force is the 63<sup>th</sup> percentile of the distribution of global factor volatility for whole sample and the 15<sup>th</sup> , 85<sup>th</sup> , and 63<sup>th</sup> percentile for developed, emerging and frontier markets, respectively.<sup>19</sup> A second possible concern regarding our analysis may stem from the fact that our measure of financial volatility is, by construction, correlated with the stock market volatility of the basket of countries that are used in the principal component analysis. Hence, we rerun our analysis using the VIX instead of _σGF_ . The correlation between the two measures is 0.8. The results are presented in table A2 and indicate that the relation between financial globalization and financial volatility depends upon the state of the global economy as in our main specification. The thresholds for which financial globalization turns to be destabilizing are now the 42<sup>nd</sup> percentile for the whole sample, the 1<sup>st</sup> , 55<sup>th</sup> , and 74<sup>th</sup> percentiles of the VIX distribution for developed, emerging, and frontier markets, respectively. The fact that higher levels of financial globalization are associated with higher stock market volatility in developed markets, for virtually all levels of the VIX, may well reflect the fact that the VIX is indeed a measure of developed market (US) financial volatility.

In our view, the right indicator to understand whether financial globalization affects financial volatility in a particular country is stock market volatility expressed in domestic currency. However, one may wonder what happens if the returns are computed in USD, hence incorporating the effects of exchange rate movements. The results are presented in table A3 and are very similar to those in local currency, although the coefficient of FGI in developed markets is now significant at 1%. The thresholds for which financial globalization becomes a destabilizing force are now the 74<sup>th</sup> percentile for the complete sample, and the 68<sup>th</sup> , 78<sup>th</sup> , and 82<sup>nd</sup> percentiles for developed, emerging, and frontier markets, respectively. This suggests that financial globalization is slightly less effective in reducing stock market volatility when expressed in USD rather than in domestic currency. This result could be driven by increases in exchange rate volatility correlated with deeper financial integration, as suggested by Donadelli and Paradiso (2014), and Caporale et al. (2011).

In order to address endogeneity concerns, in the estimates of tables 3 and 4, we use current stock market volatility and the lagged value of the FGI. As it is well-known, the lagging strategy solves the endogeneity problem if the shocks to the independent variable are not auto-correlated. This, of course, may not be the case. Hence, to partially address the problem, we decided to introduce the dependent variable and the FGI at different frequencies, monthly for the former, annual for the latter. This reduces the likelihood that an FGI shock in the previous year is correlated with a stock market volatility shock in the current month. Nonetheless, we decided to look at how our results would be affected had we introduced the variables at the same frequency. The results are presented in table A4 where all variables are expressed at annual frequency, and are quite similar to the previous ones. The thresholds for which financial globalization contributes to increase stock market volatility are now the 48, 16<sup>th</sup> , 40<sup>th</sup> , and 92<sup>th</sup> percentiles of the distribution of global market volatility, for the whole sample, developed, emerging and frontier markets, respectively. Notice, however, that our estimation sample contains only 25 annual data points for _σGF_ , in consequence the precision around these thresholds is lower.

> 19 Notice that, in the GMM estimations, to pass the second-order error autocorrelation test–for the whole sample and for developed markets–we had to introduce a second lag of the dependent variable. We also re-estimated tables 3 and 4 with this specification, and obtained virtually identical results, which are available upon request.

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