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

**Jae H. Kim 1,\* and Andrew P. Robinson 2**


Received: 26 March 2019; Accepted: 7 May 2019; Published: 15 May 2019

**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.

**Keywords:** equivalence; minimum-effect; non-inferiority; point-null hypothesis testing; zero probability paradox

**JEL Classification:** C12

> *Genuinely interesting hypotheses are neighbourhoods, not points. No parameter is exactly equal to zero; many may be so close that we can act as if they were zero.*

> > Edward Leamer (1988)
