Skip to main content

Maximum Score Methods

  • Reference work entry
  • First Online:
The New Palgrave Dictionary of Economics
  • 19 Accesses

Abstract

This article describes some aspects of maximum score estimation of parameters of multinomial and, especially, binomial choice models. In the context of binomial choice models, strengths and weaknesses of the estimation procedure are discussed, as well as its relation to classical quantile regression estimation and its nonstandard rate of convergence. The benefits of smoothing the score criterion function are also noted.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 6,499.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 8,499.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Bibliography

  • Abrevaya, J., and J. Huang. 2005. On the bootstrap of the maximum score estimator. Econometrica 73: 1175–1204.

    Article  Google Scholar 

  • Horowitz, J.L. 1992. A smoothed maximum score estimator for the binary response model. Econometrica 60: 505–531.

    Article  Google Scholar 

  • Horowitz, J.L. 1993. Optimal rates of convergence of parameter estimators in the binary response model with weak distributional assumptions. Econometric Theory 9: 1–18.

    Article  Google Scholar 

  • Horowitz, J.L. 2002. Bootstrap critical values for tests based on the smoothed maximum score estimator. Econometrica 111: 141–167.

    Article  Google Scholar 

  • Kim, J., and D. Pollard. 1990. Cube root asymptotics. Annals of Statistics 18: 191–219.

    Article  Google Scholar 

  • Koenker, R., and G. Bassett Jr. 1978. Regression quantiles. Econometrica 46: 33–50.

    Article  Google Scholar 

  • Kordas, G. 2006. Smoothed binary regression quantiles. Journal of Applied Econometrics 21: 387–407.

    Article  Google Scholar 

  • Manski, C.F. 1975. Maximum score estimation of the stochastic utility model of choice. Journal of Econometrics 3: 205–228.

    Article  Google Scholar 

  • Manski, C.F. 1985. Semiparametric analysis of discrete response: Asymptotic properties of the maximum score estimator. Journal of Econometrics 27: 313–333.

    Article  Google Scholar 

  • Manski, C.F. 1988. Analog estimation methods in econometrics. New York: Chapman and Hall.

    Google Scholar 

  • Manski, C.F. 1995. Identification problems in the social sciences. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • McFadden, D. 1974. Conditional logit analysis of qualitative choice behavior. In Frontiers in econometrics, ed. P. Zarembka. New York: Academic.

    Google Scholar 

  • Powell, J.L. 1994. Estimation of semiparametric models. In Handbook of econometrics, vol. 4, ed. R. Engle and D. McFadden. Amsterdam: North-Holland.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Copyright information

© 2018 Macmillan Publishers Ltd.

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Sherman, R.P. (2018). Maximum Score Methods. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_2847

Download citation

Publish with us

Policies and ethics