Integrating surveys with geospatial data through small area estimation to disaggregate SDG indicators at subnational level: Case study on SDG Indicators 2.3.1 and 2.3.2Food and Agriculture Organization of the United Nations, 20 gen 2023 - 46 pagine The present technical report illustrates a case study on the adoption of small area estimation techniques to produce granular sub-national estimates of SDG Indicators 2.3.1 and 2.3.2, by integrating survey microdata with auxiliary information retrieved from various trustworthy geospatial information systems. The technical report provides practical guidance to national statistical offices and other institutions wanting to implement small area estimation techniques on SDG Indicators 2.3.1 and 2.3.2 or similar indicators based on surveys microdata. |
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1x1 km Annual Agricultural Survey Integrated Agriculture Organization auxiliary information auxiliary variables Bamako Cited 01 December covariates CV of direct data disaggregation data through small Development Goal Indicators Dioila direct and model-based direct estimates Direct Model based disaggregate SDG indicators disaggregation dimensions disaggregation domains EBLUP estimates of SDG estimation to disaggregate FH estimates FH model Food and Agriculture function geospatial data geospatial information systems Households Living Conditions IAEG-SDG implemented indicators at subnational indirect estimation approaches Integrated to Households Integrating surveys Istat Kangaba Khalil Kidal Kolokani linear Living Conditions 2017 Method Direct Model microdata model-based estimates monitoring Target 2.3 Mopti package parameters population Quantile-quantile plots Quantiles random effects residuals and random Rome SAE approaches SAE models SAE techniques SDG Indicators 2.3.1 Shapiro-Wilk test Sikasso small area estimation small-scale food producers study on SDG subnational level surveys with geospatial Sustainable Development Goal UNDESA unit-level models United Nations variable of interest Yélimané