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

Author

Listed:
  • Yang Cheng

  • Partha Lahiri

  • Neung Soo Ha

  • Daniel Bonnéry

Abstract

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.

Suggested Citation

  • Yang Cheng & Partha Lahiri & Neung Soo Ha & Daniel Bonnéry, 2015. "Triple-goal estimation of unemployment rates for U.S. states using the U.S. Current Population Survey data," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 16(4), pages 511-522, December.
    • Handle: RePEc:csb:stintr:v:16:y:2015:i:4:p:511-522
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    References listed on IDEAS

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    1. Harvey Goldstein & David J. Spiegelhalter, 1996. "League Tables and Their Limitations: Statistical Issues in Comparisons of Institutional Performance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(3), pages 385-409, May.
    2. Pfeffermann, Danny & Tiller, Richard, 2006. "Small-Area Estimation With StateSpace Models Subject to Benchmark Constraints," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1387-1397, December.
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