high corruption in their industry (Table 9).<sup>19</sup> These results are highly statistically significant, again suggesting the utility of the survey approach.

At the same time, the BEEPS survey was not designed to provide a large dataset for exploring construction alone, and it is perhaps unsurprising that, partially as a result, evidence regarding the variation in corruption across countries in the sector is not strong. As we have seen, one of the BEEPS questions is “when firms in your industry do business with the government, how much of the contract value would they typically offer in additional or unofficial payments to secure the contract?” Answers, expressed as a range of percentages of the contract value, are on a six point scale from zero to above twenty percent. Taking construction firms in the 1999-2000 BEEPS dataset which answered this question, we can see how much the answers tell us about sector-level corruption using country dummies. All but nine firms out of 143 report some level of bribery. How much of the variation in estimates of industry corruption by firms in this industry across countries is explained by which country the respondent is in? If construction firms were perfectly informed about the typical level of corrupt payments to government in their industry in their country and they understood and answered the question in the same way, we would expect 100 percent of the variation in answers to be explained by the country of residence of the respondent. In fact, around 14 percent of the variation can be explained, and none of the country dummies is statistically significant (Table 10, see Figure Four for Cross-Country variation compared to standard deviations).<sup>20</sup> This performance is similar if we limit the analysis to private firms or to private firms which deal with the government.

A similar finding applies to the answer to the question “how often do firms like yours nowadays need to make extra, unofficial payments to government officials to gain government contracts?’ –which is available for a considerably larger number of firms (Table 11). The variation explained by country dummies, which one would hope to be very high, is in fact very low (with an R-squared of 0.1). The results apply even if we remove those firms that say companies never pay such bribes, suggesting that reticence about reporting such behavior does not lie behind the result. Overall, this suggests that we can say little with statistical confidence about which countries in the 1999 BEEPS dataset have more corrupt construction industries than average based on questions asking construction firms themselves how corrupt their industry is.

It should be noted that the variation will be large enough to show that construction in Azerbaijan (the worst performer) is significantly more corrupt than the best countries (Uzbekistan, Poland and Estonia).<sup>21</sup> And the survey results are useful for further econometric analysis of the causes and consequences of corruption. However, the survey

> 19 Although within a subsample of construction industry firms, it appears that firms that do not deal with the government estimate the size of bribes paid on government contracts as being significantly smaller than do firms who deal with the government.

> 20 The F-stat. is 1.43

> 21 It is also worth noting that this situation may be considerably better with the larger samples of the 2005 dataset.

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