Primary Survey Socioeconomic Dataset of the Study on Agricultural Performance and Farm Size: Village Dynamics in South Asia (VDSA)

These datasets contain many economic variables related to agriculture like crop output value, profit and several others.   These datasets can be used for testing several hypotheses related to agricultural economics, both at plot level and household level.

Users can also reproduce these datasets using the STATA 14 do file ‘VDSA data management for agricultural performance’. This STATA program file uses the Village Dynamics in South Asia (VDSA) raw data files in excel format. The resulting output will be two data files in stata format, one at plot level and other at household level. 

These plot level and household level data sets are also included in this repository.   The word file ‘guidelines’ contain instructions to extract VDSA raw data from VDSA knowledge bank and use them as inputs to run the STATA do file ‘VDSA data management for agricultural performance’  

The VDSA raw data files in excel format needed to run the stata do file are also available in this repository for users convenience

The raw VDSA data were generated by the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in partnership with Indian Council of Agricultural Research (ICAR) Institutes and the International Rice Research Institute (IRRI) and funded by the Bill & Melinda Gates Foundation (BMGF) (Grant ID: 51937).  The data were acquired in surveys by resident field investigators. Data collection was mostly through paper based questionnaires and Samsung tablets were also used since 2012. The survey instruments used for different modules are available at http://vdsa.icrisat.ac.in/vdsa-questionaires.aspx

Study sites were selected using a stepwise purposive sampling covering agro-ecological diversity of the region. Three districts within each zone were selected based on soil, climate parameters as well as the share of agricultural land under ICRISAT mandate crops. On similar lines, one typical sub-district within each district and two villages within each sub-district were selected. Within each village, ten random households from four landholding groups were selected.

Selected farmers were visited by well trained, agriculture graduate, resident field investigators, once every three weeks to collect information related to various socioeconomic indicators. Some of the data modules like details on crop cultivation activities including plot wise input, output was collected every three weeks while others like general endowments were collected once at the beginning of every agricultural year. 

The compiled data, source data, data descriptions and data management code are all published in a public repository at http://dataverse.icrisat.org/dataverse/socialscience at  https://doi.org/10.21421/D2/HDEUKU]

Some of the several benefits of these data are:

• Scientists, students, development practitioners can benefit from these data to track changes in the livelihood options of the rural poor as this data provides long-term, multi-generational perspective on agricultural, social and economic change in rural livelihoods.
• The survey sites provide a socio-economic field laboratory for teaching and training students and researchers
• This dataset can be used for diverse agricultural, development and socio-economic analysis and to better understand the dynamics of Indian agriculture.
• The data helps to provide feedback for designing policy interventions, setting research priorities and refining technologies.
• Shed light on the pathways in which new technologies, policies, and programs impact poverty, village economies, and societies