Model-Based Estimates for Farm Labor Quantities

• Activity Number: 403 - Recent Advances in Small Area Estimation
• Type: Topic-Contributed
• Date/Time: Thursday, August 12, 2021 : 2:00 PM to 3:50 PM
• Sponsor: Survey Research Methods Section
• Author(s): Lu Chen* and Nathan B. Cruze and Linda J Young
• Companies: National Institute of Statistical Sciences/USDA, NASS and NASS, USDA and USDA National Agricultural Statistics Service
• Keywords: Auxiliary Information; Agricultural Statistics; Hierarchical Bayes; Small Area Estimation

Abstract

United States Department of Agriculture’s National Agricultural Statistics Service conducts the Farm Labor Survey to produce estimates of numbers of workers, duration of workweek, and wage rates. In the traditional process, the survey estimates at different levels are reviewed by the Regional Field Offices, headquarter statisticians, and finally by the Agricultural Statistics Board (ASB). The ASB considers the relationship between current year survey estimates and previous year official values. Alternatively, implementing small area models for integrating survey estimates with additional sources of information provides more reliable official estimates and quantifies the uncertainty associated with each type of estimate. In this paper, several hierarchical Bayesian sub-area level models are developed in support of different estimates of interest in the Farm Labor Labor Survey. A 2019 case study illustrates the improvement of the direct survey estimates for areas with small sample sizes by using auxiliary information and by borrowing information across areas and sub-areas. The resulting framework provides a complete set of coherent estimates for all required geographic levels.