Approximate Bias Correction in Econometrics
AbstractThis paper discusses ways to reduce the bias of consistent estimators that are biased in finite samples. It is necessary that the bias function, which relates parameter values to bias, should be estimable by computer simulation or by some other method. If so, bias can be reduced or, in some cases that may not be unrealistic, even eliminated. In general, several evaluations of the bias function will be required to do this. Unfortunately, reducing bias may increase the variance, or even the mean squared error, of an estimator. Whether or not it does so depends on the shape of the bias functions. The techniques of the paper are illustrated by applying them to two problems: estimating the autoregressive parameter in an AR(1) model with a constant term, and estimation of a logit model.
Download InfoIf 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.
Bibliographic InfoPaper provided by Queen's University, Department of Economics in its series Working Papers with number 919.
Length: 28 pages
Date of creation: Jan 1995
Date of revision:
bias function; mean squared error; simulation; finite samples;
Other versions of this item:
- James G. MacKinnon & Anthony A. Smith, Jr., . "Approximate Bias Correction in Econometrics," GSIA Working Papers 1997-36, Carnegie Mellon University, Tepper School of Business.
- Mackinnon, J.G. & Smith, A.A., 1996. "Approximate Bias Correction in Econometrics," G.R.E.Q.A.M. 96a14, Universite Aix-Marseille III.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
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.:
- Kiviet, Jan F. & Phillips, Garry D.A., 1993. "Alternative Bias Approximations in Regressions with a Lagged-Dependent Variable," Econometric Theory, Cambridge University Press, vol. 9(01), pages 62-80, January.
- Gourieroux, C & Monfort, A & Renault, E, 1993.
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 8(S), pages S85-118, Suppl. De.
- Smith, Anthony A, Jr & Sowell, Fallaw & Zin, Stanley E, 1997.
"Fractional Integration with Drift: Estimation in Small Samples,"
Springer, vol. 22(1), pages 103-16.
- Tony Smith & Fallaw Sowell & Stanley Zin, . "Fractional integration with Drift: Estimation in Small Samples," GSIA Working Papers 22, Carnegie Mellon University, Tepper School of Business.
- James G. MacKinnon & Anthony A. Smith, Jr., .
"Approximate Bias Correction in Econometrics,"
GSIA Working Papers
1997-36, Carnegie Mellon University, Tepper School of Business.
- repec:cup:etheor:v:10:y:1994:i:1:p:116-29 is not listed on IDEAS
- Orcutt, Guy H & Winokur, Herbert S, Jr, 1969. "First Order Autoregression: Inference, Estimation, and Prediction," Econometrica, Econometric Society, vol. 37(1), pages 1-14, January.
- 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.
- Chesher, Andrew & Peters, Simon, 1994. "Symmetry, Regression Design, and Sampling Distributions," Econometric Theory, Cambridge University Press, vol. 10(01), pages 116-129, March.
- Phillips, Peter C. B., 1988. "The ET Interview: Professor James Durbin," Econometric Theory, Cambridge University Press, vol. 4(01), pages 125-157, April.
- Davidson, Russell & MacKinnon, James G., 1992. "Regression-based methods for using control variates in Monte Carlo experiments," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 203-222.
- Chesher, Andrew, 1995. "A Mirror Image Invariance for M-Estimators," Econometrica, Econometric Society, vol. 63(1), pages 207-11, January.
- Russell Davidson & James G. Mackinnon, 1990. "Regression-Based Methods for Using Control and Antithetic Variates in Monte Carlo Experiments," Working Papers 781, Queen's University, Department of Economics.
- Sawa, Takamitsu, 1978. "The exact moments of the least squares estimator for the autoregressive model," Journal of Econometrics, Elsevier, vol. 8(2), pages 159-172, October.
- repec:cup:etheor:v:9:y:1993:i:1:p:62-80 is not listed on IDEAS
- Smith, A A, Jr, 1993. "Estimating Nonlinear Time-Series Models Using Simulated Vector Autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S63-84, Suppl. De.
- Kiviet, Jan F. & Phillips, Garry D. A., 1994. "Bias assessment and reduction in linear error-correction models," Journal of Econometrics, Elsevier, vol. 63(1), pages 215-243, July.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading list or among the top items on IDEAS.Access and download statisticsgeneral 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: (Mark Babcock).
If references are entirely missing, you can add them using this form.