describes how we have interpreted these indicators, adjusted them where appropriate to enhance validity, and aggregated them into several sub-indexes.

In contructing our index, we identified four distinct dimensions of aid quality: selectivity, alignment, harmonization, and specialization. Measurement theory suggests that indicators measuring similar aspects of quality should be grouped together, which is one reason for constructing these subindexes. The four dimensions that we chose emerge from the aid effectiveness literature and from international agreements on aid, but we find that they also hold up empirically. When we categorized indicators using common-sense assignment to the four sub-indexes, we almost inevitably found that the intra- and inter-sub-index correlations confirmed those assignments. In the Results section below, we discuss why these sub-indexes may be useful in their own right, even beyond their utility in building the overall index of aid quality.

# **Aid selectivity**

Aid is widely believed to have greater development impact where it is needed most – that is, where there are large numbers of poor people – and where the policy and institutional environment is favorable to growth and development. The intuition for this belief is difficult to dispute, even if the empirical results in Burnside and Dollar (2000) have not proven very robust. For this reason, both the CGD and Easterly and Pfutze rankings incorporate measures of policy and poverty selectivity in their rankings, and Dollar and Levin (2006) focus solely on these variables in assessing likely trends in aid effectiveness.

For our aid selectivity variables, we compute measures of _policy and poverty selectivity_ using the method of Dollar and Levin (2006). Specifically, we regress the log of aid from donor i to recipient j on three variables for the recipient j: the log of its population, its GDP per capita (adjusted for purchasing power parity), and its overall score on the World Bank's annual "Country Policy and Institutional Assessment" (CPIA). The CPIA consists of 16 indicators ―representing the different policy and institutional dimensions of an effective poverty reduction and growth strategy.‖<sup>4</sup> These 16 indicators, formulated by Bank staff with input from an external panel of prominent development specialists, are grouped into 4 "clusters": macro and fiscal policy, structural policies, social policies, and public sector management (including corruption). The CPIA ratings are produced for the purpose of allocating rhe World Bank’s concessionary (IDA) lending.

This selectivity regression is run separately for each donor. Policy selectivity is measured simply by the partial regression coefficient on the CPIA score, while poverty selectivity is measured by the partial regression coefficient for per capita income (multiplied by -1 so that more positive values indicate better targeting of aid to low-income recipients).<sup>5</sup> Aid disbursements used in these regressions are for 2007, and the three independent variables are measured with a one-year lag, to reflect more accurately the information donors possess when they make their allocations. For most donors, the sample of recipients used in the regressions includes 125 countries. For multilaterals with region-specific mandates, we restrict the sample to eligible countries.<sup>6</sup>

> 4 See http://siteresources.worldbank.org/IDA/Resources/73153-1181752621336/CPIA2008questionnaire.pdf.

> 5 ―Poverty‖ selectivity is measured using GDP per capita as a proxy, because it is available for most aid recipients on an annual basis.  Actual poverty rates are estimated from surveys that are not conducted annually, if at all, in most aid recipients.

> 6 The African, Asian, Inter-American and European regional banks respectively have 50, 33, 23, and 18 eligible aid recipients.  Nielson’s (2010) comparisons across donors of the responsiveness of sectoral aid to indicators of sectoral

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