Jackknife estimation with a unit root
Jackknife estimation with a unit root
We study jackknife estimators in a first-order autoregression with a unit root. Non-overlapping sub-sample estimators have different limit distributions, so the jackknife does not fully eliminate first-order bias. We therefore derive explicit limit distributions of the numerator and denominator to calculate the expectations that determine optimal jackknife weights. Simulations show that the resulting jackknife estimator produces substantial reductions in bias and RMSE
1677-1682
Chambers, Marcus J.
6591c606-5ed7-409f-a741-77d1a13e9c39
Kyriacou, Maria
6234587e-81f1-4e1d-941d-395996f8bda7
July 2013
Chambers, Marcus J.
6591c606-5ed7-409f-a741-77d1a13e9c39
Kyriacou, Maria
6234587e-81f1-4e1d-941d-395996f8bda7
Chambers, Marcus J. and Kyriacou, Maria
(2013)
Jackknife estimation with a unit root.
Statistics and Probability Letters, 83 (7), .
(doi:10.1016/j.spl.2013.03.016).
Abstract
We study jackknife estimators in a first-order autoregression with a unit root. Non-overlapping sub-sample estimators have different limit distributions, so the jackknife does not fully eliminate first-order bias. We therefore derive explicit limit distributions of the numerator and denominator to calculate the expectations that determine optimal jackknife weights. Simulations show that the resulting jackknife estimator produces substantial reductions in bias and RMSE
Text
pii/S0167715213000990
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Published date: July 2013
Organisations:
Economics
Identifiers
Local EPrints ID: 351304
URI: http://eprints.soton.ac.uk/id/eprint/351304
ISSN: 0167-7152
PURE UUID: 6259e3b4-3f16-4810-94cd-4b9e6a51bd46
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Date deposited: 19 Apr 2013 08:44
Last modified: 14 Mar 2024 13:38
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Author:
Marcus J. Chambers
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