Developing Integer Calibration Weights for Census of Agriculture

Luca Sartore (), Kelly Toppin (), Linda Young () and Clifford Spiegelman ()
Additional contact information
Luca Sartore: National Institute of Statistical Sciences
Kelly Toppin: USDA National Agricultural Statistics Service
Linda Young: USDA National Agricultural Statistics Service
Clifford Spiegelman: USDA National Agricultural Statistics Service

Journal of Agricultural, Biological and Environmental Statistics, 2019, vol. 24, issue 1, No 2, 26-48

Abstract: Abstract When conducting a national survey or census, administrative data may be available that can provide reliable values for some of the variables. Survey and census estimates should be consistent with reliable administrative data. Calibration can be used to improve the estimates by further adjusting the survey weights so that estimates of targeted variables honor bounds obtained from administrative data. The commonly used methods of calibration produce non-integer weights. For the Census of Agriculture, estimates of farms are provided as integers so as to insure consistent estimates at all aggregation levels; thus, the calibrated weights are rounded to integers. The calibration and rounding procedure used for the 2012 Census of Agricultural produced final weights that were substantially different from the survey weights that had been adjusted for under-coverage, non-response, and misclassification. A new method that calibrates and rounds as a single process is provided. The new method produces integer, calibrated weights that tend to be consistent with more calibration targets and are more correlated with the modeled census weights. In addition, the new method is more computationally efficient. Supplementary materials accompanying this paper appear online.

Keywords: Discrete optimization; Coordinate descent; Rounding to integers; Local minimizer; Survey weights estimation; Relative errors (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s13253-018-00340-4

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