For non-stationary vector autoregressive models (VAR hereafter, or VAR with moving average, VARMA hereafter), we show that the presence of common cyclical features or cointegration leads to a reduction of the order of the implied univariate autoregressive-moving average (ARIMA hereafter) models....

This note argues that large VAR models with common cyclical feature restrictions provide an attractive framework for parsimonious implied univariate final equations, justifying on the one hand the estimation of homogenous panels with dynamic heterogeneity and a common factor structure, and on...

Combining economic time series with the aim to obtain an indicator for business cycle analyses is an important issue for policy makers. In this area, econometric techniques usually rely on systems with either a small number of series, N, or, at the other extreme, a very large N. In this paper we...

We analyze herein the importance of four types of shocks in contributing to the business cycles of the G7 economies. After disentangling the common permanent and transitory shocks in the G7 outputs, we identify the domestic and foreign components of such shocks for each country. This provides us...

In this paper we propose a new methodology to build composite coincident and leading indexes. Based on a formal definition which requires that the first difference of the leading index is the best linear predictor of the first difference of the coincident index, we show that the notion of...

This paper develops an econometric framework to understand whether co-movements observed in the international business cycle are the consequences of common shocks or common transmission mechanisms. Then we propose a new statistical measure of the importance of domestic and foreign shocks over...

This paper proposes an econometric framework to assess the importance of common shocks and common transmission mechanisms in generating international business cycles. Then we show how to decompose the cyclical effects of permanent-transitory shocks into those due to their domestic and those due...

This paper proposes a strategy to detect the presence of common serial correlation in high-dimensional systems. We show by simulations that univariate autocorrelation tests on the factors obtained by partial least squares outperform traditional tests based on canonical correlations.

We propose an approach for checking the data admissibility of non-stationary multivariate time series models (VAR or VARMA) through that of their implied individual ARIMA specifications. In particular we show that the presence of different kinds of common cyclical features restrictions, leading...