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Interval-Based Hypothesis Testing and Its Applications to Economics and Finance

Author

Listed:
  • Jae H. Kim

    (Department of Economics and Finance, La Trobe University, Bundoora, VIC 3086, Australia)

  • Andrew P. Robinson

    (School of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010, Australia)

Abstract

This paper presents a brief review of interval-based hypothesis testing, widely used in bio-statistics, medical science, and psychology, namely, tests for minimum-effect, equivalence, and non-inferiority. We present the methods in the contexts of a one-sample t -test and a test for linear restrictions in a regression. We present applications in testing for market efficiency, validity of asset-pricing models, and persistence of economic time series. We argue that, from the point of view of economics and finance, interval-based hypothesis testing provides more sensible inferential outcomes than those based on point-null hypothesis. We propose that interval-based tests be routinely employed in empirical research in business, as an alternative to point null hypothesis testing, especially in the new era of big data.

Suggested Citation

  • Jae H. Kim & Andrew P. Robinson, 2019. "Interval-Based Hypothesis Testing and Its Applications to Economics and Finance," Econometrics, MDPI, vol. 7(2), pages 1-22, May.
    • Handle: RePEc:gam:jecnmx:v:7:y:2019:i:2:p:21-:d:231401
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    References listed on IDEAS

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    3. Pankaj Agrrawal, 2023. "The Gibbons, Ross, and Shanken Test for Portfolio Efficiency: A Note Based on Its Trigonometric Properties," Mathematics, MDPI, vol. 11(9), pages 1-19, May.

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