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Model Selection Uncertainty and Detection of Threshold Effects

Jean-Yves Pitarakis ()

Discussion Paper Series In Economics And Econometrics from University of Southampton, Economics Division, School of Social Sciences

Abstract: Inferences about the presence or absence of threshold type nonlinearities in TAR models are conducted within models whose lag length has been estimated in a preliminary stage. Typically the null hypothesis of linearity is then tested against a threshold alternative on which the estimated lag length is imposed on each regime. In this paper we evaluate the properties of test statistics for detecting the presence of threshold effects in autoregressive models when this model uncertainty is taken into account. We show that this approach may lead to important distortions when the underlying model has truly threshold effects by establishing the limiting properties of the estimated lag length in the mispecified linear autoregressive fit and assessing the impact of this model uncertainty on the power of the tests. We subsequently propose a full model selection based approach designed to jointly detect the presence of threshold effects and optimally specify its dynamics and compare its performance with the traditional test based approach.

New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2004-07-01
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Related works:
Working Paper: Model Selection Uncertainty and Detection of Threshold Effecs (2004) Downloads
Journal Article: Model Selection Uncertainty and Detection of Threshold Effects (2006) Downloads
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