This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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411
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Type:
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Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Business and Economic Statistics Section
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Abstract - #307941 |
Title:
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Partially Adaptive Estimation of Truncated Regression Models: A Comparison with Several Semiparametric Estimators
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Author(s):
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Patrick Ansel Turley*+ and James B McDonald
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Companies:
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Brigham Young University and Brigham Young University
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Address:
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Department of Economics, Provo, UT, 84602,
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Keywords:
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truncated regression ;
partially adaptive ;
flexible distributions ;
semi-parametric methods ;
Monte Carlo simulations
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Abstract:
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Applying traditional regression methods or parametric methods (such as OLS or a Tobit-like estimator) to truncated regression models leads to biased and inconsistent estimators when the error distribution is misspecified. This paper proposes using partially adaptive estimators based on flexible error distributions to account for possibly skewed or leptokurtotic errors. Monte Carlo simulations and empirical applications are used to compare the performance of these estimators to several semi-parametric estimators. Preliminary results show improved performance of partially adaptive estimators over the other estimators considered based on the sample RMSE for the data considered.
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