# 4. **The data set**

The main data set used for this paper is the 1994 Peru LSMS. This is a nationally representative houselhold survey, funded by the World Bank and UNICEF, and executed by the Peruvian think-tank Cuanto. All household interviews were conducted between June and August, 1994. The sample is stratified by region (Lima, and the urban and rural areas of the coast, sierra and selva). The weights across strata are not constant, and expansion factors have to be used to make accurate calculations. Within each stratum, the probability of selection of every household is constant, but standard errors have to be corrected for clustering.

Like similar surveys, the LSMS gathered a wealth of information on, amongst other things, the demographic characteristics, ethnicity, expenditures, income, education, health status, and migration patterns of household members. In addition, there are two questions on volunteering included in the employment module of the survey. The first question, asked of all adults above the age of 15, asks respondents if they performed any tasks "for the benefit of the community" in the last seven days. The follow-up question asks those who volunteered how many hours they dedicated "to all these community activities". The accompanying Surveyor's Manual specifies that the activities in question are those "which were done to improve the village or neighborhood in which the respondents live, or for the benefit of its inhabitants", and lists the construction of bridges and paths, churchl-related activities, and soup kitchens as examples. It also makes clear that only activities which were done "without any payment, in cash or in kind" should be taken into account (Cuanto, 1994, p. _50)._ The answers to the first question about volunteering were recorded with the same codes used throughout the employment module. For example, if a given respondent answered that (s)he had worked repairing the roof of the local health center, the activity would be given one of the codes for "construction".<sup>6</sup> We therefore have a great deal of information about one aspect of the activity performed-we can distinguish whether "construction" involved woodwork, bricklaying, stone masonry, painting-but very little about another-we cannot tell whether repairs were made to the local school, healtlh center, or community center. This makes it impossible to estimate the net benefits from the goods or services produced with volunteer labor.<sup>7</sup>

> 6 When respondents reported that they had voluLnteered for more than one task, the task to which they devoted the greatest amount of time was recorded.

7 To see why this might complicate interpretation of the results, suppose that the poor volunteer more and that local public goods produced with volunteer labor systematically favor poor households. In this case, high rates of volunteering amongs **t** he poor could be a sign of the low opportunity cost of volunteering or of the high benefits they expect to receive, and there will be no way of disentangling the two effects. Is it possible to make a set of reasonable assumptions which would eliminate this problem? Consider two assumptions, either one of which would suffice. First, one could assume that people contribute labor for local public goods primarily because they derive moral satisfaction from contributing, rather than because of the economic value of the goods in question. Such an assumption may not be unreasonable, and is

**6**