where _K_<sup>_^_</sup> _i_<sup>is the predicted knowledge of reporting procedures as defined earlier,</sup><sup>_C_</sup> _j_<sup>and</sup><sup>_S_</sup> _j_<sup>are the mean</sup> levels of corruption and expenditure, and **_R_** _j_ is a vector of regional dummies, all for village _j_ .<sup>3</sup> The rationale for these variables is straightforward: while we expect households’ knowledge on how to report corruption to improve the incentive structure for bureaucrats, higher levels of pre-existing corruption would reduce the level of service quality and dampen the impact of better knowledge. At the same time, higher levels of village wealth are likely to increase the amount of resources available and thus make improvements in service quality more likely. This implies that we expect α _2_ and α _4_ to be positive and α _3_ to be negative.

# **3. Data and descriptive evidence**

Uganda’s second national integrity survey provides evidence on perceptions regarding corruption by firms and public sector employees which are used to illustrate the importance of the issue. We then discuss descriptive statistics from household level data on the extent of bribery, the quality of public service delivery, and knowledge of measures to reduce corruption to provide the background for subsequent econometric investigation.

# **3.1 The Uganda National Integrity Survey**

Our data come from the Second National Integrity Survey which was conducted for the Inspectorate of Government in the second half of 2002 to improve the empirical basis for policies and programmes to assess the incidence of corruption in different institutions and strengthen accountability and the quality of public service provision (Republic of Uganda 2002b). The survey covered 12,190 households in 55 of Uganda’s 56 districts that were in existence at the time the sample was drawn. In addition, an institutional module was administered to 618 private entrepreneurs as well as 480 public sector representatives.

The goal of the _household_ survey was to be representative at the district level. In each district, 20% of the sub-counties were randomly selected, starting with District Headquarters. Within these, two to three local councils (LC1s, the lowest administrative units) and subsequently households were selected randomly. The _public sector_ survey was administered in eight districts – two in each of the country’s four regions: Central, East, West and North.<sup>4</sup> A list of institutions and their respective representatives was drawn up with the goal of interviewing all units responsible for administration of law and order or provision of public services at the national, district, or sub-district level. While the non-response by Ministers at the national level was substantial, the sample is fairly complete at the district and sub-district level, consisting of about 60 interviews for each of the eight districts. For the _private sector_ survey, the database of firms

> 3 In each of these cases, respondents were asked to assess the level of improvement on a 1-5 scale. Table 8 provides results for the determinants of “significant” (top ranking) and “moderate” (second ranking) improvements in each of these sectors.

> 4 These are Kampala, Lira, Mbale/Tororo, Mbarara, Arua, Jinja(Lugazi/Kakira), Masaka and Kasese.

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