%0 Journal Article
%T Interval-Based Hypothesis Testing and Its Applications to Economics and Finance
%A Andrew P. Robinson
%A Jae H. Kim
%J -
%D 2019
%R https://doi.org/10.3390/econometrics7020021
%X 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-Tex
%K equivalence
%K minimum-effect
%K non-inferiority
%K point-null hypothesis testing
%K zero probability paradox
%U https://www.mdpi.com/2225-1146/7/2/21