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The Lower Regression Function and Testing Expectation Dependence Dominance Hypotheses

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  • Linton, O.
  • Whang, Y-J.
  • Yen, Y.

Abstract

We provide an estimator of the lower regression function and provide large sample properties for inference. We also propose a test of the hypothesis of positive expectation dependence and derive its limiting distribution under the null hypothesis and provide consistent critical values. We apply our methodology to several empirical questions.

Suggested Citation

  • Linton, O. & Whang, Y-J. & Yen, Y., 2018. "The Lower Regression Function and Testing Expectation Dependence Dominance Hypotheses," Cambridge Working Papers in Economics 1880, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:1880
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    References listed on IDEAS

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    8. Juan Carlos Escanciano & Javier Hualde, 2009. "Persistence In Nonlinear Time Series: A Nonparametric Approach," CAEPR Working Papers 2009-003, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    9. Lasse Heje Pedersen, 2015. "Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined," Economics Books, Princeton University Press, edition 1, number 10441.
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    Cited by:

    1. Denuit, Michel & Trufin, Julien & Verdebout, Thomas, 2021. "Testing for more positive expectation dependence with application to model comparison," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 163-172.
    2. Denuit, Michel & Trufin, Julien & Verdebout, Thomas, 2021. "Testing for more positive expectation dependence with application to model comparison," LIDAM Discussion Papers ISBA 2021021, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

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