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A distribution-free test for outliers

Author

Listed:
  • Candelon, Bertrand
  • Metiu, Norbert

Abstract

Determining whether a data set contains one or more outliers is a challenge commonly faced in applied statistics. This paper introduces a distribution-free test for multiple outliers in data drawn from an unknown data generating process. Besides, a sequential algorithm is proposed in order to identify the outlying observations in the sample. Our methodology relies on a two-stage nonparametric bootstrap procedure. Monte Carlo experiments show that the proposed test has good asymptotic properties, even for relatively small samples and heavy tailed distributions. The new outlier detection test could be instrumental in a wide range of statistical applications. The empirical performance of the test is illustrated by means of two examples in the fields of aeronautics and macroeconomics.

Suggested Citation

  • Candelon, Bertrand & Metiu, Norbert, 2013. "A distribution-free test for outliers," Discussion Papers 02/2013, Deutsche Bundesbank.
    • Handle: RePEc:zbw:bubdps:022013
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    File URL: https://www.econstor.eu/bitstream/10419/68604/1/735352828.pdf
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    References listed on IDEAS

    as
    1. John Walsh, 1959. "Large sample nonparametric rejection of outlying observations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 10(3), pages 223-232, September.
    2. Carmen M. Reinhart & Kenneth S. Rogoff, 2011. "From Financial Crash to Debt Crisis," American Economic Review, American Economic Association, vol. 101(5), pages 1676-1706, August.
    3. Kindleberger, Charles P., 1991. "The Economic Crisis of 1619 to 1623," The Journal of Economic History, Cambridge University Press, vol. 51(1), pages 149-175, March.
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    Cited by:

    1. Fricke, Christoph & Menkhoff, Lukas, 2015. "Financial conditions, macroeconomic factors and disaggregated bond excess returns," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 80-94.
    2. Candelon, Bertrand & Metiu, Norbert & Straetmans, Stefan, 2013. "Disentangling economic recessions and depressions," Discussion Papers 43/2013, Deutsche Bundesbank.
    3. Namrata Chaudhary & Drimik Roy Chowdhury, 2019. "Data Preprocessing for Evaluation of Recommendation Models in E-Commerce," Data, MDPI, vol. 4(1), pages 1-22, January.

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    More about this item

    Keywords

    bootstrap; mode testing; nonparametric statistics; outlier detection;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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