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Some New Estimators for Small-Area Means with Application to the Assessment of Farmland Values

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  • Pfeffermann, Danny
  • Barnard, Charles H

Abstract

Regression models that account for main state effects and nested county effects are considered for the assessment of farmland values. Empirical predictors obtained by replacing the unknown variances in the formula of the optimal predictors by maximum likelihood estimates are presented. The computations are carried out by simple iterations between two SAS procedures. Estimators for the prediction variances are derived, and a modification to secure the robustness of the predictors is proposed. The procedure is applied to data on nonirrigated cropland in the Corn Belt states and is shown to yield predictors with considerably lower predictions mean squared errors than the survey estimators and other regression-type estimators.

Suggested Citation

  • 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.
  • Handle: RePEc:bes:jnlbes:v:9:y:1991:i:1:p:73-84
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    Citations

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    Cited by:

    1. Alex Costa & Albert Satorra & Eva Ventura, 2003. "An Empirical Evaluation of Five Small Area Estimators," General Economics and Teaching 0312003, EconWPA.
    2. G. Datta & M. Ghosh & R. Steorts & J. Maples, 2011. "Bayesian benchmarking with applications to small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(3), pages 574-588, November.
    3. Danny Pfeffermann & Anna Sikov & Richard Tiller, 2014. "Single- and two-stage cross-sectional and time series benchmarking procedures for small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(4), pages 631-666, December.
    4. Àlex Costa & Albert Satorra & Eva Ventura, 2003. "An empirical evaluation of small area estimators," Economics Working Papers 674, Department of Economics and Business, Universitat Pompeu Fabra, revised Jun 2003.
    5. Malay Ghosh & Tatsuya Kubokawa & Yuki Kawakubo, 2014. "Benchmarked Empirical Bayes Methods in Multiplicative Area-level Models with Risk Evaluation," CIRJE F-Series CIRJE-F-918, CIRJE, Faculty of Economics, University of Tokyo.
    6. Àlex Costa & Albert Satorra & Eva Ventura, 2001. "Estimadores compuestos en estadística regional: aplicación para la tasa de variación de la ocupación en la industria," Economics Working Papers 590, Department of Economics and Business, Universitat Pompeu Fabra.
    7. repec:spr:stmapp:v:26:y:2017:i:4:d:10.1007_s10260-017-0379-x is not listed on IDEAS
    8. 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.
    9. María José Lombardía & Stefan Sperlich, 2008. "Semiparametric inference in generalized mixed effects models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(5), pages 913-930.

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