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Robust estimation of wages in small enterprises: the application to Poland’s districts

Author

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  • Dehnel Grażyna

    (Poznan University of Economics and Business, Department of Statistics, Poznań, Poland .)

  • Wawrowski Łukasz

    (Poznan University of Economics and Business, Department of Statistics, Poznań, Poland .)

Abstract

The paper presents an empirical study designed to test a small area estimation method. The aim of the study is to apply a robust version of the Fay-Herriot model to the estimation of average wages in the small business sector. Unlike the classical Fay-Herriot model, its robust version makes it possible to meet the assumption of normality of random effects under the presence of outliers. Moreover, the use of this version of the Fay-Herriot model helps to improve the precision of estimates, especially in domains where samples are of small sizes. These alternative models are supplied with auxiliary variables. The study seeks to present the characteristics of and differences among small business units cross-classified by selected NACE sections and district units of the provinces of Mazowieckie and Wielkopolskie. It was carried out on the basis of data from a survey conducted by the Statistical Office in Poznan and from administrative registers. It is the first study which attempts to produce estimates of average wages for this sector of the national economy.

Suggested Citation

  • Dehnel Grażyna & Wawrowski Łukasz, 2020. "Robust estimation of wages in small enterprises: the application to Poland’s districts," Statistics in Transition New Series, Statistics Poland, vol. 21(1), pages 137-157, March.
    • Handle: RePEc:vrs:stintr:v:21:y:2020:i:1:p:137-157:n:8
    DOI: 10.21307/stattrans-2020-008
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    References listed on IDEAS

    as
    1. Nikos Tzavidis & Li‐Chun Zhang & Angela Luna & Timo Schmid & Natalia Rojas‐Perilla, 2018. "From start to finish: a framework for the production of small area official statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 927-979, October.
    2. Ray Chambers & Hukum Chandra & Nicola Salvati & Nikos Tzavidis, 2014. "Outlier robust small area estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(1), pages 47-69, January.
    3. María Guadarrama & Isabel Molina & J. N. K. Rao, 2016. "A Comparison Of Small Area Estimation Methods For Poverty Mapping," Statistics in Transition New Series, Polish Statistical Association, vol. 17(1), pages 41-66, March.
    4. repec:csb:stintr:v:17:y:2016:i:1:p:41-66 is not listed on IDEAS
    5. Lumley, Thomas, 2004. "Analysis of Complex Survey Samples," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 9(i08).
    6. Ray Chambers & Nikos Tzavidis, 2006. "M-quantile models for small area estimation," Biometrika, Biometrika Trust, vol. 93(2), pages 255-268, June.
    7. Grażyna Dehnel, 2016. "M-Estimators In Business Statistics," Statistics in Transition New Series, Polish Statistical Association, vol. 17(4), pages 749-762, December.
    8. González-Manteiga, W. & Lombardi­a, M.J. & Molina, I. & Morales, D. & Santamari­a, L., 2008. "Analytic and bootstrap approximations of prediction errors under a multivariate Fay-Herriot model," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5242-5252, August.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    small area estimation; indirect estimation; robust Fay-Herriot model; administrative registers; enterprise statistics;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • M20 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - General

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