_ln(disbursements)_ i,t = _α + β CPIAi,t‐1 + γ ln(populationi,t‐1) + δ ln(GNI p.C.i,t‐1) + λ’Xi,t‐k + αi + σt + εi,t_ where _i_ refers to the recipient country and _t_ to the Bank’s fiscal year. Errors _εi,t_ are robust to heteroscedasticity and clustered at the recipient country level and we include time‐fixed effects _σt_ and, in most regressions, recipient fixed effects _αi_ .

The inclusion of recipient fixed effects controls for any time‐invariant recipient characteristics that may influence aid allocations: estimates of poverty‐ and policy‐selectivity are then informed only by changes over time within countries in aid, GNI per capita, and quality of policy.<sup>22</sup> However, we also report results from pooled OLS (with standard errors clustered by recipient), in which estimates are informed primarily by cross‐country rather than over‐time variation in the data. The CPIA ratings are designed to compare the quality of policies across countries at a point in time using all relevant information at that time. Changes in ratings from one year to the next sometimes reflect newly‐available information rather than actual changes in the quality of policies and institutions, and ratings from prior years are not “corrected.” Over‐time variations in the data therefore are likely to incorporate substantially more measurement error than in the cross‐sectional variation. Reassuringly, the fixed effects estimates (which minimize omitted variable bias) reported below are largely consistent with the pooled OLS estimates (which are likely based on less noisy data).

Table 3 shows results with recipient‐ and year‐fixed effects for all IDA countries (columns 1‐ 3) and all developing countries (columns 4‐6). Trust funds and IDA provide significantly higher aid to poorer and better‐governed (i.e. higher CPIA) countries (columns 3 and 1 respectively). Trust fund allocations are thus much more similar to IDA than to other ODA in terms of poverty and policy selectivity.<sup>23</sup> Coefficients on (log of) GNI per capita (and on log of population) are interpretable as elasticities, so a 1% increase in per capita GNI reduces IDA flows by 1.9% (column 1) and TF aid by 2.5% (column 3). A 1‐point increase in the CPIA rating (measured on a 1 to 6 scale) is associated with a nearly 20‐fold increase in IDA flows ( = _e_<sup>3.031</sup> - 1) and 7-fold increase in TF aid ( = _e_<sup>2.088</sup> - 1). Note, however, that a 1‐point increase in CPIA is very large in relative terms, equal to nearly two standard deviations.

Even for a sample that includes non‐IDA countries (column 6), trust funds are very policy‐ selective as well as poverty‐selective. As shown in Table 4, this holds true in OLS regressions with year‐fixed effects that allow for the inclusion of time‐invariant variables. The main difference is that the estimated effects of country size are more consistent and significant. The coefficients on population for other aid types in Table 4 reflects the bias in favor of small‐countries (in per capita terms) frequently noted in the literature, but this bias is nearly absent for trust fund aid, where the coefficient on population is even slightly above one (see Fleck and Kilby 2010). When we include a dummy for fragile countries and limit the sample to the post‐2005 years accordingly, we do not find that these countries receive more trust fund aid (Table 5, column 2). Moreover, the inclusion of this

> 22 Hausman tests show that fixed effects are preferred over random effects.

> 23 There is no statistical difference between the coefficients on the selectivity variables for IDA and TF aid, while coefficients are significantly different between trust fund aid and other aid flows (p‐value=0.002 for GNI p.c. and p‐ value=0.023 for the CPIA score). We run SUR models to test the equality of coefficients using the _suest_ command in Stata.

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