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Adjusting economic estimates in business surveys

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  • M. D. Ugarte
  • A. F. Militino
  • T. Goicoa

Abstract

Statistics for small areas within larger regions are recently required for many economic variables. However, when adding the estimates of the small areas within the larger regions, the results do not match up to those obtained with the appropriate estimator originally derived for the larger region. To avoid discrepancies between estimates benchmarking methods are commonly used in practice. In this paper, we discuss the suitability of using a restricted predictor versus a traditional direct calibrated estimator. The results are illustrated with the 2000 Business Survey of the Basque Country, Spain.

Suggested Citation

  • M. D. Ugarte & A. F. Militino & T. Goicoa, 2008. "Adjusting economic estimates in business surveys," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(11), pages 1253-1265.
    • Handle: RePEc:taf:japsta:v:35:y:2008:i:11:p:1253-1265
    DOI: 10.1080/02664760802319709
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    References listed on IDEAS

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    1. Gonzalez-Manteiga, W. & Lombardia, M.J. & Molina, I. & Morales, D. & Santamaria, L., 2007. "Estimation of the mean squared error of predictors of small area linear parameters under a logistic mixed model," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2720-2733, February.
    2. J. Durbin & B. Quenneville, 1997. "Benchmarking by State Space Models," International Statistical Review, International Statistical Institute, vol. 65(1), pages 23-48, April.
    3. Salkever, David S., 1976. "The use of dummy variables to compute predictions, prediction errors, and confidence intervals," Journal of Econometrics, Elsevier, vol. 4(4), pages 393-397, November.
    4. A. F. Militino & M. D. Ugarte & T. Goicoa, 2007. "A BLUP Synthetic Versus an EBLUP Estimator: An Empirical Study of a Small Area Estimation Problem," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(2), pages 153-165.
    5. Pfeffermann, Danny & Barnard, Charles H, 1991. "Some New Estimators for Small-Area Means with Application to the Assessment of Farmland Values," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(1), pages 73-84, January.
    6. Jiming Jiang & P. Lahiri, 2006. "Mixed model prediction and small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 15(1), pages 1-96, June.
    7. 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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    Cited by:

    1. Militino, A.F. & Goicoa, T. & Ugarte, M.D., 2012. "Estimating the percentage of food expenditure in small areas using bias-corrected P-spline based estimators," Computational Statistics & Data Analysis, Elsevier, vol. 56(10), pages 2934-2948.

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