This paper extends the notion of common cycles to quarterly time series having unit roots both at the zero and seasonal frequencies. It is shown that common cycles are present in the Hylleberg-Engle-Granger-Yoo decomposition of these series when there exists a linear combination of their...

This note concerns with the marginal models associated with a given vector autoregressive model. In particular, it is shown that a reduction in the orders of the univariate ARMA marginal models can be determined by the presence of variables integrated with different orders. The concepts and...

Modelling comovements amongst multiple economic variables takes up a relevant part of the literature in time series econometrics. Comovement can be defined as "move together", that is as movement that several series have in common. The pattern of the series could be of different nature, such as...

This paper considers methods for forecasting macroeconomic time series in a framework where the number of predictors, N, is too large to apply traditional regression models but not su¢ciently large to resort to statistical inference based on double asymptotics. Our interest is motivated by a...

Modelling comovements amongst multiple economic variables takes up a relevant part of the literature in time series econometrics. Comovement can be defined as “move together”, that is as movement that several series have in common. The pattern of the series could be of different nature, such...

This note concerns with the marginal models associated with a given vector autoregressive model. In particular, it is shown that a reduction in the orders of the univariate ARMA marginal models can be determined by the presence of variables integrated with different orders. The concepts and...

This paper considers methods for forecasting macroeconomic time series in a framework where the number of predictors, N, is too large to apply traditional regression models but not sufficiently large to resort to statistical inference based on double asymptotics. Our interest is motivated by a...

This paper proposes a strategy to detect and impose reduced-rank restrictions in medium vector autoregressive models. In this framework, it is known that Canonical Correlation Analysis (CCA) does not perform well because inversions of large covariance matrices are required. We propose a method...