Unit Root Model Selection*
نویسنده
چکیده
Some limit properties for information based model selection criteria are given in the context of unit root evaluation and various assumptions about initial conditions. Allowing for a nonparametric short memory component, standard information criteria are shown to be weakly consistent for a unit root provided the penalty coefficient Cn ! 1 and Cn/n ! 0 as n ! 1. Strong consistency holds when Cn/ (log log n) ! 1 under conventional assumptions on initial conditions and under a slightly stronger condition when initial conditions are infinitely distant in the unit root model. The limit distribution of the AIC criterion is obtained.
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