Donor governments hold the view that international NGOs have an important role to play within the international aid architecture. The share of bilateral official development assistance (ODA) channelled to or through NGOs exceeded 10 per cent in 2005-6 for various OECD countries, notably the Netherlands (19.5 per cent), Switzerland (17.2), and Spain (15.9).1

Overall, the combined budget of international NGOs based in the member countries of the OECD’s Development Assistance Committee (DAC) amounted to almost US$27 billion in 2005 (Gatignon 2007). Notwithstanding the quantitative importance of NGO aid, little is known

about where NGO aid is spent and how well targeted it actually is. If at all, NGO aid is analysed in country-specific studies.2 The literature making use of cross-country regressions is largely confined to ODA, mainly because data constraints typically prevented performing cross-country regressions for NGO aid. For instance OECD/DAC data are seriously deficient with respect to NGO aid at the level of individual recipient countries (Nunnenkamp et al. 2008). This chapter aims to close this empirical gap by compiling and analysing a new dataset on aid allocation, collected for 61 NGOs based in 13 donor countries, and thus rather unique in its coverage. Data were collected from the annual reports of the international NGOs or provided by them on request. The chapter is structured as follows. It commences with a review of

literature, and comes with five propositions as to what determines the cross country choices of NGOs. It continues by describing the data and the multivariate regression methodology. The following section displays the results. Three sets of regression analyses are executed: (1) eligibility stage regressions for the total sample (what determines if NGOs become active somewhere?); (2) level stage regressions for the total sample (what determines how active NGOs become somewhere?); (3) eligibility stage regressions with reduced samples (on the basis of nationality of the NGOs). This chapter comes to a close by a discussion of the findings and a conclusion.