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Developing Integer Calibration Weights for Census of Agriculture

  • Luca SartoreEmail author
  • Kelly Toppin
  • Linda Young
  • Clifford Spiegelman
Article
  • 26 Downloads

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 

Supplementary material

13253_2018_340_MOESM1_ESM.zip (21.4 mb)
Supplementary material 1 (zip 21877 KB)

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Copyright information

© International Biometric Society 2018

Authors and Affiliations

  1. 1.National Institute of Statistical SciencesWashingtonUSA
  2. 2.USDA National Agricultural Statistics ServiceWashingtonUSA
  3. 3.Texas A&M UniversityCollege StationUSA

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