Testing a Large Set of Zero Restrictions in Regression Models, with an Application to Mixed Frequency Granger Causality

38 Pages Posted: 12 Jun 2015 Last revised: 11 Nov 2019

See all articles by Eric Ghysels

Eric Ghysels

University of North Carolina Kenan-Flagler Business School; University of North Carolina (UNC) at Chapel Hill - Department of Economics

Jonathan B. Hill

University of North Carolina (UNC) at Chapel Hill – Department of Economics

Kaiji Motegi

Kobe University - Graduate School of Economics

Date Written: November 10, 2019

Abstract

This paper proposes a new test for a large set of zero restrictions in regression models based on a seemingly overlooked, but simple, dimension reduction technique. The procedure involves multiple parsimonious regression models where key regressors are split across simple regressions. Each parsimonious regression model has one key regressor and other regressors not associated with the null hypothesis. The test is based on the maximum of the squared parameters of the key regressors. Parsimony ensures sharper estimates and therefore improves power in small sample. We present the general theory of our test and focus on mixed frequency Granger causality as a prominent application involving many zero restrictions.

Keywords: dimension reduction, Granger causality test, max test, Mixed Data Sampling (MIDAS), parsimonious regression models

JEL Classification: C12, C22, C51

Suggested Citation

Ghysels, Eric and Hill, Jonathan B. and Motegi, Kaiji, Testing a Large Set of Zero Restrictions in Regression Models, with an Application to Mixed Frequency Granger Causality (November 10, 2019). Available at SSRN: https://ssrn.com/abstract=2616736 or http://dx.doi.org/10.2139/ssrn.2616736

Eric Ghysels

University of North Carolina Kenan-Flagler Business School ( email )

Kenan-Flagler Business School
Chapel Hill, NC 27599-3490
United States

University of North Carolina (UNC) at Chapel Hill - Department of Economics ( email )

Gardner Hall, CB 3305
Chapel Hill, NC 27599
United States
919-966-5325 (Phone)
919-966-4986 (Fax)

HOME PAGE: http://https://eghysels.web.unc.edu/

Jonathan B. Hill

University of North Carolina (UNC) at Chapel Hill – Department of Economics ( email )

102 Ridge Road
Chapel Hill, NC NC 27514
United States

Kaiji Motegi (Contact Author)

Kobe University - Graduate School of Economics ( email )

2-1, Rokkodai
Nada-Ku
Kobe, Hyogo, 657-8501
Japan

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