The Tamil Nadu Social Network Mapping Survey (SNM) is a unique social network dataset assembled during 2014-16 from 111 villages across four districts in the South Indian state of Tamil Nadu, India. These four districts cover a population of 2.5 million people. The sample is largely representative of rural Tamil Nadu. Tamil Nadu is among India's richer states, and this is reflected in lower fertility rates and higher literacy rates relative to countrywide averages. The districts in the SNM survey sample are slightly richer than average and this is reflected in our study sample having a more literate population and slightly lower scheduled caste population. Tamil Nadu has lower tribal populations than the average Indian state, and the sample has a lower caste (scheduled caste) population that is more representative of the Indian average.
The SNM dataset is particularly well suited for the network research. First, the network data for 111 independent villages meet some assumptions required to make valid statistical inferences with this type of data. Second, complete network data exist on both financial and social connections for almost all households in every village. Third, there are data on both within-village contacts and outside-village contacts, which is very rare. Finally, the dataset includes detailed measures from all households on self-assessed well-being, income and wealth, public good provision and community participation, which is unique in the context of network mapping datasets.
These data were collected in conjunction with a large-scale impact evaluation of access to formal financial services. The final sample of villages was randomly drawn based on identified service areas of our implementing financial institution partner. The sample was randomly drawn within the villages having 40 to 250 households in the four study districts, excluding the designated branch locations. Beginning in 2014, a social network mapping survey (SNM) was administered in this randomly chosen subset of 111 villages of the four districts. To accomplish this, a census of households was undertaken in selected villages, listing members of all households who are at least 18 years old. This census data was used to create an electronic directory of each study village that included photographs of each residence that could be used to verify respondents reported network links in the network mapping exercise.
The network survey was administered to both the head and spouse of each household. To map the full network of social and financial connections within each sampled village, respondents were asked to list their social and financial contacts both within and outside the village. Specifically, they were asked to identify all individuals within the village with whom they: (i) spend leisure time; (ii) could borrow money in case of emergency; and (iii) could borrow to finance a business investment. In addition, respondents were asked to list all individuals living outside of the village from whom they could borrow money in case of emergency. In addition to naming each link both inside and outside the village, respondents were asked to name: their relationship to the named contact (friend, family, employer, moneylender); the actual amount borrowed from each contact; the amount they could borrow from each contact in case of emergency; the amount they could borrow from each contact to finance a business investment; and the number of contact days with each link (out of past 7). For outside links, respondents were also asked the distance to each contact (whether the link lives within walking distance, same Panchayat, same district or outside Tamil Nadu). The information on outside contacts was collected in 97 villages.
To complement the social network mapping data, two additional surveys were implemented in the sample villages. First, in all 111 villages, all household in the village completed a survey on the following topics: labor, income, land ownership, community leadership and risk aversion. Second, in each village, 20% of households were randomly chosen to complete two rounds of more detailed surveys covering several topics related to household socio-economic status, including incomes and assets, labor market participation, and health and well-being. The survey also collects information on financial ties (actual and potential transfers) and social connections (socialization and leisure time) among respondents.
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