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Year of publication
Subject
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bias correction 3 finite sample moments 3 Nagar approximation 2 OLS bias 2 and the estimated bias is small and statistically insignificant 1 but has a higher MSE. A hypothesis test is given for the presence of this bias. The techniques are applied to survey data on food expenditure 1 but not always. In simulations 1 efficiency gains 1 higher-order asymptotic expansions 1 jackknife and pairs bootstrap methods are equal to Op(n-3/2). Sometimes they are effective at lowering bias and MSE 1 lagged dependent variables 1 pairs bootstrap 1 pairs bootstrap The O(n-1) bias and O(n-2) MSE of OLS are derived for iid samples. An approach is suggested for handling nonexistent finite sample moments. Bias corrections based on plug-in 1 size improvement 1 the bootstrap correction removes more bias than the others 1 weighting 1
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Online availability
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Free 3
Type of publication
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Book / Working Paper 3
Language
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English 2 Undetermined 1
Author
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Magee, Lonnie 2 KIVIET, Jan F. 1 PHILLIPS, Garry D.A. 1
Institution
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Department of Economics, McMaster University 2 Division of Economics, Nanyang Technological University 1
Published in...
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Economic Growth Centre Working Paper Series 1 Quantitative Studies in Economics and Population Research Reports 1 Social and Economic Dimensions of an Aging Population Research Papers 1
Source
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RePEc 3
Showing 1 - 3 of 3
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Ordinary Least Squares Bias and Bias Corrections for <em>iid</em> Samples
Magee, Lonnie - Department of Economics, McMaster University - 2007
nonexistent finite sample moments. Bias corrections based on plug-in, weighting, jackknife and pairs bootstrap methods are equal … insignificant. Key words: OLS bias; finite sample moments; Nagar approximation; bias correction; pairs bootstrap JEL …
Persistent link: https://www.econbiz.de/10005181112
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Improved Variance Estimation of Maximum Likelihood Estimators in Stable First-Order Dynamic Regression Models
KIVIET, Jan F.; PHILLIPS, Garry D.A. - Division of Economics, Nanyang Technological University - 2012
In dynamic regression models conditional maximum likelihood (least-squares) coefficient and variance estimators are biased. From expansions of the coefficient variance and its estimator we obtain an approximation to the bias in variance es- timation and a bias corrected variance estimator, for...
Persistent link: https://www.econbiz.de/10010927739
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Cover Image
Ordinary Least Squares Bias and Bias Corrections for iid Samples
Magee, Lonnie - Department of Economics, McMaster University - 2007
finite sample moments. Bias corrections based on plug-in, weighting, jackknife and pairs bootstrap methods are equal to Op …
Persistent link: https://www.econbiz.de/10005181076
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