This paper proposes a nonparametric simultaneous test for parametric specification of the conditional mean and variance functions in a time series regression model. The test is based on an empirical likelihood (EL) statistic that measures the goodness-of-fit between the parametric estimates and...

In this note I show that the method proposed in Thomakos (2008) for optimal linear filtering, smoothing and trend extraction for a unit root process can be applied with no changes when a drift parameter is added to the process. The method in the aforementioned paper is based on Singular Spectrum...

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables model...

We derive new theoretical results on the properties of the adaptive least absolute shrinkage and selection operator (adaptive lasso) for time series regression models. In particular we investigate the question of how to conduct finite sample inference on the parameters given an adaptive lasso...

We introduce conditional score residuals and provide a general framework for the diagnostic analysis of time series models. A key feature of conditional score residuals is that they account for the shape of the conditional distribution. These residuals offer reliable and powerful diagnostic...

We consider the problem of testing for unit root in time series where the error term of the series is near unit root. As the error term approaches unit root, existing tests no longer retain reasonable small sample properties. We introduce a test statistic that is well-behaved in small sample...

When estimating the parameters of a process, researchers have to choose a reference unit of time (unit period). If the unit period is set equal to the sampling interval, then the parameter estimates will not necessarily be comparable across data sets with different sampling frequencies. However,...

An economic time series can often be viewed as a noisy proxy for an underlying economic variable. Measurement errors will influence the dynamic properties of the observed process and may conceal the persistence of the underlying time series. In this paper we develop instrumental variable (IV)...

A limit theory is established for autoregressive time series that smooths the transition between local and moderate deviations from unity and provides a transitional form that links conventional unit root distributions and the standard normal. Edgeworth expansions of the limit theory are given....