IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Iatrogenic Specification Error: A Cautionary Tale of Cleaning Data

  • Bollinger, Christopher R.

    ()

    (University of Kentucky)

  • Chandra, Amitabh

    ()

    (Harvard Kennedy School)

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.

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: http://ftp.iza.org/dp1093.pdf
Download Restriction: no

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 1093.

as
in new window

Length: 24 pages
Date of creation: Mar 2004
Date of revision:
Publication status: published in: Journal of Labor Economics, 2005, 23 (2), 235-257
Handle: RePEc:iza:izadps:dp1093
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
Email:


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. Manski, C.F., 1992. "Identification Problems in the Social Sciences," Working papers 9217, Wisconsin Madison - Social Systems.
  2. 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.
  3. Goldberger, Arthur S., 1981. "Linear regression after selection," Journal of Econometrics, Elsevier, vol. 15(3), pages 357-366, April.
  4. 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.
  5. David Card & Alan Krueger, 1990. "School Quality and Black/White Relative Earnings: A Direct Assessment," Working Papers 652, Princeton University, Department of Economics, Industrial Relations Section..
  6. 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.
  7. 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.
  8. 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.
  9. Bollinger, Christopher R., 1996. "Bounding mean regressions when a binary regressor is mismeasured," Journal of Econometrics, Elsevier, vol. 73(2), pages 387-399, August.
  10. 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.
  11. 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.
  12. Joshua Angrist & Alan Krueger, 1998. "Empirical Strategies in Labor Economics," Working Papers 780, Princeton University, Department of Economics, Industrial Relations Section..
  13. 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.
  14. 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.
  15. 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.
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: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.

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