Multiple Testing in Economics

21 Pages Posted: 23 Nov 2013  

Campbell R. Harvey

Duke University - Fuqua School of Business; National Bureau of Economic Research (NBER); Duke Innovation & Entrepreneurship Initiative

Yan Liu

Texas A&M University, Department of Finance

Date Written: November 21, 2013

Abstract

We propose a new way to conduct multiple hypothesis testing in economics research. Our framework allows for correlation among tests and incomplete data, both of which are prevalent in economic meta-analysis. Our simulations show that that our method is able to produce the correct p-value cutoff that controls the overall rate of false discoveries at a prespecified level of significance. The single hypothesis test, as used by most researchers, leads to too many false discoveries and should be avoided.

Keywords: Multiple tests, Correlation, Incomplete data, Meta-analysis, Data mining, False discoveries, Type I error, Type II error

JEL Classification: C12, C13, C21, C22, C52, G12, O11, B41

Suggested Citation

Harvey, Campbell R. and Liu, Yan, Multiple Testing in Economics (November 21, 2013). Available at SSRN: https://ssrn.com/abstract=2358214 or http://dx.doi.org/10.2139/ssrn.2358214

Campbell R. Harvey (Contact Author)

Duke University - Fuqua School of Business ( email )

Box 90120
Durham, NC 27708-0120
United States
919-660-7768 (Phone)
919-660-8030 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Duke Innovation & Entrepreneurship Initiative ( email )

215 Morris St., Suite 300
Durham, NC 27701
United States

Yan Liu

Texas A&M University, Department of Finance ( email )

Wehner 401Q, MS 4353
College Station, TX 77843-4218
United States

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