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

1
Department of Economics and Finance, La Trobe University, Bundoora, VIC 3086, Australia
2
School of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010, Australia
*
Author to whom correspondence should be addressed.
Econometrics 2019, 7(2), 21; https://doi.org/10.3390/econometrics7020021
Received: 26 March 2019 / Revised: 6 May 2019 / Accepted: 7 May 2019 / Published: 15 May 2019
(This article belongs to the Special Issue Towards a New Paradigm for Statistical Evidence)
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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. View Full-Text
Keywords: equivalence; minimum-effect; non-inferiority; point-null hypothesis testing; zero probability paradox equivalence; minimum-effect; non-inferiority; point-null hypothesis testing; zero probability paradox
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Kim, J.H.; Robinson, A.P. Interval-Based Hypothesis Testing and Its Applications to Economics and Finance. Econometrics 2019, 7, 21.

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