significantly different from each other.<sup>13</sup> This may well reflect different interpretation of the intermediate categories (mostly, frequently, sometimes, seldom), but it is also likely to reflect the fact that different types of firm in different parts of the country face different risk of infrastructure corruption victimization. As a result, while there is undoubtedly useful information in these survey responses regarding petty corruption in infrastructure that can be used for econometric analysis, this set of answers would not be suitable to determine differing policy positions or prescriptions at the sector level between countries.

Uncertainty or within-country variation in response as well as, perhaps, the limited development impact of petty corruption in infrastructure, may account for the apparently weak relationship between surveyed petty corruption levels and infrastructure outcomes. Table 7 reports on correlations between answers to Business Environment Survey questions (the percentage of firms who say gifts are required for connections to infrastructure) and sectoral outcome indicators controlling for GDP per capita. There is a positive and significant link between the reported extent of petty corruption in telecommunications and the waiting list for a telephone mainline. Otherwise, the relationship between our indicators of infrastructure outcomes and measures of petty corruption are insignificant.<sup>14</sup> It should be emphasized that all of these results cover a very small number of observations (11-23 countries). Nonetheless, based on the data we have and as with earlier studies linking general corruption perceptions measures to infrastructure outcomes, infrastructure-specific survey measures of petty corruption also appear to be weakly related to outcomes. We will see that this may be in part because the form of petty corruption caught by such surveys may be some of the least damaging in terms of outcomes.

# **How Much Can Surveys Tell Us about Grand Corruption?**

The approach of surveying firms which are likely to be directly involved in grand corruption again appears likely to produce more accurate measures than perceptions indices.

Once more, there remain difficulties with these surveys too, however. Not least is the issue of honest and accurate reporting. Direct questions asking business owners to estimate the percent of their own costs that are accounted for by bribe payments can illicit considerably different responses as a result of these problems. Henderson and Kuncoro

> 13 The average of within-country standard deviations is 1.2 compared to the standard deviation of country averages which is 0.4.

> 14 Although there are better dependent variables for water, and non-technical losses would be a better dependent variable for electricity (again, this is not available for as many countries).  We also have some (very) preliminary evidence of a link between estimates of corruption in construction and infrastructure outcomes for roads from Investment Climate Survey data.  Table 2 reports that average percentages reported for the value of a gift required to secure a government contract reported by investment climate surveys is negatively and significantly correlated with the percentage of a country’s roads which are paved after controlling for GDP per capita.  Once more, this is a weak proxy for quality, but available for more countries than better measures.  Source: http://iresearch.worldbank.org/ics/jsp/index.jsp.

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