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Linear and Nonparametric Quantile Regression

In: Quantile Regression for Spatial Data

Author

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  • Daniel P. McMillen

    (University of Illinois)

Abstract

Quantile regression estimates can be presented in tables alongside linear regression estimates. A possible advantage of this approach to presenting quantile regression results is that it is easy to compare the values of the coefficients and standard errors with OLS estimates and across quantiles. As we have seen, quantile estimates actually contain far more information than can be presented in simple tables. The estimates imply a full distribution of values for the dependent variable. It also is easy to show how changes in the explanatory variables affect the distribution of the dependent variable.

Suggested Citation

  • Daniel P. McMillen, 2013. "Linear and Nonparametric Quantile Regression," SpringerBriefs in Regional Science, in: Quantile Regression for Spatial Data, edition 127, chapter 0, pages 13-27, Springer.
  • Handle: RePEc:spr:sbrchp:978-3-642-31815-3_2
    DOI: 10.1007/978-3-642-31815-3_2
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    Cited by:

    1. Pieter Jan Trinks & Bert Scholtens, 2017. "The Opportunity Cost of Negative Screening in Socially Responsible Investing," Journal of Business Ethics, Springer, vol. 140(2), pages 193-208, January.

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