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Model-Based Estimates for Farm Labor Quantities

Author

Listed:
  • Lu Chen

    (National Institute of Statistical Sciences, 1750 K Street NW Suite 1100, Washington, DC 20006, USA
    United States Department of Agriculture, National Agricultural Statistics Service, 1400 Independence Avenue SW, Washington, DC 20250, USA)

  • Nathan B. Cruze

    (NASA Langley Research Center, Mail Stop 290, Hampton, VA 23681, USA)

  • Linda J. Young

    (United States Department of Agriculture, National Agricultural Statistics Service, 1400 Independence Avenue SW, Washington, DC 20250, USA)

Abstract

The United States Department of Agriculture’s (USDA’s) National Agricultural Statistics Service (NASS) conducts the Farm Labor Survey to produce estimates of the number of workers, duration of the workweek, and wage rates for all agricultural workers. Traditionally, expert opinion is used to integrate auxiliary information, such as the previous year’s estimates, with the survey’s direct estimates. Alternatively, implementing small area models for integrating survey estimates with additional sources of information provides more reliable official estimates and valid measures of uncertainty for each type of estimate. In this paper, several hierarchical Bayesian subarea-level models are developed in support of different estimates of interest in the Farm Labor Survey. A 2020 case study illustrates the improvement of the direct survey estimates for areas with small sample sizes by using auxiliary information and borrowing information across areas and subareas. The resulting framework provides a complete set of coherent estimates for all required geographic levels. These methods were incorporated into the official Farm Labor publication for the first time in 2020.

Suggested Citation

  • Lu Chen & Nathan B. Cruze & Linda J. Young, 2022. "Model-Based Estimates for Farm Labor Quantities," Stats, MDPI, vol. 5(3), pages 1-17, August.
    • Handle: RePEc:gam:jstats:v:5:y:2022:i:3:p:43-754:d:879090
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    References listed on IDEAS

    as
    1. Shuchi Goyal & Gauri Sankar Datta & Abhyuday Mandal, 2021. "A Hierarchical Bayes Unit-Level Small Area Estimation Model for Normal Mixture Populations," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 215-241, May.
    2. Andreea L. Erciulescu & Nathan B. Cruze & Balgobin Nandram, 2019. "Model‐based county level crop estimates incorporating auxiliary sources of information," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(1), pages 283-303, January.
    3. Torabi, Mahmoud & Rao, J.N.K., 2014. "On small area estimation under a sub-area level model," Journal of Multivariate Analysis, Elsevier, vol. 127(C), pages 36-55.
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