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RESET for quantile regression

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Abstract

This paper proposes a simple specification test for quantile regression models. Our test is based on Ramsey’s (J. R. Stat. Soc. B 31:350–371, 1969) RESET (regression specification error test). Comparing to existing nonparametric specification tests, the proposed test does not contain kernel functions and bandwidth parameters and is easy to implement. Although the proposed test is not necessarily consistent against all types of misspecification, simulation results indicate that our test has reasonable size and power properties and can be more powerful than nonparametric specification tests in small samples.

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References

  • Angrist J, Chernozhukov V, Fernández-Val I (2006) Quantile regression under misspecification, with an application to the US wage structure. Econometrica 74:539–563

    Article  MATH  MathSciNet  Google Scholar 

  • Bierens HJ, Ginther DK (2001) Integrated conditional moment testing of quadratic regression models. Empir Econ 26:307–324

    Article  Google Scholar 

  • Ihaka R, Gentleman R (1996) R: A language for data analysis and graphics. J Comput Graph Stat 5:299–314

    Article  Google Scholar 

  • Kim T-H, White H (2002) Estimation, inference, and specification testing for possibly misspecified quantile regression. Working paper

  • Koenker R (2005) Quantile regression. Cambridge University Press, Cambridge

    MATH  Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

  • Newey WK, McFadden DL (1994) Large sample estimation and hypothesis testing. In: Engle RF, McFadden DL (eds) Handbook of econometrics, vol IV. Elsevier, Amsterdam, pp 2213–2245

    Google Scholar 

  • Parzen MI, Wei L, Ying Z (1994) A resampling method based on pivotal estimating functions. Biometrika 81:341–350

    Article  MATH  MathSciNet  Google Scholar 

  • Ramsey JB (1969) Tests for specification errors in classical linear least-squares regression analysis. J R Stat Soc B 31:350–371

    MATH  MathSciNet  Google Scholar 

  • Ramsey JB, Schmidt P (1976) Some further results on the use of OLS and BLUS residuals in specification error tests. J Am Stat Assoc 71:389–390

    Article  MATH  MathSciNet  Google Scholar 

  • Zheng JX (1998) A consistent nonparametric test of parametric regression models under conditioning quantile restrictions. Econom Theory 14:123–138

    Google Scholar 

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Correspondence to Taisuke Otsu.

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Otsu, T. RESET for quantile regression. TEST 18, 381–391 (2009). https://doi.org/10.1007/s11749-008-0097-7

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  • DOI: https://doi.org/10.1007/s11749-008-0097-7

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