Activity Number:
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107
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Type:
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Contributed
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Date/Time:
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Monday, August 12, 2002 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Survey Research Methods*
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Abstract - #301742 |
Title:
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A Weighted Jackknife Method in Small-area Estimation
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Author(s):
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Shijie Chen*+ and Partha Lahiri
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Affiliation(s):
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RTI International and University of Nebraska/Univ. of Maryland
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Address:
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3040 Cornwallis Road, Research Triangle Park, North Carolina, 27709, USA
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Keywords:
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small-area estimation ; Jackknife ; weighted ; Fay-Herriot ; SAIPE
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Abstract:
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In this paper, we consider a weighted jackknife method to estimate the mean square error (MSE) of empirical best linear unbiased predictor (EBLUP) of a small-area mean for the well-celebrated Fay-Herriot model. The proposed MSE estimator improves on the existing MSE estimators and is robust under a variety of situations. For example, the proposed MSE estimator performs better than the corresponding Taylor series MSE estimator when the number of small-areas is small or when for a particular small-area the model mean differs from the actual observations considerably. We illustrate our methodology for the U. S. Census Bureau's SAIPE program.
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