Some New Estimators for Small-Area Means with Application to the Assessment of Farmland Values
AbstractRegression 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.
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Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 9 (1991)
Issue (Month): 1 (January)
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Web page: http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main
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- Alex Costa & Albert Satorra & Eva Ventura, 2003. "An Empirical Evaluation of Five Small Area Estimators," General Economics and Teaching 0312003, EconWPA.
- 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, vol. 20(3), pages 574-588, November.
- 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.
- 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.
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