James–Stein estimators for time series regression models

Second order optimality for estimators in time series regression models

We consider the second order asymptotic properties of an efficient frequency domain regression coefficient estimator β̂ proposed by Hannan [4]. This estimator is a semiparametric estimator based on nonparametric spectral estimators. We derive the second order Edgeworth expansion of the distribution of β̂. Then it is shown that the second order asymptotic properties are independent of the bandwidt...

Regression Models for Time Series Analysis

Kernel Weighted GMM Estimators for Linear Time Series Models

This paper analyzes the higher order asymptotic properties of Generalized Method of Moments (GMM) estimators for linear time series models using many lags as instruments. A data dependent moment selection method based on minimizing the approximate mean squared error is developed. In addition, a new version of the GMM estimator based on kernel weighted moment conditions is proposed. It is shown ...

Predictions in Time Series Using Regression Models

Adaptive estimation in time series regression models

This work develops adaptive estimators for a linear regression model with serially correlated errors. We show that these results continue to hold when the order of the ARMA process characterizing the errors is unknown. The finite sample results are promising, indicating that substantial efficiency gains may be possible for samples as small as 50 observations. We use these estimators to investig...