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Small area quantile estimation based on distribution function using linear mixed models

Author

Listed:
  • Stachurski Tomasz

    (University of Economics in Katowice, College of Management, Department of Statistics, Econometrics and Mathematics, ul. 1 Maja 50, 40-287 Katowice)

Abstract

In economic studies researchers are often interested in the estimation of the distribution function or certain functions of the distribution function such as quantiles. This work focuses on the estimation quantiles as inverses of the estimates of the distribution function in the presence of auxiliary information that is correlated with the study variable. In the paper a plug-in estimator of the distribution function is proposed which is used to obtain quantiles in the population and in the small areas. Performance of the proposed method is compared with other estimators of the distribution function and quantiles using the simulation study. The obtained results show that the proposed method usually has smaller relative biases and relative RMSE comparing to other methods of obtaining quantiles based on inverting the distribution function.

Suggested Citation

  • Stachurski Tomasz, 2021. "Small area quantile estimation based on distribution function using linear mixed models," Economics and Business Review, Sciendo, vol. 7(2), pages 97-114, June.
    • Handle: RePEc:vrs:ecobur:v:7:y:2021:i:2:p:97-114:n:3
    DOI: 10.18559/ebr.2021.2.7
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    References listed on IDEAS

    as
    1. Molina, Isabel & Rao, J.N.K., 2009. "Small area estimation on poverty indicators," DES - Working Papers. Statistics and Econometrics. WS ws091505, Universidad Carlos III de Madrid. Departamento de Estadística.
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    More about this item

    Keywords

    quantile; distribution function; small area estimation; survey sampling; linear mixed model; Monte Carlo simulation;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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