Triple-goal estimation of unemployment rates for U.S. states using the U.S. Current Population Survey data


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Statistics in Transition New Series

Polish Statistical Association

Central Statistical Office of Poland

Subject: Economics, Statistics & Probability


ISSN: 1234-7655
eISSN: 2450-0291





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VOLUME 16 , ISSUE 4 (December 2015) > List of articles

Triple-goal estimation of unemployment rates for U.S. states using the U.S. Current Population Survey data

Daniel Bonnéry * / Yang Cheng * / Neung Soo Ha * / Partha Lahiri *

Keywords : complex survey data, empirical distribution function, Monte Carlo Markov Chain, rank, risk, small area estimation,

Citation Information : Statistics in Transition New Series. Volume 16, Issue 4, Pages 511-522,

License : (CC BY 4.0)

Published Online: 01-November-2017



In this paper, we first develop a triple-goal small area estimation methodology for simultaneous estimation of unemployment rates for U.S. states using the Current Population Survey (CPS) data and a two-level random sampling variance normal model. The main goal of this paper is to illustrate the utility of the triple-goal methodology in generating a single series of unemployment rate estimates for three separate purposes: developing estimates for individual small area means, producing empirical distribution function (EDF) of true small area means, and the ranking of the small areas by true small area means. We achieve our goal using a Monte Carlo simulation experiment and a real data analysis.

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