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Author
Bonnéry Daniel (University of Maryland), Rheng Yung (U.S. Census Bureau), Ha Neung Soo (Nielsen), Luhiri Partha (University of Maryland)
Title
Triple-goal Estimation of Unemployment Rates for U.S. States Using the U.S. Current Population Survey Data
Source
Statistics in Transition, 2015, vol. 16, nr 4, s. 511-522, rys., tab., bibliogr. s. 520-521
Issue title
The Measurement of Subjective Well-Being in Survey Research
Keyword
Statystyka małych obszarów, Łańcuch Markowa, Symulacja Monte Carlo, Ryzyko, Analiza danych
Small area estimates, Markov chain, Monte Carlo simulation, Risk, Data analysis
Note
summ.
Materiały z międzynarodowej konferencji Small Area Estimation (SAE 2014), Poznań.
Country
Stany Zjednoczone Ameryki
United States of America (USA)
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. (original abstract)
Accessibility
The Main Library of the Cracow University of Economics
The Library of Warsaw School of Economics
The Library of University of Economics in Katowice
The Main Library of the Wroclaw University of Economics
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Bibliography
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  1. CONLON, E. M. and LOUIS, T. A. (1999). Addressing Multiple Goals in Evaluating Region-specific Risk Using Bayesian Methods. In Disease Mapping and Risk Assessment for Public Health, Chichester: Wiley, 31-47.
  2. DEVINE, O. J. and LOUIS, T. A. (1994). A Constrained Empirical Bayes Estimator for Incidence Rates in Areas with Small Populations. Statistics in Medicine, 13,1119-1133.
  3. EFRON, B. and MORRIS, C. (1975). Data Analysis Using Stein's Estimator and Its Generalizations. Journal of the American Statistical Association, 70, 311319.
  4. GELMAN, A. and PRICE, P. N. (1999). All Maps of Parameter Estimates are Misleading. Statistics in Medicine, 18, 3221-3234.
  5. GHOSH, M. (1992). Constrained Bayes Estimation with Applications. Journal of the American Statistical Association, 87, 533-540.
  6. GOLDSTEIN, H. and SPIEGELHALTER, D. J. (1996). League Tables and Their Limitations: Statistical Issues in Comparisons of Institutional Performance. Journal of Royal Statistical Society, Series A., 159, 385-409.
  7. GURNEY, M. and DALY, J. F. (1965). A Multivariate Approach to the Estimation in Periodic Sample Surveys. In Proceeding- of the Social Statistics Section, ALA., 242-257.
  8. HA, N. S., LAHIRI, P., and PARSONS, P. (2014). Methods and Results for Small Area Estimation Using Smoking Data from The 2008 National Health Interview Survey. Statistics- in Medicine, 33, 3932-3945.
  9. JIANG, J. and LAHIRI, P. (2006). Mixed Model Prediction and Small Area Estimation. Test, 15, 111-999.
  10. LAHIRI, P. (1990). Adjusted Bayes and Empirical Bayes Estimation in Population Sampling. Lankhya, 52, 50-66.
  11. LAIRD, N. M. and LOUIS, T. A. (1989). Empirical Bayes Ranking Methods. Journal of Educational Statistics 14, 29-46.
  12. LANDRUM, M. B., BRONSKILL, S. E., and NORMAND, S. (2000). Analytic Methods for Constructing Cross-Sectional Profiles of Health Care Providers Health Services Outcomes Research Methodology, 1, 23- 47.
  13. LENT, J., MILLER, S., CANTWELL, P., and DUFF, M. (1999). Effects of composite weights Current Population Survey. Journal of Official Statistics 15, 431-448.
  14. LIU, B., LAHIRI, P., and KALTON, G. (2014). Hierarchical Bayes Modeling of Survey-Weighted Small Area Proportions. Survey Methodology, 40, 1-13.
  15. LOUIS, T. (1984). Estimating a Population of Parameter Values Using Bayes and Empirical Bayes Methods. Journal of the American Statistical Association, 79, 393- 398.
  16. PFEFFERMANN, D. (2013). New Important Developments in Small Area Estimation. Statistical Science, 28, 1, 40- 68
  17. PFEFFERMANN, D. and TILLER, R. B. (2006). Small Area Estimation With State-Space Models Subject to Benchmark Constraints. Journal of the American Statistical Association, 101, 1387-1397.
  18. RAO, J. N. K. (2003). Small Area Estimation.. Wiley Series in Survey Methodology, Hoboken: NJ.
  19. SHEN, W. and LOUIS, T. (1998). Triple-Goal Estimates in Two-Stage Hierarchical Models. Journal of Royal Statistical Society, Serie- B., 60, 455-471.
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ISSN
1234-7655
Language
eng
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