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Communications in Statistics - Simulation and Computation Volume 51, 2022 - Issue 6
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Original Articles

A computationally fast estimator for semiparametric multinomial choice model

Changbiao Liua School of Mathematics and Statistics, Northeast Normal University, Changchun, China;b College of Mathematical Sciences, Inner Mongolia Normal University, Huhhot, ChinaCorrespondence[email protected]
&
Jun Wanga School of Mathematics and Statistics, Northeast Normal University, Changchun, China
Pages 3355-3362 | Received 08 Jul 2019, Accepted 01 Jan 2020, Published online: 17 Jan 2020

References

  • Chiong, K. X., and M. Shum. 2019. Random projection estimation of discrete choice models with large choice sets. Management Science 65 (1):256–71. doi:10.1287/mnsc.2017.2928.
  • Fox, J. 2007. Semi-parametric estimation of multinomial discrete choice models using a subset of choices. The Rand Journal of Economics 38 (4):1002–29. doi:10.1111/j.0741-6261.2007.00123.x.
  • Manski, C. F. 1975. Maximum score estimation of the stochastic utility model. Journal of Econometrics 3 (3):205–28. doi:10.1016/0304-4076(75)90032-9.
  • Rockafellar, R. T. 1970. Convex analysis. Princeton Mathematical Series, No. 28. Princeton, NJ: Princeton University Press.
  • Shi, X. X., M. Shum, and W. Song. 2018. Estimating semi-parametric panel multinomial choice models using cyclic monotonicity. Econometrica 2:737–61. doi:10.3982/ECTA14115.
  • Yan, J. 2013. A smoothed maximum score estimator for multinomial discrete choice models. Working Paper, University of Wisconsin-Maison. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.369.5360.

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