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Bias Reduction through First-order Mean Correction, Bootstrapping and Recursive Mean Adjustment

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Author Info
K. Patterson
Abstract

Standard methods of estimation for autoregressive models are known to be biased in finite samples, which has implications for estimation, hypothesis testing, confidence interval construction and forecasting. Three methods of bias reduction are considered here: first-order bias correction, FOBC, where the total bias is approximated by the O(T - 1 ) bias; bootstrapping; and recursive mean adjustment, RMA. In addition, we show how first-order bias correction is related to linear bias correction. The practically important case where the AR model includes an unknown linear trend is considered in detail. The fidelity of nominal to actual coverage of confidence intervals is also assessed. A simulation study covers the AR(1) model and a number of extensions based on the empirical AR(p) models fitted by Nelson & Plosser (1982). Overall, which method dominates depends on the criterion adopted: bootstrapping tends to be the best at reducing bias, recursive mean adjustment is best at reducing mean squared error, whilst FOBC does particularly well in maintaining the fidelity of confidence intervals.

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Publisher Info
Article provided by Taylor and Francis Journals in its journal Journal of Applied Statistics.

Volume (Year): 34 (2007)
Issue (Month): 1 (January)
Pages: 23-45
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Handle: RePEc:taf:japsta:v:34:y:2007:i:1:p:23-45

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Related research
Keywords: Autoregressive model; bias; first-order correction; bootstrap bias correction; recursive mean adjustment;

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. James G. MacKinnon, 2006. "Bootstrap Methods in Econometrics," Working Papers 1028, Queen's University, Department of Economics. [Downloadable!]
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  2. MacKinnon, James G. & Smith Jr., Anthony A., 1998. "Approximate bias correction in econometrics," Journal of Econometrics, Elsevier, vol. 85(2), pages 205-230, August. [Downloadable!] (restricted)
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  3. Jeremy Berkowitz & Lutz Kilian, 2000. "Recent developments in bootstrapping time series," Econometric Reviews, Taylor and Francis Journals, vol. 19(1), pages 1-48. [Downloadable!] (restricted)
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  4. Peter C. Schotman & Herman K. van Dijk, 1991. "On Bayesian routes to unit roots," Discussion Paper / Institute for Empirical Macroeconomics 43, Federal Reserve Bank of Minneapolis. [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Jean-Marie Dufour & Abderrahim Taamouti, 2008. "Short and long run causality measures: theory and inference," Economics Working Papers we083720, Universidad Carlos III, Departamento de Economía. [Downloadable!]
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