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...

This work presents a comparison of different techniques for disaggregating annual flow time series by a quarterly related indicator, based on a Monte Carlo experiment. A first goal of the study is related to the estimation of the autoregressive parameter implied by the solution proposed by Chow...

This work deals with the problem of obtaining an appropriate preliminary estimate of an unobserved high frequency (say monthly) time series. This problem arises when temporally disaggregating an observed series of low frequency (say quarterly) data. The preliminary estimated series should not...

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...

This paper assesses the statistical reliability of different measures of the output gap - the multivariate Hodrick-Prescott Filter, the multivariate unobserved components method and the structural vector autoregressive model - in the Euro area. Three criteria are used: the consistency of...

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...