sampling inherent in survey longitudinal data, (3) incorporation of predetermined variables in estimation, and (4 …This chapter presents a unified set of estimation methods for fitting a rich array of models describing dynamic … chapter is motivated by the principle that, whenever possible, estimation methods should rely on routines available in …

building are parameter estimation and evaluation that are also briefly considered. There are two possibilities of generating …

nonparametric estimation where the focus is the nonparametric quantity itself and the choice rule balances asymptotic variance with … squared asymptotic bias. It turns out that the optimal bandwidth for interval estimation has a different expansion rate and is … typically substantially larger than the optimal bandwidth for point estimation of the standard errors. The new approach to …

The literature on heteroskedasticity and autocorrelation robust (HAR) inference is extensive but its usefulness relies …

We develop a new targeted maximum likelihood estimation method that provides improved forecasting for misspecified …-validation procedure. In a set of Monte Carlo experiments we reveal that the estimation method can significantly improve the forecasting …

nonstationary. We also establish the estimation theory and asymptotic properties for these models in the short horizon and long …

This paper considers model averaging in spectral density estimation. We construct the spectral density function by …