Towards a core approach for cross-sectional farm household survey data collection: a tiered setup for quantifying key farm and livelihood indicators
There is an urgent need to improve the characterisation of agricultural systems at household level to enable a more efficient assessment of the capacity households to adopt a range of agricultural intervention options. Local drivers and factors need to be identified that might constrain or provide opportunities within a specified agricultural system (Carletto et al., 2015), while on the other hand generalisable standardized characteristics need to be identified that would allow robust comparisons between different systems (Frelat et al., 2016; van Wijk et al., 2014). The assessment of opportunities at smallholder farm household level to improve their livelihoods needs integration of validated standardised agricultural, poverty, nutrition and gender indicators in the quantitative characterisation of these households. This will allow us to assess how these welfare indicators vary across a farm household population and across different agro-ecological and socioeconomic conditions. Such data would also allow us to better assess how they may change over time. Furthering such a standardization across all institutes within the CGIAR (who have been estimated to conduct baseline interviews with around 180,000 farmers per year) would allow for much easier application of big data method applications for analyzing the household level data themselves, as well as for linking these data to other larger scale information sources like spatial crop yield data, climate data, market access data, roadmap data, etc. The Big Data platform of the CGIAR has therefore stimulated an effort to define how a common core of a cross-sectional household survey focusing on rural households could look like, the so-called 100Q exercise (with 100Q standing for 100 Questions that that core should contain). The core survey should deliver key information around the agricultural activities and off farm income of the household, as well as key welfare indicators focusing on poverty, food security, dietary diversity and gender equity. Within this effort a workshop was held in Rome, Italy, in December 2018, where a group of scientists from different centers of the CGIAR and partner institutions discussed how such a core approach for cross-sectional surveys could look, and what type of information should be captured. This report is a short reflection of what was discussed during this workshop, and tries to summarize the overall conclusions of this workshop into core modules of key aspects and indicators of rural farm livelihoods. This information can be used as building blocks for survey development, thereby resulting in more harmonized household survey data collection across CGIAR centers.
Authors
Wijk, Mark T. van; Álvarez, Cristina; Anupama, Guvvala; Arnaud, Elizabeth; Azzarri, Carlo; Burra, Dharani Dhar; Caracciolo, Francesco; Coomes, David A.; Garbero, Alessandra; Gotor, Elisabetta; Heckert, Jessica; Johnson, Nancy L.; Kim, Soonho; Miro, Berta; Muliro, Jacqueline; Shikuku, Kelvin Mashisia; Tyszler, Marcelo; Valdivia, Roberto O.; Viviani, Sara; Vrolijk, Hans; Kruseman, Gideon K.
Citation
van Wijk, Mark; Alvarez, Cristina; Anupama, Guvvala; Arnaud, Elizabeth; Azzarri, Carlo; Burra, Dharani; Caracciolo, Francesco; Coomes, David; Garbero, Alessandra; Gotor, Elisabetta; Heckert, Jessica; Johnson, Nancy; Kim, Soonho; Miro, Berta; Muliro, Jacqueline; Shikuku, Kelvin; Tyszler, Marcelo; Valdivia, Roberto; Viviani, Sara; Vrolijk, Hans & Kruseman, Gideon (2019). Towards a core approach for cross-sectional farm household survey data collection: a tiered setup for quantifying key farm and livelihood indicators. Community of Practice on Socio-economic Data report COPSED-2019-001. CGIAR Platform for Big Data in Agriculture. 32 p.
Keywords
Socio-economic Data; Indicators; Big Data; Livelihoods; Surveys; Gender; Food Security; Dietary Diversity; Household; Data; Farms; Diet
