Disaggregating data for development: a cost-effective approach to SDG Indicators 2.1.2, 2.3.1 and 2.3.2 in Latin America using small area estimation

Khalil, C.A.; Rahija, M.; Candia Calderon, A.G.; di Candia, S.; Fehrmann, C.; Rodriguez de España, M.; Vargas, G.L.;  Viviani, S.;

Disaggregating data for development: a cost-effective approach to SDG Indicators 2.1.2, 2.3.1 and 2.3.2 in Latin America using small area estimation

Autores

Khalil, C.A.; Rahija, M.; Candia Calderon, A.G.; di Candia, S.; Fehrmann, C.; Rodriguez de España, M.; Vargas, G.L.; Viviani, S.;

Editor

FAO ;

Descripción

This paper presents the experience of the Food and Agriculture Organization of the United Nations (FAO) in providing technical assistance to four countries in Latin America – Brazil, Chile, Colombia and Ecuador – to produce small area estimates for three Sustainable Development Goal (SDG) indicators: SDG Indicator 2.1.2, on the prevalence of moderate and severe food insecurity in the population based on the Food Insecurity Experience Scale (FIES); SDG Indicator 2.3.1, measuring the average value of agricultural production per labour unit; and SDG Indicator 2.3.2, on the average income of small-scale food producers.The paper describes the methodological details and results of the case studies developed, showing how small area estimation can be used to increase the precision of estimates at the subnational level and produce predictions in estimation domains excluded from the sample. It discusses the policy implications of having SDG estimates at the subnational level, and how countries can use this information to formulate programmes and allocate funds. The paper concludes with recommendations on how small area estimation can be incorporated in the processes implemented at the national level to produce agriculture and food security statistics.