In this paper we discuss two methods for the estimation of linear dynamic factor models. The first method is behavioural in nature and consists of the least squares approximation of the observed data by means of a linear system. The second method is based on the statistical concept of principal...

In this paper we extend the univariate periodic integration model to multivariate cointegrated time series. We analyze representation issues of a multivariate periodic model. We argue that simple adding an index s to the parameters in an otherwise nonperiodic Vector AutoRegression (VAR) leads to...

We propose methods to test for common deterministic seasonality, while allowing for possible seasonal unit roots. For this purpose, we consider panel methods, where we allow for individualand for common dynamics. To decide on the presence of seasonal unit roots, we introduce a decision-based...

We consider representation, estimation and inference on cointegration in a periodic vector autoregressive time series model (PVAR). We show that cointegration amounts to a restriction on a product of parameter matrices. We therefore use GMM to construct estimators of the long-run (cointegration)...

Generalized Method of Moments (GMM) Estimators are derived for Reduced Rank Regression Models, the Error Corrections Cointegration Model (ECCM) and the Incomplete Simultaneous Equations Model (INSEM). The GMM (2SLS) estimators of the cointegrating vector in the ECCM are shown to have normal...

We construct limiting and small sample distributions of maximum likelihood estimators (mle) from the property that they satisfy the first order condition (foc). The foc relates the mle of the analyzed model to the mle of an encompassing model and shows that the mle of the analyzed model is a...