Nonlinear Econometric Models with Deterministically Trending Variables

Donald Andrews () and Christopher McDermott

No 1053, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: This paper considers an alternative asymptotic framework to standard sequential asymptotics for nonlinear models with deterministically trending variables. The asymptotic distributions of generalized method of moments estimators and corresponding test statistics are derived using this framework. The asymptotic distributions are shown to be the same with deterministically trending variables as with non-trending variables. That is, the distributions are normal and chi-squared respectively. The asymptotic covariance matrices of the estimators, however, are found to depend on the form of the trends. These findings provide a justification for the use of standard asymptotic approximations in nonlinear models even when the variables have deterministic trends.

Keywords: Asymptotics; deterministic trend; generalized method of moments estimator; hypothesis test; nonlinear econometric model; time trend (search for similar items in EconPapers)
Pages: 25 pages
Date: 1993-08
Note: CFP 907.
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Citations: View citations in EconPapers (1)

Published in Review of Economic Studies (1005), 62: 343-360

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Journal Article: Nonlinear Econometric Models with Deterministically Trending Variables (1995)
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