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We developed several measures to analyze the global financial cycle employing dynamic factor models and data for 25 advanced and emerging countries spanning 1980 to 2019. These measures were assessed using the similarity and synchronicity metrics proposed by Mink et al. (Oxford Economic Papers 64, 217–236, 2012). The findings indicate a strong similarity and synchronization of global cycles in asset prices and capital flows, particularly evident during crisis episodes. Furthermore, we observe significant co‐movement between our financial cycle measures and two literature‐based measures that utilize top‐down and bottom‐up approaches. However, the VIX index shows a lower level of co‐movement with our global financial cycle measures. [ABSTRACT FROM AUTHOR]

Recent years have seen many attempts to combine expenditure-side estimates of U.S. real output (GDE) growth with income-side estimates (GDI) to improve estimates of real GDP growth. We show how to incorporate information from multiple releases of noisy data to provide more precise estimates while avoiding some of the identifying assumptions required in earlier work. This relies on a new insight: using multiple data releases allows us to distinguish news and noise measurement errors in situations where a single vintage does not. We find that (a) the data prefer averaging across multiple releases instead of discarding early releases in favor of later ones, and (b) that initial estimates of GDI are quite informative. Our new measure, GDP++, undergoes smaller revisions and tracks expenditure measures of GDP growth more closely than either the simple average of the expenditure and income measures published by the BEA or the GDP growth measure of Aruoba et al. published by the Federal Reserve Bank of Philadelphia. [ABSTRACT FROM AUTHOR]

This note proposes a new criterion for the determination of the number of factors in an approximate static factor model. The criterion is strongly associated with the scree test and compares the differences between consecutive eigenvalues to a threshold. The size of the threshold is derived from a hyperbola and depends only on the sample size and the number of factors k. Monte Carlo simulations compare its properties with well-established estimators from the literature. Our criterion shows similar results as the standard implementations of these estimators, but is not prone to a lack of robustness against a too large a priori determined maximum number of factors kmax. [ABSTRACT FROM AUTHOR]

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