**Table 13: Combined Index and Numerical Index**

||(1)<br>All Inflows|(2)<br>All Outflows|(3)<br><sup>Resident</sup><br>Inflows^|(4)<br>Resident<br>Outflows^|(5)<br>Non-Resident<br>Inflows^|(6)<br> <br>Non-Resident<br>Outflows^|
|---|---|---|---|---|---|---|
|Cyclical comp. of G|DP 0.066|0.339|0.335|0.785|-0.212|0.269|
||[0.35]|[0.87]|[0.64]|[0.89]|[0.51]|[0.80]|
|Constant|0.034***|0.045***|0.060***|0.135***|0.061***|0.022***|
||[294.26]|[191.52]|[187.95]|[252.87]|[243.21]|[106.21]|
|Observations|2596|2596|2596|2596|2596|2596|
|R-squared|0.000|0.001|0.000|0.000|0.000|0.000|
|# of countries|42|42|42|42|42|42|

_Notes_ : The dependent variables in Column (1) and Column (2) are combined indices of restrictions on resident and non-resident inflows and outflows, respectively. ^ The dependent variables in Columns (3) – (6) are indices of CFMs on the respective type of flow. The indices can take values of -4 (Large Tightening), 0 (no change) and 4 (Large Easing). The 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.

Stylized Fact 4 in the previous section points to substantial cross-country differences in the use of CFMs. We test whether such differences also apply to the cyclicality of CFMs. Chart 6 plots for each country the unconditional correlation between the use of CFMs and the cyclical component of domestic real GDP. The chart shows that indeed there is a substantial degree of heterogeneity across countries, with roughly half the correlations being negative and the other half being positive. However, only one correlation coefficient is significantly different from zero for the use of CFMs on inflows and only four correlation coefficients are significantly different from zero for the use of CFMs on outflows (similar results are reported by Fernandez et al., 2015). These country-level observations, reinforce our conjecture that CFMs are not used as a cyclical policy tool even within specific regions or groups of countries.

# C **hart 6: Cross-country differences in the cyclicality of CFMs**

<!-- Start of picture text --> Correlation of CFM on inflows and output gap Correlation of CFM on outflows and output gap<br>.5 .5 Peru*<br>.4 .4<br>Philippines*<br>.3 Brazil* .3 Ukraine* Croatia*<br>Azerbaijan Thailand<br>.2.1 Thailand Tanzania Ukraine Mexico Jordan Russian Federation Argentina Czech Republic Ghana Macedonia Croatia .2.1 India Kazakhstan Indonesia Bulgaria Turkey Jordan Ghana Colombia Russian Federation Tanzania Hungary Azerbaijan Brazil<br>0-.1-.2 India Israel Peru Colombia Poland Romania Lithuania Chile Bulgaria Turkey Hungary China 0-.1-.2 Belarus Romania Malaysia Poland El Salvador<br>Correlation(Changes(-1,0,1)) -.3 Albania Malaysia South Africa Kazakhstan Indonesia Philippines Republic of Korea Correlation(Changes(-1,0,1)) -.3 Israel Albania Chile China Mexico Argentina Paraguay South Africa Czech Republic Republic of Korea<br>Macedonia<br>-.4 -.4<br>-.5 -.5<br><!-- End of picture text --> _Notes:_ Correlation between changes to CFMs and the cyclical component of GDP. * indicates that correlations are significantly different from 0 at the 5% significance level.

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