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The lower regression function and testing expectation dependence dominance hypotheses

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  • Oliver Linton
  • Yoon Jae Whang
  • Yu-Min Yen

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 the question of portfolio choice and to the question of the relation of growth to public debt.

Suggested Citation

  • Oliver Linton & Yoon Jae Whang & Yu-Min Yen, 2021. "The lower regression function and testing expectation dependence dominance hypotheses," Econometric Reviews, Taylor & Francis Journals, vol. 40(8), pages 709-727, September.
  • Handle: RePEc:taf:emetrv:v:40:y:2021:i:8:p:709-727
    DOI: 10.1080/07474938.2021.1889177
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    References listed on IDEAS

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    1. Thomas Herndon & Michael Ash & Robert Pollin, 2014. "Does high public debt consistently stifle economic growth? A critique of Reinhart and Rogoff," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 38(2), pages 257-279.
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    8. Delgado, Miguel A., 1993. "Testing the equality of nonparametric regression curves," Statistics & Probability Letters, Elsevier, vol. 17(3), pages 199-204, June.
    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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