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Sample Survey Calibration: An Informationtheoretic perspective

Author

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  • Martin Wittenberg

    (School of Economics, University of Cape Town)

Abstract

We show that the pseudo empirical maximum likelihood estimator can be recast as a calibration estimator. The process of estimating the probabilities pk of the distribution function can be done also in a maximum entropy framework. We suggest that a minimum cross-entropy estimator has attractive theoretical properties. A Monte Carlo simulation suggests that this estimator outperforms the PEMLE and the Horvitz-Thompson estimator. This is a joint SALDRU/DataFirst Working Paper as part of the Mellon Data Quality Project. For more information about the project visit www.datafirst.uct.ac.za.

Suggested Citation

  • Martin Wittenberg, 2009. "Sample Survey Calibration: An Informationtheoretic perspective," SALDRU Working Papers 41, Southern Africa Labour and Development Research Unit, University of Cape Town.
    • Handle: RePEc:ldr:wpaper::41
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    References listed on IDEAS

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    1. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    2. Joachim Merz & Henning Stolze, 2008. "Representative time use data and new harmonised calibration of the American Heritage Time Use Data (AHTUD) 1965-1999," electronic International Journal of Time Use Research, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)) and The International Association for Time Use Research (IATUR), vol. 5(1), pages 90-126, November.
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    Cited by:

    1. Laaksonen Seppo & Hämäläinen Auli, 2018. "Joint Response Propensity And Calibration Method," Statistics in Transition New Series, Statistics Poland, vol. 19(1), pages 45-60, March.
    2. 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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    Keywords

    sample weights; calibration; pseudo-empirical maximum likelihood estimation; cross entropy;
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