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Accounting for Asymmetry in M-Estimation

Author

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  • Manuel Stapper

Abstract

Standard M-Estimation techniques are biased if an asymmetric distribution is assumed. This article proposes a novel approach that uses an adaptive asymmetric loss function to tackle the bias. Its consistency and asymptotic normality are proven. The robustness properties are assessed in a simulation study showing similar performance compared to existing approaches. Its versatility is demonstrated in three applications to time series data, an instrumental regression and a classification task.

Suggested Citation

  • Manuel Stapper, 2024. "Accounting for Asymmetry in M-Estimation," CQE Working Papers 10924, Center for Quantitative Economics (CQE), University of Muenster.
    • Handle: RePEc:cqe:wpaper:10924
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    File URL: https://www.wiwi.uni-muenster.de/cqe/sites/cqe/files/CQE_Paper/cqe_wp_109_2024.pdf
    File Function: Version of October 2024
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    Keywords

    Robust Statistics; M-Estimation; Computational Statistics;
    All these keywords.

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