Econometric Theory

Research Article

WEIGHTED AVERAGE POWER SIMILAR TESTS FOR STRUCTURAL CHANGE IN THE GAUSSIAN LINEAR REGRESSION MODEL

Giovanni Forchinia1 c1

a1 Monash University

Abstract

Average exponential F tests for structural change in a Gaussian linear regression model and modifications thereof maximize a weighted average power that incorporates specific weighting functions to make the resulting test statistics simple. Generalizations of these tests involve the numerical evaluation of (potentially) complicated integrals. In this paper, we suggest a uniform Laplace approximation to evaluate weighted average power test statistics for which a simple closed form does not exist. We also show that a modification of the avg-F test is optimal under a very large class of weighting functions and can be written as a ratio of quadratic forms so that both its p-values and critical values are easy to calculate using numerical algorithms.

Correspondence

c1 Address correspondence to Giovanni Forchini, Department of Econometrics and Business Statistics, Monash University, Clayton, Victoria 3800, Australia; e-mail: Giovanni.Forchini@BusEco.monash.edu.au

Footnotes

I thank Peter Phillips, Patrick Marsh, and Simone Grose for useful and encouraging comments. Comments from two referees and the co-editor Richard Smith improved the presentation of the paper. This research was partially supported by Australian Research Council grant DP0771445.

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