Prediction Using Distributed Lagged Subset Model

Suparman Suparman

Abstract

This  article  examines  the  problem  of  determining  the  future  value  of  the  dependent variable in the distributed lagged subset model. Unlike a distributed lag model in general, which assumes that all coefficients are not zero. In a distributed lagged subset model, some coefficients may be zero. The purpose of  this  study was  to determine  the predictive value of  the dependent variable in a distributed lagged subset model. The approach used to estimate the parameters of a distributed lagged subset model is the least square method and Ck statistic. Least squares method is used to determine the estimators of the coefficient of a distributed lagged subset model. Ck Statistic is used to select the best distributed lagged subset model. Some  simulations are delivered and prove  the efficiency of  this approach. Furthermore, this approach is implemented in real economic data. 
Keywords : Distributed lagged subset model, Prediction, Least square method, Ck Statistic.
 

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