overall sensitivity of countries’cross-border ‡ows to common shocks, and thus the quantitative relevance of the global ...nancial cycle for total capital ‡ows –a ...rst-order question from the macroeconomic perspective. Also, while most previous literature has focused on gross in‡ows, we consider both aggregate in‡ows and out‡ows. This allows us to examine their commonality, as well as the di¤erences in the extent to which they re‡ect the global cycle.

The analysis is conducted in the framework of a two-level latent factor model that combines global factors a¤ecting all countries with factors a¤ecting speci...c groups of countries – advanced, emerging and developing. The two-level factor model setting permits disentangling the common shocks with global reach from those a¤ecting only particular country groups. The variance decompositions obtained from the factor model provide a direct assessment of the quantitative importance of the global cycle for capital ‡ows across the world as well as across particular country groups.

The model is estimated using a recently-developed extension of the standard principalcomponent approach to the multi-level setting. This approach avoids unnecessary parameter restrictions often imposed in earlier literature, and o¤ers the key advantage of its computational simplicity. Recursive estimation of the factor model over moving time samples allows us to assess changes over time in the overall contribution of common shocks –rather than just that of particular variables, as considered by the existing literature.

To determine the observable counterparts of the latent factors, we analyze the relation between the estimated factors and global variables stressed in the ’push vs pull’literature. Likewise, we explore the determinants of countries’exposure to the global cycle by relating the estimated factor loadings to variables describing countries’ structural and policy framework, including in particular the exchange rate regime.

We ...nd that capital ‡ows exhibit a considerable degree of commonality among advanced and emerging countries. For both in‡ows and out‡ows, information criteria indicate the presence of one global factor plus one group factor for each of the two groups.<sup>3</sup> On average, the estimated common factors account for just under half of the observed variation of gross capital ‡ows of advanced and emerging countries. However, there are clear di¤erences across

> 3Cerutti, Claessens and Puy (2017) also employ a two-level latent factor model to examine disaggregated ‡ows to advanced and emerging countries. Like us, they ...nd a common factor driving gross in‡ows to emerging countries but, in contrast with our results, they do not ...nd a common factor behind in‡ows to advanced economies, nor a global factor a¤ecting in‡ows to both groups of countries. One possible reason for the discrepancy ia that we use a di¤erent dataset (aggregate annual data rather than their quarterly disaggregated data) and estimation method. Still, in our sample in‡ows to advanced countries display stronger commonality (as re‡ected by cross-country correlations) than those to emerging or developing countries. Using quarterly data, Advjiev et al (2017b) likewise ...nd that aggregate debt in‡ows to advanced countries react more strongly to global shocks than do in‡ows to emerging countries. Further, as discussed below, measures of cross-sectional dependence computed on our data strongly indicate the presence of common factors in advanced-country in‡ows (as well as out‡ows).

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