Iatrogenic Specification Error: A Cautionary Tale of Cleaning Data
In empirical research it is common practice to use sensible rules of thumb for cleaning data. Measurement error is often the justification for removing (trimming) or recoding (winsorizing) observations whose values lie outside a specified range. We consider a general measurement error process that nests many plausible models. Analytic results demonstrate that winsorizing and trimming are only solutions for a narrow class of measurement error processes. Indeed, for the measurement error processes found in most social-science data, such procedures can induce or exacerbate bias, and even inflate the variance estimates. We term this source of bias "Iatrogenic" (or econometrician induced) error. Monte Carlo simulations and empirical results from the Census PUMS data and 2001 CPS data demonstrate the fragility of trimming and winsorizing as solutions to measurement error in the dependent variable. Even on asymptotic variance and RMSE criteria, we are unable to find generalizable justifications for commonly used cleaning procedures.
|Date of creation:||Mar 2004|
|Date of revision:|
|Publication status:||published in: Journal of Labor Economics, 2005, 23 (2), 235-257|
|Contact details of provider:|| Postal: IZA, P.O. Box 7240, D-53072 Bonn, Germany|
Phone: +49 228 3894 223
Fax: +49 228 3894 180
Web page: http://www.iza.org
|Order Information:|| Postal: IZA, Margard Ody, P.O. Box 7240, D-53072 Bonn, Germany|
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.:
- Manski, C.F., 1992. "Identification Problems in the Social Sciences," Working papers 9217, Wisconsin Madison - Social Systems.
- Marco Manacorda, 2004. "Can the Scala Mobile Explain the Fall and Rise of Earnings Inequality in Italy? A Semiparametric Analysis, 19771993," Journal of Labor Economics, University of Chicago Press, vol. 22(3), pages 585-614, July.
- Juhn, Chinhui & Murphy, Kevin M & Pierce, Brooks, 1993. "Wage Inequality and the Rise in Returns to Skill," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 410-42, June.
- David Card & Alan B. Krueger, 1991.
"School Quality and Black-White Relative Earnings: A Direct Assessment,"
NBER Working Papers
3713, National Bureau of Economic Research, Inc.
- David Card & Alan B. Krueger, 1992. "School Quality and Black-White Relative Earnings: A Direct Assessment," The Quarterly Journal of Economics, Oxford University Press, vol. 107(1), pages 151-200.
- Joshua Angrist & Alan Krueger, 1998.
"Empirical Strategies in Labor Economics,"
98-7, Massachusetts Institute of Technology (MIT), Department of Economics.
- Goldberger, Arthur S., 1981. "Linear regression after selection," Journal of Econometrics, Elsevier, vol. 15(3), pages 357-366, April.
- Bollinger, Christopher R, 1998. "Measurement Error in the Current Population Survey: A Nonparametric Look," Journal of Labor Economics, University of Chicago Press, vol. 16(3), pages 576-94, July.
- Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, vol. 63(2), pages 281-302, March.
- Bound, John & Krueger, Alan B, 1991.
"The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right?,"
Journal of Labor Economics,
University of Chicago Press, vol. 9(1), pages 1-24, January.
- John Bound & Alan B. Krueger, 1989. "The Extent of Measurement Error In Longitudinal Earnings Data: Do Two Wrongs Make A Right?," NBER Working Papers 2885, National Bureau of Economic Research, Inc.
- Mellow, Wesley & Sider, Hal, 1983. "Accuracy of Response in Labor Market Surveys: Evidence and Implications," Journal of Labor Economics, University of Chicago Press, vol. 1(4), pages 331-44, October.
- MacDonald, Glenn M & Robinson, Chris, 1985. "Cautionary Tails about Arbitrary Deletion of Observations; or, Throwing the Variance Out with the Bathwater," Journal of Labor Economics, University of Chicago Press, vol. 3(2), pages 124-52, April.
- Barry T. Hirsch & Edward J. Schumacher, 2004.
"Match Bias in Wage Gap Estimates Due to Earnings Imputation,"
Journal of Labor Economics,
University of Chicago Press, vol. 22(3), pages 689-722, July.
- Hirsch, Barry & Schumacher, Edward J., 2003. "Match Bias in Wage Gap Estimates Due to Earnings Imputation," IZA Discussion Papers 783, Institute for the Study of Labor (IZA).
- Bound, John, et al, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, vol. 12(3), pages 345-68, July.
- Dean R. Hyslop & Guido W. Imbens, 2000.
"Bias from Classical and Other Forms of Measurement Error,"
NBER Technical Working Papers
0257, National Bureau of Economic Research, Inc.
- Hyslop, Dean R & Imbens, Guido W, 2001. "Bias from Classical and Other Forms of Measurement Error," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 475-81, October.
- Bollinger, Christopher R., 1996. "Bounding mean regressions when a binary regressor is mismeasured," Journal of Econometrics, Elsevier, vol. 73(2), pages 387-399, August.
When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp1093. 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: (Mark Fallak)
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.