use unit costs per square meter in 1996-1998.<sup>14</sup> Second, we pool across different sources of costs here, so the costs could be estimated, contracted, or actual costs. However, the difference in unit costs of a factor of three to four is unlikely to be due to just differences in the source of costs.<sup>15</sup> We do not have enough observations for narrow work activities within these different cost types to separately show the differences for a large set of countries. To account for systematic differences across cost types, we have also compared the cost of construction projects, after partialling out the effects of cost types in a regression. The order of countries, as well as the range of unit costs, remains substantively the same.

Table 3 lists the variables we use from the ROCKS database and the main additional variables we have compiled. Table S.3 shows the descriptive statistics.<sup>16</sup> Measures of corruption and conflict employed in the empirical literature are to varying degrees subjective measures, based on perceptions of individuals working in the private and public sector. To test whether the results are sensitive to the particular measure employed, we use measures from three sources. If we find patterns that are robust across a range of indicators, we are more confident that the results reflect a particular pattern.

First, our most direct measure for conflict episodes comes from the version 4-2012 of the UCDP/PRIO Armed Conflict Dataset, published by the Uppsala Conflict Data Program (UCDP) and the International Peace Research Institute, Oslo (PRIO).<sup>17</sup> Readers are referred to Gleditsch et al. (2002), Themnér and Wallensteen (2012), and the Dataset Codebook for

> 14Costs per square meter are missing for many observations in 2006–2008, so we only use unit costs of work activities from the earlier period.

> 15Flyvbjerg et al. (2003) find average cost overruns for roads are about 20% for projects in Europe and North America; Alexeeva et al. (2008) find average cost overruns by country for the DRC, Malawi, Tanzania, Mozambique, Ghana, and Nigeria to be between 12.05% and 39.72%; Alexeeva et al. (2011) find average cost overruns by country for Georgia, Serbia, Estonia, Armenia, Macedonia, Albania, Azerbaijan, and Kazakhstan to be between 6% and 47%.

> 16Some variables are not available for the year of the construction project. We therefore distinguish between the following cases: first, if the variable is only available at one point of time we assign the available value to the construction project; second, if the variable is available for at least two years we distinguish between the following three cases: (i) when the construction project took place before the year the variable becomes available, we use data from the first year of the variable; (ii) when the construction project took place after the last time the explanatory variable is recorded, we then use the value of the last available observation; (iii) if the construction project took place in a year for which there are data points both before and after, we linearly interpolate the explanatory variable.

> 17The other potential conflict data set is the Correlates of War data set. Due to concerns over transparency and consistency as well as a high threshold of deaths (Miguel et al. 2004) we prefer the Armed Conflict Dataset (ACD).

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