Model‐based county level crop estimates incorporating auxiliary sources of information
In 2011, USDA’s National Agricultural Statistics Service started the complete implementation of the County Agricultural Production Survey (CAPS). CAPS is an annual survey to provide accurate county-level acreage and production estimates of approved federal and state crop commodities. The current top-down method of producing official county-level estimates that satisfy the countydistrict-state benchmarking constraint is an expert assessment incorporating multiple sources of information. We propose a model-based method that combines the CAPS survey acreage data with auxiliary data and improves county-level survey estimation, while providing measures of uncertainty for the county-level acreage estimates. Auxiliary sources of information include remote sensing, weather data, and planted acreage administrative data from other USDA agencies. A novel hierarchical Bayesian subarea-level model is proposed and implemented, with an additional hierarchical level for the sampling variances. County-level model-based acreage estimates have lower coefficients of variation than the corresponding county-level survey acreage estimates. Top-down benchmarking methods are investigated and the final acreage estimates satisfy the county-districtstate benchmarking constraint.