Often researchers find parametric models restrictive and sensitive to deviations from the parametric specifications; semi-nonparametric models are more flexible and robust, but lead to other complications such as introducing infinite-dimensional parameter spaces that may not be compact and the...

Log periodogram (LP) regression is shown to be consistent and to have a mixed normal limit distribution when the memory parameter d = 1. Gaussian errors are not required. Tests of d = 1 based on LP regression are consistent against d < 1 alternatives but inconsistent against d > 1 alternatives. A test based on a modified LP regression that...</1>

In the present paper we confine ourselves to proposing tests for smooth transition nonlinearity in the presence ou outliers. We consider outlier robust estimation techniques to modify the tests developed by Luukkonen et al

In this paper we consider model selection for time series with increasing (or decreasing) seasonal variation, where this variation can be described by (seasonal) unit root models with significant deterministic components or by models with less unit roots but with shiftsin seasonal means or trends

The paradox that a parametric approach makes less assumptions than a nonparametric one can be seen as an obstacle for a wider use of frequency domain techniques in econometrics. This paper offers a throrough appraisal of the parametric model in the presence of notoriously short economic time...

This paper offers a new method for estimation and forecasting of the linear and nonlinear time series when the stationarity assumption is violated. Our general local parametric approach particularly applies to general varying-coefficient parametric models, such as AR or GARCH, whose coefficients...

This paper analyses the properties of jackknife estimators of the first-order autoregressive coefficient when the time series of interest contains a unit root. It is shown that, when the sub-samples do not overlap, the sub-sample estimators have different limiting distributions from the...

Econometric estimation using simulation techniques, such as the efficient method of moments, may betime consuming. The use of ordinary matrix programming languages such as Gauss, Matlab, Ox or S-plus will very often cause extra delay. For the Efficient Method of Moments implemented to...

State space models with nonstationary processes and fixed regression effects require a state vector with diffuse initial conditions. Different likelihood functions can be adopted for the estimation of parameters in time series models with diffuse initial conditions. In this paper we consider...

We consider the problem of smoothing data on two-dimensional grids with holes or gaps. Such grids are often referred to as difficult regions. Since the data is not observed on these locations, the gap is not part of the domain. We cannot apply standard smoothing methods since they smooth over...