correlation coefficients between the three variables<sup>13</sup> . However, the relation between bank, borrower and project performance is the core behind this investigation and as Figure 2 shows through a three-dimensional scatterplot, there is a remarkable dispersion and variability of projects ratings between these variables, which encourages this research.

In addition to these, we also introduce another available project specific control: the meannormalized size of the project in terms of million dollar value<sup>14</sup> . In addition to this specific control, other country-wide variables are included as well in ( ): GDP per capita (constant 2005 international dollars), from the World Development Indicators (World Bank 2010); the growth rate of income per capita (World Bank 2010) between the years of the project; a measure of volatility, as the standard deviation of GDP per capita (World Bank 2010) during the years of the project, in order to catch the relation between a volatile economy and project performance (Guillamont and Laajaj 2006); an infrastructure index, based on Calderon, Moral-Benito and Serven (2011)<sup>15</sup> ; drawing from the previous literature, democratic accountability (reported from now on as accountability) and government stability (reported as stability); some variables that account for the quality of national administrative institutions, bureaucracy and corruption; last but not least that ethnic tensions (reported as ethnic) and external conflict (reported as ext. conflict) as a solid literature (Easterly and Levine, 1997) proofed their detrimental impact on growth.

These last six institutional variables<sup>16</sup> come from the International Country Risk Guide (Political Risk Services 2010), all of them are measures of risk and are constructed through an inverse index: therefore a low measure of “corruption” means a high risk of corruption and viceversa; therefore zero is the highest corruption risk, while six is the lowest.

> 13 To clarify this refer to Figure 1 and Annex B as they provide a project-per-project sense of how the ratings are correlated in terms of bank and borrower performance through a rich scatterplot.

> 14 W e transform the project sizes in constant 2005 international dollars in order to use inter-temporally comparable figures. In addition to this we normalize the project size according to a cross-country inter-temporal mean (104.68 million 2005 PPP dollars). In this way we measure the elasticity of project outcome to relative size, rather than dollar value and it should allow an easier interpretation

> 15 From Calderon, Moral-Benito and Serven (2011): “We use a principal component procedure to build a synthetic index summarizing different dimensions of infrastructure. We focus on three key infrastructure sectors: telecommunications, power and road transport. This choice is consistent with previous literature on the output impact of infrastructure, which has typically focused on one of these individual sectors, most often telecommunications. The synthetic infrastructure index is the first principal component of three variables measuring the availability of infrastructure services in these three sectors”.

> 16 All of their definitions are available in Annex C.

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