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Doubly Robust-type Estimation of Population Moments and Parameters in Biased Sampling

Author

Listed:
  • Takahiro Hoshino

    (Faculty of Ecoomics, Keio University)

  • Yuya Shimizu

    (Graduate School of Economics, Keio University)

Abstract

We propose an estimation method of population moments or population parameters in "biased sampling data" in which for some units of data, not only the variable of interest but also the covariates, have missing observations and the proportion of "missingness" is unknown. We use auxiliary information such as the distribution of covariates or their moments in random sampling data in order to correct the bias. Moreover, with additional assumptions, we can correct the bias even if we have only the moment information of covariates. The main contribution of this paper is the development of a doubly robust-type estimator for biased sampling data. This method provides a consistent estimator if either the regression function or the assignment mechanism is correctly specified. We prove the consistency and semi-parametric efficiency of the doubly robust estimator. Both the simulation and empirical application results demonstrate that the proposed estimation method is more robust than existing methods.

Suggested Citation

  • Takahiro Hoshino & Yuya Shimizu, 2019. "Doubly Robust-type Estimation of Population Moments and Parameters in Biased Sampling," Keio-IES Discussion Paper Series 2019-006, Institute for Economics Studies, Keio University.
    • Handle: RePEc:keo:dpaper:2019-006
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    References listed on IDEAS

    as
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    4. Keisuke Hirano & Guido W. Imbens & Geert Ridder & Donald B. Rubin, 2001. "Combining Panel Data Sets with Attrition and Refreshment Samples," Econometrica, Econometric Society, vol. 69(6), pages 1645-1659, November.
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    6. Nevo, Aviv, 2003. "Using Weights to Adjust for Sample Selection When Auxiliary Information Is Available," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 43-52, January.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Auxiliary information; Biased sampling; Missing data; Propensity score; Doubly robust estimator;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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