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Habtamu K. Benecha

USDA National Agricultural Statistics Service (NASS)



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Denise A. Abreu

USDA National Agricultural Statistics Service



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Jake Abernethy

USDA National Agricultural Statistics Service



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Luca Sartore

National Institute of Statistical Sciences



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Linda J. Young

USDA National Agricultural Statistics Service



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516 – Estimation with Complex Samples

Evaluation of a New Approach for Estimating the Number of U.S. Farms

Sponsor: Survey Research Methods Section
Keywords: Misclassification Error, Area-frame, List-frame, Logistic Regression, Capture-recapture

Habtamu K. Benecha

USDA National Agricultural Statistics Service (NASS)

Denise A. Abreu

USDA National Agricultural Statistics Service

Jake Abernethy

USDA National Agricultural Statistics Service

Luca Sartore

National Institute of Statistical Sciences

Linda J. Young

USDA National Agricultural Statistics Service

USDA’s National Agricultural Statistics Service (NASS) employs the June Area Survey (JAS) to produce annual estimates of U.S. farm numbers. The JAS is an area-frame-based survey conducted every year during the first two weeks of June. NASS also publishes an independent estimate of the number of farms from the quinquennial Census of Agriculture. Studies conducted by NASS have shown that farm number estimates from the JAS can be biased, mainly due to misclassification of agricultural tracts during the pre-screening and data collection processes. To adjust for the bias, NASS has developed a capture-recapture model that uses NASS’s list frame as the second sample, where estimation is performed based on records in the JAS with matches in the list frame. In the current paper, we describe an alternative capture-recapture approach that uses all available data from the JAS and the Census of Agriculture to correct for biases due to misclassification and to produce more stable farm number estimates.

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