Asymptotic Power Advantages of Long-Horizon Regression Tests

Ohio State University

40 Pages Posted: 19 Jul 2002

See all articles by Nelson C. Mark

Nelson C. Mark

University of Notre Dame - Department of Economics and Econometrics; National Bureau of Economic Research (NBER)

Donggyu Sul

Independent

Date Written: June 2002

Abstract

Local asymptotic power advantages are available for testing the null hypothesis that the slope coefficient is zero in regressions of y(t+k)-y(t) on x(t) for k > 1 where the x(t) and the change in y(t) are I(0) series. The advantages of these long-horizon regression tests accrue in a linear environment over empirically relevant regions of the admissible parameter space. In Monte Carlo experiments, small sample power advantages to long-horizon regression tests accrue in a region of the parameter space that is larger than that predicted by the asymptotic analysis.

Keywords: Local Asymptotic Power, Long-Horizon, Regression

JEL Classification: C12, C22, G12

Suggested Citation

Mark, Nelson Chung and Sul, Donggyu, Asymptotic Power Advantages of Long-Horizon Regression Tests (June 2002). Ohio State University, Available at SSRN: https://ssrn.com/abstract=316779 or http://dx.doi.org/10.2139/ssrn.316779

Nelson Chung Mark (Contact Author)

University of Notre Dame - Department of Economics and Econometrics ( email )

442 Flanner
Notre Dame, IN 46556
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Donggyu Sul

Independent