Regarding the use of other policies, we find that countries generally lower their policy rates, when confronted by a sudden stop of capital flows; as well as relax their macroprudential regulations. This is consistent with Eichengreen and Gupta (2016), who note that in the period since the 2000s, counties have responded to sudden stops by lowering their policy rates, in order to support economic activity and financial markets; letting their exchange rates depreciate; and relaxing the macroprudential rules.<sup>24</sup> Similarly, countries typically respond to surges by raising the policy rates, letting their exchange rates appreciate, and accumulating reserves.

Finally, instead of analyzing the use of various policy measures only around the extreme events of sudden stops or sudden surges, we also analyze them for the regular pace of capital flows. Just like the cyclical components of output and credit, we calculate the cyclical component of capital flows by applying an HP-filter to capital flows as percent of trend GDP.<sup>25</sup> To alleviate the endogeneity concerns we lag the cyclical component of capital flows by a quarter in the regressions. Results are consistent with those established for the episodes of sudden stops and sudden surges. In the periods when capital inflows are above trend, monetary policy is tightened, the exchange rate appreciates, reserves are accumulated, but there is no change in capital flow measures.

**Table 11: Pace of Capital flows and Policy Tools**

||(1)<br>**C**|(2)<br>**apital Flow**|(3)<br>**Measures**<br>|(4)<br>**on**<br>|(5)|(6)|(7)|(8)<br>|(9)|
|---|---|---|---|---|---|---|---|---|---|
||||Non-|Non-||||Real||
||Resident<br>Inflows|Resident<br>Outflows|Resident<br>Inflows|Resident<br>Outflows|Interest<br>Rates|Macroprud<br>Regulation|Exchange<br>Rates|<br>effective<br>exch rate|FX<br>Reserves|
|Cyclical comp. of|0.003|0.006|0.000|0.000|0.053**|0.010|-0.012***|0.007***|0.015***|
|capital flows, lagged|[1.05]|[1.24]|[0.03]|[0.10]|[2.71]|[1.01]|[4.74]|[3.24]|[3.53]|
|Constant|0.025***|0.041***|0.016***|0.007***|-0.089***|0.062***|0.001***|0.000**|-0.001***|
||[279.27]|[249.39]|[181.64]|[57.13]|[106.21]|[93.32]|[14.83]|[2.54]|[9.44]|
|Observations|2292|2292|2292|2292|1641|1427|2254|1911|2258|
|R-squared|0.000|0.001|0.000|0.000|0.013|0.001|0.049|0.019|0.022|
|# of countries|37|37|37|37|30|25|37|30|37|

_Notes_ : Dependent variables in Columns 1-4 are indices of CFM on respective type of flows, which take value of -1/0/1 (Tightening/no change/Easing). The dependent variable in Column 5 is a binary variable of policy rate changes. A value of -1/1 indicates a reduction/increase in policy rates by at least 25bps over previous quarter. Dependent variable in Column 6 is a measure of macroprudential regulation taken from Cerruti et al. (2017). A value of 1 indicates a tightening of restrictions and a value of -1 an easing. The dependent variables in Column 7-9 are the cyclical components of log nominal exchange rates, log real effective exchange rate and log foreign reserves, respectively. The RHS variable is cyclical component of capital inflows. Regressions include country fixed effects. Robust t statistics are in parenthesis. *, ** and *** indicate that the coefficients are significant at the 10, 5 and 1 percent level.

> 24 Eichengreen and Gupta (2017) note that monetary easing and currency depreciation have been feasible because countries have reduced their foreign currency mismatches, limiting adverse balance-sheet effects from depreciation.

> 25 The series had some outliers, when values were more than 5 standard deviations further from the mean. We dropped these 12 observations.

22