GNI per capita, smoothed for exchange rate changes using the Atlas method, rather than GDP per capita, which is used more commonly in the aid allocation literature. The World Bank also uses GNI per capita in its lending classifications (including eligibility for IDA) and its income classifications. Unsurprisingly, poverty selectivity of World Bank‐administered aid (IDA or trust funds) tends to be somewhat weaker if we use GDP per capita in our regressions instead of the measure the World Bank uses in its own allocation policies, GNI per capita. The choice of GNI or GDP makes little difference, however, for most other results, including the policy selectivity of aid.<sup>17</sup> Data for both income measures and for population come from the World Development Indicators (WDI 2015).

Aggregated and partially‐disaggregated CPIA scores for IDA‐eligible countries are publicly available from the WDI (2015) since 2005, and range from a minimum score of 1 (lowest quality policies) to a maximum of 6 (highest quality). For non‐IDA countries and prior years, scores are not publicly available, but were obtained with the necessary permissions by one of the authors from internal World Bank databases. In contrast to Wagner (2016), we are therefore able to include observations dating to 2002, and for non‐IDA as well as IDA countries. In a few cases, CPIA scores are not assigned after countries fall into arrears with the World Bank and are no longer classified as active borrowers. This typically is the case when the quality of policies and governance are very low, as indicated by their CPIA scores for years when they were active borrowers. In these cases, we replace the missing score with the lowest score received by any other country in this year, but results are not sensitive to dropping these observations instead.

Our main tests do not include other control variables, because our interest is mostly in comparing selectivity across aid sources. We control in some tests for a fragile state dummy, because some donors in recent years have given them favored status in allocating aid. A very small share of IDA funds are set aside for a handful of “post‐conflict” countries that overlap considerably with fragile state status. We create a dummy variable for fragile country status from the official World Bank list of fragile and conflict situations, first produced in 2006 and updated annually. When we include the fragile dummy, we limit the sample to the fiscal years 2006‐2012, where the dummy equals one in those country‐years in which a country was on the official lists of fragile situations.<sup>18</sup> We create a separate dummy for countries eligible for special “post‐conflict” funding (World Bank 2014b). In some specifications, we also control for (logged) bilateral aid and development aid received from official donors through channels other than trust funds and IDA using OECD/DAC data (2015) and World Bank data for (logged) IDA flows. If other aid flows are to some extent policy‐ and poverty‐selective, these aid flows are collinear with our measures of policy quality and poverty for which the coefficients are then imprecisely estimated.

In robustness tests, we control for several donor‐interest variables, following the literature on allocation of bilateral aid (e.g., Alesina and Dollar 2000). First, we measure geopolitical interests

> 17 Full results using GDP per capita are available from the authors upon request. In reporting results below we note two instances in which significant results for one variable become insignificant when GDP is used instead of GNI. 18 The absence of a list prior to 2006 likely reflects the lack of any influential view among donors that “fragility” was an important concept or that fragile states should be treated differently.

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