IDEAS home Printed from
MyIDEAS: Login to save this paper or follow this series

Bias Correction and Out-of-Sample Forecast Accuracy

  • Hyeongwoo Kim
  • Nazif Durmaz

We evaluate the usefulness of bias-correction methods for autoregressive (AR) models in terms of out-of-sample forecast accuracy, employing two popular methods proposed by Hansen (1999) and So and Shin (1999). Our Monte Carlo simulations show that these methods do not necessarily achieve better forecasting performances than the bias-uncorrected Least Squares (LS) method, because bias correction tends to increase the variance of the estimator. There is a gain from correcting for bias only when the true data generating process is sufficiently persistent. Though the bias arises in finite samples, the sample size (N) is not a crucial factor of the gains from bias-correction, because both the bias and the variance tend to decrease as N goes up. We also provide a real data application with 7 commodity price indices which confirms our findings.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
Download Restriction: no

Paper provided by Department of Economics, Auburn University in its series Auburn Economics Working Paper Series with number auwp2010-02.

in new window

Date of creation: May 2010
Date of revision:
Handle: RePEc:abn:wpaper:auwp2010-02
Contact details of provider: Postal: 0326 Haley Center, Auburn University, AL 36849-5049
Phone: (334) 844-4910
Fax: (334) 844-4615
Web page:

More information through EDIRC

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.:

as in new window
  1. Bruce E. Hansen, 1999. "The Grid Bootstrap And The Autoregressive Model," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 594-607, November.
  2. Hyeongwoo Kim & Ippei Fujiwara & Bruce E. Hansen & Masao Ogaki, 2013. "Purchasing Power Parity and the Taylor Rule," CAMA Working Papers 2013-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  3. Andrews, Donald W K & Chen, Hong-Yuan, 1994. "Approximately Median-Unbiased Estimation of Autoregressive Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 187-204, April.
  4. Kim, Hyeongwoo, 2009. "On the usefulness of the contrarian strategy across national stock markets: A grid bootstrap analysis," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 734-744, December.
  5. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  6. Hyeongwoo Kim & Young-Kyu Moh, 2010. "Examining the Evidence of Purchasing Power Parity by Recursive Mean Adjustment," Auburn Economics Working Paper Series auwp2010-08, Department of Economics, Auburn University.
  7. Donggyu Sul & Peter C.B. Phillips & Choi, Chi-Young, 2003. "Prewhitening Bias in HAC Estimation," Cowles Foundation Discussion Papers 1436, Cowles Foundation for Research in Economics, Yale University.
  8. Cheung, Yin-Wong & Lai, Kon S., 2000. "On the purchasing power parity puzzle," Journal of International Economics, Elsevier, vol. 52(2), pages 321-330, December.
  9. Andrews, Donald W K, 1993. "Exactly Median-Unbiased Estimation of First Order Autoregressive/Unit Root Models," Econometrica, Econometric Society, vol. 61(1), pages 139-65, January.
  10. Taylor, A M Robert, 2002. "Regression-Based Unit Root Tests with Recursive Mean Adjustment for Seasonal and Nonseasonal Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 269-81, April.
  11. Gospodinov, Nikolay, 2002. "Median unbiased forecasts for highly persistent autoregressive processes," Journal of Econometrics, Elsevier, vol. 111(1), pages 85-101, November.
  12. Serena Ng & Pierre Perron, 1997. "Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power," Boston College Working Papers in Economics 369, Boston College Department of Economics, revised 01 Sep 2000.
  13. Kim, Jae H., 2003. "Forecasting autoregressive time series with bias-corrected parameter estimators," International Journal of Forecasting, Elsevier, vol. 19(3), pages 493-502.
  14. Rossi, Barbara, 2005. "Confidence Intervals for Half-Life Deviations From Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 432-442, October.
  15. Jón Steinsson, 2008. "The Dynamic Behavior of the Real Exchange Rate in Sticky Price Models," NBER Working Papers 13910, National Bureau of Economic Research, Inc.
  16. Chi-Young Choi & Nelson C. Mark & Donggyu Sul, 2010. "Bias Reduction in Dynamic Panel Data Models by Common Recursive Mean Adjustment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(5), pages 567-599, October.
  17. Murray, Christian J. & Papell, David H., 2002. "The purchasing power parity persistence paradigm," Journal of International Economics, Elsevier, vol. 56(1), pages 1-19, January.
  18. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-66, July.
  19. Alan M. Taylor, 2000. "Potential Pitfalls for the Purchasing-Power-Parity Puzzle? Sampling and Specification Biases in Mean-Reversion Tests of the Law of One Price," NBER Working Papers 7577, National Bureau of Economic Research, Inc.
  20. Cook, Steven, 2002. "Correcting size distortion of the Dickey-Fuller test via recursive mean adjustment," Statistics & Probability Letters, Elsevier, vol. 60(1), pages 75-79, November.
  21. Anna Mikusheva, 2007. "Uniform Inference in Autoregressive Models," Econometrica, Econometric Society, vol. 75(5), pages 1411-1452, 09.
  22. Karanasos, M. & Sekioua, S.H. & Zeng, N., 2006. "On the order of integration of monthly US ex-ante and ex-post real interest rates: New evidence from over a century of data," Economics Letters, Elsevier, vol. 90(2), pages 163-169, February.
  23. Kim, Hyeongwoo & Stern, Liliana V. & Stern, Michael L., 2010. "Half-life bias correction and the G7 stock markets," Economics Letters, Elsevier, vol. 109(1), pages 1-3, October.
  24. So, Beong Soo & Shin, Dong Wan, 1999. "Recursive mean adjustment in time-series inferences," Statistics & Probability Letters, Elsevier, vol. 43(1), pages 65-73, May.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:abn:wpaper:auwp2010-02. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Hyeongwoo Kim)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.