was not designed for, and would not be suitable for, strongly differentiating levels of corruption within sectors across countries.

Questions are not exact, and open to subjective interpretation. One cannot expect one person in a company to have perfect knowledge of company revenues, contract sizes and, in particular, the size of bribes paid. Furthermore, there are many different types of construction firm, and they will frequently be working with different levels of government or different departments within those levels. But if these factors are what accounts for the variability of responses, it suggests the danger of assuming one indicator can accurately gauge levels of corruption even regarding one distinct activity at the level of the sector (let alone all activities at the level of the country). This suggests the danger of using even survey evidence as an ‘actionable indicator’ of levels of corruption.

Survey responses are likely to be the most plausible method to determine the extent and level of payments linked to petty corruption in infrastructure and grand corruption in construction. At the same time, even answers regarding petty corruption have to be treated with some care. Furthermore, there is significant evidence that corruption payments vary considerably across and within sectors within the same country, suggesting the need for surveys with large enough samples of construction industries and specific enough questions to allow for inter-sectoral analysis. Finally, the firm survey is likely to be an inappropriate instrument to illuminate grand corruption within utility firms, because infrastructure provision tends to be so concentrated.

# **Its Not How Much You Divert, But How You Divert It That Matters**

Even were data on the size and frequency of payments significantly improved, a focus on such payments may underestimate and misplace the economic damage done by corruption in infrastructure projects. One source of mis-estimation is to confuse the financial and economic costs of bribe payments themselves. Payments are not a ‘deadweight loss,’ in that bribe recipients can and do spend the money (this is sometimes how they are caught). More importantly, the major damage done by corruption is probably not the narrow financial loss of bribe payments but the economic cost in terms of skewed spending priorities, along with substandard construction and operation.

Imagine a road project that costs $1 million to build but generates $320,000 in economic returns each year after construction for 10 years. The project’s overall economic rate of return is about 30 percent (the average ERR for World Bank transport projects exiting FY97-02). If the project had suffered from collusive bidding, and this had raised the price of construction by 20 percent, to $1.2 million, the project’s ERR would drop to 26 percent.<sup>22</sup> This is a significant decline, but it still leaves the project at more than double the ‘hurdle rate’ of a 10 percent ERR.<sup>23</sup>

> 22 This (and subsequent calculations) view the corrupt payment as a transfer but accounts for a (high) marginal cost of government funds lost to corruption of 1.50 (a fifty percent deadweight loss).

> 23 This is approximately the economic impact of poor road construction suggested by Olken (2004).

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