We propose a general framework for measuring frequency dynamics of connectedness in economic variables based on spectral representation of variance decompositions. We argue that the frequency dynamics is insightful when studying the connectedness of variables as shocks with heterogeneous...

In this paper we revisit the methodological aspects of the issue of spurious cycles: using the well-established clinometric data, we apply an empirical strategy to identify spurious periodicities and cross-validate the results. The analysis of cyclical fluctuations involves numerous challenges,...

In this paper we revisit the methodological aspects of the issue of spurious cycles: using the well-established clinometric data, we apply an empirical strategy to identify spurious periodicities and cross-validate the results. The analysis of cyclical fluctuations involves numerous challenges,...

We propose a general framework for measuring frequency dynamics of connectedness in economic variables based on spectral representation of variance decompositions. We argue that the frequency dynamics is insightful when studying the connectedness of variables as shocks with heterogeneous...

The aim of this work is to analyze the business cycles of the Mercosur?s member countries in order to investigate their degree of synchronization. The econometric model uses the Beveridge-Nelson-Stock-Watson multivariate trend-cycle decomposition, taking into account the presence of common...

In his celebrated 1966 Econometrica article, Granger first hypothesized that there is a ‘typical’ spectral shape for an economic variable. This ‘typical’ shape implies decreasing levels of energy as frequency increases, which in turn implies an extremely long cycle in economic...

The Hilbert-Huang transform (HHT) was developed late last century but has still to be introduced to the vast majority of economists. The HHT transform is a way of extracting the frequency mode features of cycles embedded in any time series using an adaptive data method that can be applied...