window estimation. This o¤ers two advantages: ...rst, the windows cover a shorter time span (20 years), which partly mitigates (although it certainly does not eliminate) the concern with the variation of the explanatory variables over time. Second, it allows us to build a panel combining the factor loading estimates from the di¤erent windows, so that the estimation can exploit, at least to some extent, the time variation of the regressors across windows.

Table 8 reports the estimation results, for both the CIF and COD global factor loadings.<sup>28</sup> In addition to ...nancial openness, ...nancial depth and the exchange rate regime, we also examine the role of trade openness, which might o¤er another channel for the propagation of global ...nancial conditions. The explanatory variables are averaged over the corresponding 20-year window. In particular, we compute GLS estimates, using an AR(1) speci...cation to take into account the likely persistence arising from the fact that consecutive windows share a good deal of information.

The ...rst ...ve columns of Table 8 correspond to the regressions with the CIF global factor loadings as dependent variable. The results indicate that countries’exposure to the global forces behind capital in‡ows rises signi...cantly with their degree of ...nancial openness (column 1), as well as trade openness (column 2) and ...nancial depth (column 3). A higher degree of exchange rate rigidity (i.e., a decline in the value of the exchange rate regime index) has the same e¤ect (column 4). These results are highly signi...cant, and survive when all four variables are jointly considered (column 5), except for the e¤ect of trade openness, which becomes insigni...cant.

The last ...ve columns of Table 8 report the results using the COD global factor loadings as dependent variable. For the most part, the estimates are not very di¤erent from those obtained with the CIF factor loadings. This is unsurprising given that, as shown earlier, the loadings on both global factors show large positive correlation. The main di¤erence is that the coe¢ cient estimate on the exchange rate regime in column 4 of the out‡ow loadings regressions is only half as large as that in column 4 of the in‡ow loadings regressions. Finally, when all four regressors are jointly considered, the exchange rate regime becomes insigni...cant, and only ...nancial openness and ...nancial depth remain statistically signi...cant. The conclusion is that, once these two variables are taken into account, the degree of exchange rate rigidity still matters for countries’sensitivity to the global forces driving capital in‡ows, but not for their sensitivity to the global forces driving capital out‡ows.<sup>29</sup>

> 28We focus on the global factor loadings, because – as Figures 4 and 5 showed – they vary markedly between advanced and emerging countries, much more so than do the group factor loadings. They also display more variation over time than do the group factor loadings, as can be inferred from the cyclical patterns shown in Figures 8-10.

> 29For emerging markets, Obstfeld, Ostry and Qureshi (2017) likewise ...nd a signi...cant dampening e¤ect of exchange rate ‡exibility on the responsiveness of gross in‡ows to global risk, as measured by the VXO index, but not on the response of gross out‡ows. In contrast, Cerutti, Claessens and Puy (2017) ...nd the

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