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Covariates Hiding in the Tails

Author

Listed:
  • Milian Bachem
  • Lerby Ergun
  • Casper de Vries

Abstract

Scaling behavior measured in cross-sectional studies through the tail index of a power law is prone to a bias. This hampers inference; in particular, time variation in estimated tail indices may be erroneous. In the case of a linear factor model, the factor biases the tail indices in the left and right tail in opposite directions. This fact can be exploited to reduce the bias. We show how this bias arises from the factor, how to remedy for the bias and how to apply our methods to financial data and geographic location data.

Suggested Citation

  • Milian Bachem & Lerby Ergun & Casper de Vries, 2021. "Covariates Hiding in the Tails," Staff Working Papers 21-45, Bank of Canada.
    • Handle: RePEc:bca:bocawp:21-45
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    References listed on IDEAS

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    More about this item

    Keywords

    Econometric and statistical methods;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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