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Testing for Structural Change in the Presence of Auxiliary Models Author info | Abstract | Publisher info | Download info | Related research | Statistics Eric Ghysels ()
Alain Guay
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Several estimation procedures such as the Efficient Method of Moments (EMM) of Gallant and Tauchen (1996) and Indirect Inference procedure of Gouriéroux, Monfort and Renault (1993) involve two models, an auxiliary one and a model of interest. The role played by both models poses challenges and provides new opportunities for hypothesis testing beyond the usual Wald, LM and LR-type tests. In this paper we present the asymptotic distribution theory for various classes of tests for structural change. Some procedures are extensions of standard tests while others are specific to the dual model setup and exploit its unique features. Plusieurs méthodes d'estimation nécessitent un modèle instrumental et un modèle d'intérêt. On retrouve parmi ces méthodes la méthode des moments efficace de Gallant et Tauchen (1996) et l'Inférence Indirecte proposée par Gouriéroux, Monfort et Renault (1993). La présence de ces deux modèles procure de nouvelles occasions d'inférence. Dans cet article, on présente et dérive la loi asymptotique de différents tests de changement structurel. Certaines procédures sont des extensions de tests standards tandis que d'autres sont spécifiquement adaptées à la présence des deux modèles.
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Paper provided by CIRANO in its series CIRANO Working Papers with number
2001s-54.
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Date of creation: 01 Sep 2001Date of revision:
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Keywords: Simulated method of estimation structural stability testing optimal tests Méthodes simulées d'estimations test de stabilité structurelle tests optimaux Other versions of this item:
Find related papers by JEL classification: C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models
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