similarities. The district and block sampling is less relevant for this paper and is described in more detail in Besley _et_ al. (2005.) Each block consists of several GPs, which in turn have between 1 and 6 villages depending on the state. From each sampled block, in the states of AP, KA and TN, we randomly sampled 6 GPs in every block. In Kerala the population per GP is roughly double that in the other three states. For this reason in Kerala we sampled 3 GPs in every block. This procedure gave us a total of 201 GPs. From these we selected a village sample. In AP, Karnataka and Tamil Nadu we sampled all villages if the GP had 3 or fewer villages. If it had more than three villages, then we selected the GP head’s village and randomly selected two other villages. We excluded all villages with less than 200 persons from our sampling frame. All hamlets with population over 200 were considered as independent villages in drawing the sample. In Kerala we directly sampled wards instead of villages (as villages in Kerala tend to be very large) -- we sampled 6 wards per GP. This gave us a final village sample size of 527<sup>7</sup> villages. For sampled villages, any associated hamlets were also included as part of the sample.

# **3.2. Data collection**

The information about the sanitation outcomes was collected in 2003 through (1) questionnaires administered to Gram Panchayat members and (2) direct observation of the condition of the roads by field investigators. The questionnaires collected data on the frequency of actions regarding public health and sanitation and on the allocation of responsibility for these tasks. We specified a list of sanitation measures, and asked the Gram Panchayat members who was responsible for carrying them out, and whether these were ever done in the village. Tables 1 and 2 summarize this information. To collect the direct observation data, our investigators first constructed detailed maps of the village showing all the roads and paths. They then assessed the condition of each road along the dimensions detailed in Table 3, and noted the characteristics of the inhabitants by the side of that road. In particular they noted the caste and religion of the inhabitants, whether they were GP members, and whether important village institutions such as schools, health centers, were by the side of the road. Compared with the respondents’ reported perception of whether a task was ever done, the direct observation data give us much more objective information on the actual sanitary conditions on the ground.

In addition to the sanitation outcomes, we have additional village-level information, collected in a previous survey conducted the previous year in 2002. This information was collected from the official census (population, literacy, area), interviews with GP members (whether the village is the GP headquarter and whether the village is the GP president’s village), and from participatory appraisal methods (the fraction Scheduled Castes/Tribes in the village, the fraction land owned by the upper castes, and oligarchy – the extent to which the GP members control the important functions in the village.)

# **4. Analytical Methods**

To analyze the determinants of information about GP responsibilities we use the village level data. To examine the inter- and intra-village distribution of sanitation outcomes we use the road level dataset onto which we merged the village level information. Hence, the unit of observation

> 7 The state-wise break up is AP: 69 villages, KA: 182 villages, KE: 126 wards; TN 129 villages.

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