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A Two‐level GREG Estimator for Consistent Estimation in Household Surveys

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  • Anne Konrad
  • Jan Pablo Burgard
  • Ralf Münnich

Abstract

Household surveys provide information on both person‐level and household‐level characteristics. To ensure consistent estimates between both levels, statistical offices often use integrated weights that are equal for all persons within a household and the household itself. However, these integrated weights ignore the individual patterns of the persons, and the heterogeneity within a household is no longer reflected. As an alternative to integrated weighting, we propose a two‐level generalised regression estimator that is capable of both ensuring consistent person and household estimates and allowing for different weights for persons within a household. A Monte Carlo simulation supports the superiority of our two‐level generalised regression estimator compared with integrated weighting.

Suggested Citation

  • Anne Konrad & Jan Pablo Burgard & Ralf Münnich, 2021. "A Two‐level GREG Estimator for Consistent Estimation in Household Surveys," International Statistical Review, International Statistical Institute, vol. 89(3), pages 635-656, December.
    • Handle: RePEc:bla:istatr:v:89:y:2021:i:3:p:635-656
    DOI: 10.1111/insr.12460
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    References listed on IDEAS

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    1. Takis Merkouris, 2004. "Combining Independent Regression Estimators From Multiple Surveys," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1131-1139, December.
    2. Jan Pablo Burgard & Jan-Philipp Kolb & Hariolf Merkle & Ralf Münnich, 2017. "Synthetic data for open and reproducible methodological research in social sciences and official statistics," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 11(3), pages 233-244, December.
    3. Nicola Branson & Martin Wittenberg, 2014. "Reweighting South African National Household Survey Data to Create a Consistent Series Over Time: A Cross-Entropy Estimation Approach," South African Journal of Economics, Economic Society of South Africa, vol. 82(1), pages 19-38, March.
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    5. Yves Tillé, 1998. "Estimation in Surveys Using Conditional Inclusion Probabilities: Simple Random Sampling," International Statistical Review, International Statistical Institute, vol. 66(3), pages 303-322, December.
    6. Jan Pablo Burgard & Ralf Münnich & Martin Rupp, 2019. "A Generalized Calibration Approach Ensuring Coherent Estimates with Small Area Constraints," Research Papers in Economics 2019-10, University of Trier, Department of Economics.
    7. Alessio Guandalini & Yves Tillé, 2017. "Design-based Estimators Calibrated on Estimated Totals from Multiple Surveys," International Statistical Review, International Statistical Institute, vol. 85(2), pages 250-269, August.
    8. Denis Devaud & Yves Tillé, 2019. "Deville and Särndal’s calibration: revisiting a 25-years-old successful optimization problem," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(4), pages 1033-1065, December.
    9. Denis Devaud & Yves Tillé, 2019. "Rejoinder on: Deville and Särndal’s calibration: revisiting a 25-year-old successful optimization problem," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(4), pages 1087-1091, December.
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