# **3 Evidence on the Extent of Corruption versus** **_Grand Corruption_ in Utilities**

Matching theoretical approaches and assumptions, there is considerable evidence that corruption is a significant issue in infrastructure provision. At the operational level, Gulati and Rao (2006) find that, in Bangladesh and Orissa, in India, around 55 percent of generated power is paid for; the rest is lost to technical and commercial losses. Of this, perhaps 15-18 percent is accounted for by ‘true technical’ losses, suggesting leakage due to illegal connections or underbilling accounts for as much as 30 percent of generated power. Davis (2004) suggests that unaccounted for water accounts for 35 percent of total flows in India.

At the statistical level across countries, we have mounting survey evidence regarding petty corruption related to utility provision. Global evidence on the extent of payments for connections to energy, water and electricity are provided by the World Bank’s enterprise surveys, and this can be used to uncover correlations with sector characteristics and outcomes (Clarke and Xu, 2002; Kenny, 2006).

Regarding grand corruption in utility provision, existing data provide an ample basis for casestudy analysis of grand corruption throughout the infrastructure cycle –from policy through construction to operation (see, for example Davis, 2004; Gulati and Rao, 2006; and Cross and Plummer, 2006). For one element of this process –construction—we also have survey evidence. The Business Environment and Enterprise Performance Survey (BEEPS), which covered 4,000 firms in 22 transition countries, provides information about firms’ expenses in various forms of bribery (Hellman et al., 2000). Analysis of these data suggest that construction firms pay considerably more than the average firm in bribes, with a focus on bypassing regulation and obtaining government contracts (Kenny, 2007).

At the same time, existing enterprise surveys have excluded infrastructure providers on the grounds that, at the country level, there are too few firms to guarantee response anonymity or to ensure statistical confidence in answers. This has left analyses of the extent and impact of grand corruption in infrastructure relying on proxy or general measures of corruption. Most widely used in such studies have been general perceptions indices such as Transparency International’s Corruption Perceptions Index (for example Estache, Goicoechea and Trujillo, 2006; Tanzi and Davoodi, 1998).

Cross-country perception indices of corruption have played an important role in raising awareness of corruption and emphasizing the importance of institutions in development. There are strong correlations between governance indices and GDP growth (Kaufmann et al., 2006), and numerous empirical studies point to (perceived) corruption as an important reason for slow economic development (Mauro, 1997; Leite and Weidemann, 1999; Poirson, 1998; Mo, 2001). Studies utilizing general perceptions measures have also provided some interesting suggestive evidence regarding impacts on infrastructure. –Tanzi and Davoodi (1998) find that general corruption perceptions scores are correlated with lower quality infrastructure provision and low expenditures on maintenance. Using a dataset covering 80 electricity distribution firms in 13 Latin American countries in 1994-2001, Bo and Rossi (2007) find corruption to be the most important explanatory factor behind variation in efficiency among the companies. Guasch and Straub (2005) find that perceptions of corruption are linked to an increased likelihood of infrastructure firm-led contract renegotiation in the presence of weak regulatory bodies, also this study was based on data from Latin-America. Estache, Goicoechea and Trujillo (2006) find perceived corruption correlated with lower energy use, and interaction effects between sector policies and the impact of corruption.