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Dual regression

Author

Listed:
  • Richard Spady
  • Sami Stouli
Abstract
We propose an alternative ('dual regression') to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while largely avoiding the need for `rearrangement' to repair the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach relies on a mathematical programming characterization of conditional distribution functions which, in its simplest form, provides a simultaneous estimator of location and scale parameters in a linear heteroscedastic model. The statistical properties of this estimator are derived.

Suggested Citation

  • Richard Spady & Sami Stouli, 2016. "Dual regression," CeMMAP working papers 04/16, Institute for Fiscal Studies.
    • Handle: RePEc:azt:cemmap:04/16
    DOI: 10.1920/wp.cem.2016.0516
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    References listed on IDEAS

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    1. Victor Chernozhukov & Iv·n Fern·ndez-Val & Alfred Galichon, 2010. "Quantile and Probability Curves Without Crossing," Econometrica, Econometric Society, vol. 78(3), pages 1093-1125, May.
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    5. Antonio Cosma & Olivier Scaillet & Rainer von Sachs, 2005. "Multiariate Wavelet-based sahpe preserving estimation for dependant observation," FAME Research Paper Series rp144, International Center for Financial Asset Management and Engineering.
    6. Belloni, Alexandre & Chernozhukov, Victor & Chetverikov, Denis & Fernández-Val, Iván, 2019. "Conditional quantile processes based on series or many regressors," Journal of Econometrics, Elsevier, vol. 213(1), pages 4-29.
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    13. Parker, Thomas, 2013. "A Comparison Of Alternative Approaches To Supremum-Norm Goodness-Of-Fit Tests With Estimated Parameters," Econometric Theory, Cambridge University Press, vol. 29(5), pages 969-1008, October.
    14. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Quantile and probability curves without crossing," CeMMAP working papers CWP10/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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    Cited by:

    1. Richard Spady & Sami Stouli, 2018. "Simultaneous mean-variance regression," CeMMAP working papers CWP25/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Newey, Whitney & Stouli, Sami, 2021. "Control variables, discrete instruments, and identification of structural functions," Journal of Econometrics, Elsevier, vol. 222(1), pages 73-88.

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