governance indices aimed to capturing different aspects related to the quality of governance, the presence of corruption within the institutions and the accessibility of public services provided to the citizens.

We begin selecting the survey questions from the public official survey that describe each governance dimension. Table A.1 in the Appendix provides a detailed list of the questions used to construct these indices. Typically, more than one question is used to construct each governance index. In the original survey all questions about individual perceptions were scaled from 1 to 7. We therefore rescaled them from 0 to 100, in order to facilitate percent interpretation (0 always meaning the lowest level of quality of governance, corruption, accessibility or service performance). We then average the responses from public officials working in the same public agency. Finally, for each governance dimension we synthesize the questions into agency-level indices using factor analysis technique.

To capture the idea that the quality of governance and corrupt practices within the same agency may differ in a significant way depending on the geographical location of the agency, we further separate agencies located in different cities and introduce them in the sample as different units of observation, one per region (departamento). This leads to a sample of 161 agency-region observations, and for each one we have constructed a measure of accessibility to public services – the dependent variable – and the governance indices –the explanatory variables.

Since all the data used at the agency-level is based on only public officials’ responses, careful attention must be paid to the possibility of endogeneity biases at the estimation stage. As a first step to address this problem, we thoroughly reviewed and selected the survey questions used in the construction of our variables based on the most objective evaluation by public officials.

Following the literature on the determinants of corruption (Treisman, 2000; Gatti, 2001) we include two additional control variables at the agency-level analysis that in our view may affect also the decision about seeking or not a public service: the regional average household income level and the percentage of the population whose native language is other than Spanish.<sup>10</sup> The idea is that the institutional and economic development of a region may affect access to services and these two variables – the level of regional development and language stratification – have been shown to be significant proxies of these factors. Finally, we include a dummy capturing whether the agencies of the individual respondent are municipal or not, as well as a dummy distinguishing judicial public agencies from other types of institutions. We complete our set of explanatory and control variables by including regional dummies.

Table 3.1 provides the definitions of the dependent variables used at each level of analysis and the survey questions used to construct them. Table 3.2 provides the definitions of the explanatory variables (household characteristics, governance characteristics, corruption and governance indices, and other controls) used in the empirical analysis.

<Table 3.1 around here> <Table 3.2 around here>

> 10 To construct these variables we use the data from the LSMS household survey done for Peru in 2001.

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