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Exact computation of max weighted score estimators

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Author Info

  • Florios, Kostas
  • Skouras, Spyros

Abstract

We show that exact computation of a family of 'max weighted score' estimators, including Manski's max score estimator, can be achieved efficiently by reformulating them as mixed integer programs (MIP) with disjunctive constraints. The advantage of our MIP formulation is that estimates are exact and can be computed using widely available solvers in reasonable time. In a classic work-trip mode choice application, our method delivers exact estimates that lead to a different economic interpretation of the data than previous heuristic estimates. In a small Monte Carlo study we find that our approach is computationally efficient for usual estimation problem sizes.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 146 (2008)
Issue (Month): 1 (September)
Pages: 86-91

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Handle: RePEc:eee:econom:v:146:y:2008:i:1:p:86-91

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Web page: http://www.elsevier.com/locate/jeconom

Related research

Keywords: Maximum score Mixed integer programming Estimator computation Work-trip mode choice;

References

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  1. Manski, Charles F. & Thompson, T. Scott, 1986. "Operational characteristics of maximum score estimation," Journal of Econometrics, Elsevier, vol. 32(1), pages 85-108, June.
  2. Donald W. K. Andrews, 1997. "A Stopping Rule for the Computation of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 65(4), pages 913-932, July.
  3. Timothy J. Bartik & J.S. Butler & Jin Tan Liu, 1990. "Maximum Score Estimates of the Determinants of Residential Mobility: Implications for the Value of Residential Attachment and Neighborhood Amenities," Upjohn Working Papers and Journal Articles 90-01, W.E. Upjohn Institute for Employment Research.
  4. Gozalo, Pedro & Linton, Oliver, 2000. "Local nonlinear least squares: Using parametric information in nonparametric regression," Journal of Econometrics, Elsevier, vol. 99(1), pages 63-106, November.
  5. Jouneau-Sion, Frederic & Torres, Olivier, 2006. "MMC techniques for limited dependent variables models: Implementation by the branch-and-bound algorithm," Journal of Econometrics, Elsevier, vol. 133(2), pages 479-512, August.
  6. Pinkse, C. A. P., 1993. "On the computation of semiparametric estimates in limited dependent variable models," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 185-205, July.
  7. Das, Sanghamitra, 1991. "A semiparametric structural analysis of the idling of cement kilns," Journal of Econometrics, Elsevier, vol. 50(3), pages 235-256, December.
  8. Thomas J. Kniesner & Anthony T. LoSasso, 2001. "Intergenerational Labor Market and Welfare Consequences of Poor Health," Center for Policy Research Working Papers 37, Center for Policy Research, Maxwell School, Syracuse University.
  9. Dufour, Jean-Marie, 2006. "Monte Carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics," Journal of Econometrics, Elsevier, vol. 133(2), pages 443-477, August.
  10. Manski, Charles F., 1975. "Maximum score estimation of the stochastic utility model of choice," Journal of Econometrics, Elsevier, vol. 3(3), pages 205-228, August.
  11. Jason Abrevaya & Jian Huang, 2005. "On the Bootstrap of the Maximum Score Estimator," Econometrica, Econometric Society, vol. 73(4), pages 1175-1204, 07.
  12. Skouras, Spyros, 2001. "Financial returns and efficiency as seen by an artificial technical analyst," Journal of Economic Dynamics and Control, Elsevier, vol. 25(1-2), pages 213-244, January.
  13. Horowitz, Joel L., 1993. "Semiparametric estimation of a work-trip mode choice model," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 49-70, July.
  14. 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.
  15. McDonald, James B., 1996. "An application and comparison of some flexible parametric and semi-parametric qualitative response models," Economics Letters, Elsevier, vol. 53(2), pages 145-152, November.
  16. Horowitz, Joel L., 2004. "Semiparametric models," Papers 2004,17, Humboldt-Universit├Ąt Berlin, Center for Applied Statistics and Economics (CASE).
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Citations

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Cited by:
  1. Dries Benoit & Rahim Alhamzawi & Keming Yu, 2013. "Bayesian lasso binary quantile regression," Computational Statistics, Springer, vol. 28(6), pages 2861-2873, December.
  2. Le-Yu Chen & Sokbae 'Simon' Lee & Myung Jae Sung, 2013. "Maximum score estimation of preference parameters for a binary choice model under uncertainty," CeMMAP working papers CWP14/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  3. D. F. Benoit & D. Van Den Poel, 2010. "Binary quantile regression: A Bayesian approach based on the asymmetric Laplace density," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 10/662, Ghent University, Faculty of Economics and Business Administration.

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