End-of-Sample Instability Tests

44 Pages Posted: 13 Jun 2002

Date Written: May 2002


This paper considers tests for structural instability of short duration, such as at the end of the sample. The key feature of the testing problem is that the number, m, of observations in the period of potential change is relatively small -- possibly as small as one. The well-known F test of Chow (1960) for this problem only applies in a linear regression model with normally distributed iid errors and strictly exogenous regressors, even when the total number of observations, n + m, is large.

We generalize the F test to cover regression models with much more general error processes, regressors that are not strictly exogenous, and estimation by instrumental variables as well as least squares. In addition, we extend the F test to nonlinear models estimated by generalized method of moments and maximum likelihood.

Asymptotic critical values that are valid as n approaching infinity with m fixed are provided using a subsampling-like method. The results apply quite generally to processes that are strictly stationary and ergodic under the null hypothesis of no structural instability.

Keywords: Instrumental Variable Estimator, Least Squares Estimator, Parameter Change, Structural Instability Test, Structural Change

JEL Classification: C12, C52

Suggested Citation

Andrews, Donald W. K., End-of-Sample Instability Tests (May 2002). Available at SSRN: https://ssrn.com/abstract=313004

Donald W. K. Andrews (Contact Author)

Yale University - Cowles Foundation ( email )

Box 208281
New Haven, CT 06520-8281
United States
203-432-3698 (Phone)
203-432-6167 (Fax)

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