Table 1 Summary statistics

|Variable|Mean|Std. dev.|25th pctl|75th pctl|Min|Max|
|---|---|---|---|---|---|---|
|Log(price)|4.64|0.13|4.59|4.68|3.07|5.19|
|Instrumented FIR (%)|-0.16|0.22|-0.34|0.00|-0.70|0.25|
|Stripped spread (bps)<br>|278|286|129|357|0|4,904|
|EIR duration (%)<br>|6.35|3.91|3.48|7.71|-0.03|19.08|
|Average life (years)<br>|9.6|8.9|4.0|9.9|1.0|99.8|
|Face amount (billion U.S. dollars)<br>|1.3|0.8|0.7|1.6|0.5|7.0|
|CDS (bps)|298|694|104|285|42|6,171|

Note: This table displays summary statistics for the main variables in the analysis. _Stripped Spread_ is the difference between a bond yield-to-maturity and the corresponding point on the U.S. Treasury spot curve, where the value of collateralized flows are “stripped” from the bond. _EIR Duration_ measures the sensitivity of dirty prices to parallel shifts of the U.S. interest rates, expressed as the percentage change of dirty price if all U.S. interest rates change by 100 basis points. _Average Life_ is the weighted average period until principal repayment, and _CDS_ denotes the five-year credit default swap spread of USD-denominated sovereign bonds. Sources: Bloomberg, Datastream, J.P. Morgan Markets, Morningstar Direct, and authors’ calculations.

of funds benchmarked against the EMBIGD and EMBI Global Core for 2016–2017.<sup>14,15</sup> For each fund, we compute their _Passive Share_ = 100 _− Active Share_ , where _Active Share_ is the measure developed by Cremers and Petajisto (2009). We first estimate this variable at the country level, which is the level of the FIR measure.<sup>16</sup> This allows us to separate, even for active funds, the fraction of a fund’s portfolio that might be passive or active, consistent with the model in Section 2. We then compute the average _Passive Share_ weighted by each fund’s AUM. With this strategy, we obtain an estimated passive fund share of 50%.<sup>17</sup> We calculate _At_ by adjusting the AUM tracking the EMBIGD index, using a rescaling factor of 50%, thus obtaining the estimated passive funds tracking the index we use to compute the FIR.<sup>18</sup> We gather data on individual bond prices from Datastream and obtain several bond characteristics (maturity and duration, among others) directly from J.P. Morgan Markets. To clean our dataset, we drop extreme values of daily returns, stripped spreads, and _Zc,t_ .<sup>19</sup> We drop stripped spreads below 0 or above 5 _,_ 000 basis points as well as observations below

> 14The EMBI Global Core uses the same diversification methodology as the EMBIGD to calculate the bond weights, as described in Appendix . The criteria for including bonds in the EMBI Global Core is the same as that for the EMBIGD (and the EMBI Global), except the minimum face amount of the bonds must be US$1 billion and the maturity required to be maintained in the index is of at least one year.

> 15The data sample periods utilized in the paper are determined by data access constraints.

> 16We compute the _Active Share_ at the country level by using the country weights in the index and in the funds’ portfolios rather than bond weights. For the portfolios, we only assign bonds to a given country if they are included in the EMBIGD. Specifically, a country’s weight in a portfolio is determined by adding together the weights of all bonds from that country that are included in the EMBIGD.

> 17Appendix Table 1 provides results using alternative shares of passive funds used to construct the FIR measure. Although our quantitative estimates change slightly, the qualitative implications remain the same.

> 18For comparison, we construct _Active Share_ at the bond level, obtaining a value-weighted average of 72%. Cremers and Petajisto (2009) show an average value-weighted _Active Share_ that fluctuates between 55% and 80%.

> 19Stripped spread is defined in the notes of Table 1.

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