It is well known that in a vector autoregressive (VAR) model Granger non-causality is characterized by a set of restrictions on the VAR coefficients. This characterization has been derived under the assumption of non-singularity of the covariance matrix of the innovations. This note shows that...

The most common forecasting methods in business are based on exponential smoothing and the most common time series in business are inherently non-negative. Therefore it is of interest to consider the properties of the potential stochastic models underlying exponential smoothing when applied to...

Credible Granger-causality analysis appears to require post-sample inference, as it is well-known that in-sample fit can be a poor guide to actual forecasting effectiveness. However, post-sample model testing requires an often-consequential <em>a priori</em> partitioning of the data into an...

This survey reviews diverse academic production on compositional dynamic series analysis. Although time dimension of compositional series has been little investigated, this kind of data structure is widely available and utilized in social sciences research. This way, a review of the...

This study uses a structural vector autoregressive (SVAR) model to examine the relationships between the intensity of drilling (i.e. investment) for natural gas production, natural gas withdrawals, economic activity and natural gas prices in the United States. The results show that the reaction...