<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</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.

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

College of Management, Department of Statistics, Econometrics and Mathematics

Economics and Business Review

This work is licensed under the Creative Commons Attribution 4.0 International License.

In economic studies researchers are often interested in the estimation of the distribution function or certain functions of the distribution function such as...

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

Published Online: Jul 20, 2021

Page range: 97 - 114

Received: Jan 18, 2021

Accepted: Jun 25, 2021

DOI: https://doi.org/10.18559/ebr.2021.2.7

Keywords
quantile, distribution function, small area estimation, survey sampling, linear mixed model, Monte Carlo simulation

© 2021 Tomasz Stachurski, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Published Online: Jul 20, 2021

Page range: 97 - 114

Received: Jan 18, 2021

Accepted: Jun 25, 2021

DOI: https://doi.org/10.18559/ebr.2021.2.7

Keywordsquantile, distribution function, small area estimation, survey sampling, linear mixed model, Monte Carlo simulation

© 2021 Tomasz Stachurski, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
quantile, distribution function, small area estimation, survey sampling, linear mixed model, Monte Carlo simulation