We investigate the effects of the misspecification of cointegrating ranks at other frequencies on the inference of seasonal cointegration at the frequency of interest such as test for cointegrating rank and estimation of cointegrating vector. Earlier studies mostly focused on a single frequency...

We shed light on a class of models that increase the flexibility of the seasonal pattern within a framework of the structural time series model. The basic idea is to drive the seasonal summation model by a moving average process rather than by a white noise or an AR process. Generally, such an...

This paper examines the distributions of (zero frequency) unit root test statistics for I(1) processes in the presence of noninvertible moving average components. The analysis initially considers a noninvertible MA(1), for which the asymptotic distribution of the ADF test statistic under the...

Government statistical agencies are required to seasonally adjust non-stationary time series resulting from an aggregate of a number of cross-sectional time series. Traditionally, this has been achieved using the X-11 or X12-ARIMA process by us- ing either direct or indirect seasonal adjustment....

This paper discusses how to model and forecast a vector of time series sampled at different frequencies. To this end we first study how aggregation over time affects both, the dynamic components of a time series and their observability, in a multivariate linear framework. We find that the basic...