individuals and households, it was based on the National Population Register (NPR) from the 2011 Population Census. The Government of India made the SECC publicly available on the internet in a mix of PDF and Excel formats. See Figure A2 for a de-identified sample page for a single household. We scraped over two million files, parsed the files into text data, and translated these from twelve different Indian languages into English. At the individual level, these data contain variables describing age, gender, occupation, caste group, disability and marital status. Data on occupations are written free-form in the SECC; after translation, we cleaned and matched these descriptions to the 2004 National Classification of Occupations (NCO). Our main occupational variables (share of workers in agriculture and share of workers in non-agricultural manual labor) are based on this classification: agricultural workers are those with NCO single digit code 6 (skilled agricultural workers) or NCO 2 digit 92 (agricultural laborers), while non-agricultural manual laborers are those with NCO single digit code 9 (elementary occupations) excluding those in agriculture (code 92).

At the household level, this dataset contains variables describing housing, landholdings, agricultural assets, household assets and sources of income.

We geocoded and matched these data to our other datasets at the village level. This dataset is unique in describing the economic conditions of every person and household in rural India, at a spatial resolution unavailable from comparable sample surveys.

# **A3 Economic and population censuses**

The Indian Ministry of Statistics and Programme Implementation (MoSPI) conducted the 6th Economic Census in 2013. The Economic Census is a complete enumeration of all economic establishments except those engaged in crop production, defense and government administration. Establishments are any location, commercial or residential, where an economic activity is carried out. There is no minimum firm size, and both formal and informal establishments are enumerated, including people working out of their houses. We obtained the location directory for the Economic Census, and then used a series of fuzzy matching algorithms to match villages and towns by name to the population census of 2011. Employment is defined as the number of workers at the firm on the work day prior to the enumerator’s visit, including casual wage laborers. We aggregate the microdata to the village level to obtain a measure of employment in village nonfarm firms. We use the sum of employment in all firms reported in the 2013 Economic Census to produce an endline measure of nonfarm employment. The Economic Census also reports the sector of the firm, which we use to test for heterogeneous effects across the five largest sectors in our sample (livestock, forestry, manufacturing, retail and education), which together account for 79% of employment in in-village nonfarm firms. For all regressions using this data, we define the outcome variable as _log_ ( _employmenti,v_ +1), where employment is the sum of employment in June and December 2011. However, various delays meant that the majority of the surveying was conducted in 2012, with urban surveys continuing to undergo verification at the time of writing. We therefore use 2012 as the relevant year for the SECC.

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