge financial support from the Swedish Transport and Communications Research Board and the Swedish Research Council for the Humanities and Social Sciences. Helpful comments from Colin Cameron, Kurt Brännäs and Xavier de Luna and from seminar participants at the economics department at UC, Davis, CTS, Borlänge and Lund are gratefully acknowledged.

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Copyright information

© Physica-Verlag 2000

Authors and Affiliations

  • Erik Bergkvist
    • 1
  • Per Johansson
    • 2
  1. 1.Department of EconomicsUme UniversityUmeSweden
  2. 2.IFAU-Office of Labour Market Policy EvaluationUppsalaSweden

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