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Small Area Estimation for Skewed Data in the Presence of Zeroes

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  • Karlberg Forough

Abstract

Skewed distributions with representative outliers pose a problem in many surveys. Various small area prediction approaches for skewed data based on transformation models have been proposed. However, in certain applications of those predictors, the fact that the survey data also contain a non-negligible number of zero-valued observations is sometimes dealt with rather crudely, for instance by arbitrarily adding a constant to each value (to allow zeroes to be considered as “positive observations, only smaller”, instead of acknowledging their qualitatively different nature).

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  • Karlberg Forough, 2015. "Small Area Estimation for Skewed Data in the Presence of Zeroes," Statistics in Transition New Series, Polish Statistical Association, vol. 16(4), pages 541-562, December.
    • Handle: RePEc:vrs:stintr:v:16:y:2015:i:4:p:541-562:n:10
    DOI: 10.21307/stattrans-2015-032
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    References listed on IDEAS

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    1. Ray Chambers & Nikos Tzavidis, 2006. "M-quantile models for small area estimation," Biometrika, Biometrika Trust, vol. 93(2), pages 255-268, June.
    2. Huggett, Mark, 1996. "Wealth distribution in life-cycle economies," Journal of Monetary Economics, Elsevier, vol. 38(3), pages 469-494, December.
    3. Forough Karlberg, 2000. "Population total prediction under a lognormal superpopulation model," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 53-80.
    4. Mincer, Jacob, 1970. "The Distribution of Labor Incomes: A Survey with Special Reference to the Human Capital Approach," Journal of Economic Literature, American Economic Association, vol. 8(1), pages 1-26, March.
    5. Eric V. Slud & Tapabrata Maiti, 2006. "Mean‐squared error estimation in transformed Fay–Herriot models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(2), pages 239-257, April.
    6. Wang, Junyuan & Fuller, Wayne A., 2003. "The Mean Squared Error of Small Area Predictors Constructed With Estimated Area Variances," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 716-723, January.
    7. Jiang, Jiming & Lahiri, P., 2006. "Estimation of Finite Population Domain Means: A Model-Assisted Empirical Best Prediction Approach," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 301-311, March.
    8. Molina, Isabel, 2009. "Uncertainty under a multivariate nested-error regression model with logarithmic transformation," Journal of Multivariate Analysis, Elsevier, vol. 100(5), pages 963-980, May.
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