Dual frame design in agricultural surveys: reviewing roots and methodological perspectives

Claudio Ferraz, F. Mecatti () and J. Torres ()
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F. Mecatti: University of Milano-Bicocca
J. Torres: Federal University of Pernambuco

Statistical Methods & Applications, 2023, vol. 32, issue 2, No 11, 593-617

Abstract: Abstract This paper intends to contribute to an up-to-date discussion of dual frame designs in agricultural surveys. It starts by reviewing historical scenarios of applications to envision new perspectives, and ends by presenting a modern approach to the problem. A dual frame sampling design is proposed that has the appeal of relying on low-cost technological resources. The design has enough generality to allow for applications not only on agricultural but also on rural and environmental surveys, or any other survey related to the use of soil. Unbiased estimations based on domain and multiplicity approaches are presented and their major differences are discussed. Design parameters, design feasibility by different sample size allocations, as well as the statistical performance of several dual frame estimators are investigated using a Monte Carlo simulation study that is built on information from the Brazilian agricultural census of 2006 and FAO’s Global Strategy’s field experiences in the city of Goiana, Pernambuco. The results show dual frames present a gain in precision when compared to a single area frame survey. In addition, the choice of the best design and estimator depends upon scenarios with different types of allocation and different sizes of area frame segments.

Keywords: Area sampling; Area frame; Multiple frame; Multiplicity estimator; Optimum estimator; Screening estimator; Master frame (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10260-022-00669-8

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