An Efficient Almon Two-parameter Estimator for the Heteroscedastic Distributed Lag Model: A Monte Carlo Evidence

Résumé fourni par la source

The distributed lag models (DLM) are very useful in econometrics and statistics. The technique of Almon polynomial distributed lag is a commonly used estimation method when dealing with the DLM. To circumvent the problem of multicollinearity associated with the Almon technique, the Almon two parameter estimator (ATPE) is recently proposed in the literature, which has some advantages over other available estimators. However, the ATPE may become severely inefficient when the DLM is plagued with the heteroscedasticity of unknown form. This study is intended to address this issue and propose an adaptive version of the ATPE which is more efficient than the ATPE in the presence of heteroscedasticity of unknown form. To gauge the performance of our proposed method, a Monte Carlo simulation scheme is used where mean squared error is used as the evaluation criteria. The simulation results witness the supremacy of our proposed method.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.