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Finite sample nonparametric tests for linear regressions

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  • Karl Schlag
  • Olivier Gossner

Abstract

We introduce several exact nonparametric tests for finite sample multivariate linear regressions, and compare their powers. This fills an important gap in the literature where the only known nonparametric tests are either asymptotic, or assume one covariate only.

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Bibliographic Info

Paper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 1212.

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Date of creation: Mar 2010
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Handle: RePEc:upf:upfgen:1212

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Web page: http://www.econ.upf.edu/

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Keywords: Exact; linear regression; nonparametric.;

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  1. Karl Schlag, 2008. "Exact tests for correlation and for the slope in simple linear regressions without making assumptions," Economics Working Papers 1097, Department of Economics and Business, Universitat Pompeu Fabra.
  2. Dufour, J.M. & Hallin, M., 1992. "Improved Eaton Bounds for Linear Combinations of Bounded Random Variables with Statistical Applications," Cahiers de recherche 9224, Universite de Montreal, Departement de sciences economiques.
  3. Jean-Marie Dufour, 2003. "Identification, weak instruments, and statistical inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 36(4), pages 767-808, November.
  4. DUFOUR, Jean-Marie, 2003. "Identification, Weak Instruments and Statistical Inference in Econometrics," Cahiers de recherche 10-2003, Centre interuniversitaire de recherche en ├ęconomie quantitative, CIREQ.
  5. Karl H. Schlag, 2006. "Designing Non-Parametric Estimates and Tests for Means," Economics Working Papers ECO2006/26, European University Institute.
  6. James G. MacKinnon & Halbert White, 1983. "Some Heteroskedasticity Consistent Covariance Matrix Estimators with Improved Finite Sample Properties," Working Papers 537, Queen's University, Department of Economics.
  7. Karl Schlag, 2008. "A new method for constructing exact tests without making any assumptions," Economics Working Papers 1109, Department of Economics and Business, Universitat Pompeu Fabra.
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