This paper concentrates on the properties of estimators in a semiparametric EV model, particularly considering the effects of missing data and linear process errors according to the actual situation. The… Click to show full abstract
This paper concentrates on the properties of estimators in a semiparametric EV model, particularly considering the effects of missing data and linear process errors according to the actual situation. The missing data are processed by three different methods: the direct deletion method, imputation (interpolation fill) method, and regression surrogate method. Also, the corresponding estimators of the slope parameter β and the nonparameter variable g ⋅ are obtained. All the estimators are asymptotically normal, and the consistency rates for which can achieve o n − 1 / 6 log n . Besides, the performance of the estimators is investigated by one sample experiment.
               
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