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Iatrogenic Specification Error: A Cautionary Tale of Cleaning Data

Author

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  • Bollinger, Christopher R.

    () (University of Kentucky)

  • Chandra, Amitabh

    () (Harvard Kennedy School)

Abstract

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.

Suggested Citation

  • Bollinger, Christopher R. & Chandra, Amitabh, 2004. "Iatrogenic Specification Error: A Cautionary Tale of Cleaning Data," IZA Discussion Papers 1093, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp1093
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    Cited by:

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    2. Christopher R. Bollinger & Amitabh Chandra, 2005. "Iatrogenic Specification Error: A Cautionary Tale of Cleaning Data," Journal of Labor Economics, University of Chicago Press, vol. 23(2), pages 235-258, April.
    3. Narayana Kocherlakota & Luigi Pistaferri, 2009. "Asset Pricing Implications of Pareto Optimality with Private Information," Journal of Political Economy, University of Chicago Press, vol. 117(3), pages 555-590, June.
    4. Puja Vasudeva Dutta, 2006. "Returns to Education: New Evidence for India, 1983-1999," Education Economics, Taylor & Francis Journals, vol. 14(4), pages 431-451.
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    6. Lozano, Fernando A., 2012. "What Happened to God's Time? The Evolution of Secularism and Hours of Work in America, Evidence from Religious Holidays," IZA Discussion Papers 6552, Institute for the Study of Labor (IZA).
    7. Djavad Salehi-Isfahani & Insan Tunali & Ragui Assaad, 2009. "A Comparative Study Of Returns To Education Of Urban Men In Egypt, Iran, And Turkey," Middle East Development Journal (MEDJ), World Scientific Publishing Co. Pte. Ltd., vol. 1(02), pages 145-187.
    8. Frémeaux, Nicolas & Lefranc, Arnaud, 2017. "Assortative Mating and Earnings Inequality in France," IZA Discussion Papers 11084, Institute for the Study of Labor (IZA).
    9. Alexandre Mas, 2008. "Labour Unrest and the Quality of Production: Evidence from the Construction Equipment Resale Market," Review of Economic Studies, Oxford University Press, vol. 75(1), pages 229-258.
    10. Harley Frazis & Mark A Loewenstein, 2006. "Wage Compression and the Division of Returns to Productivity Growth: Evidence from EOPP," Working Papers 398, U.S. Bureau of Labor Statistics.
    11. Seik Kim, 2013. "Wage Mobility of Foreign-Born Workers in the United States," Journal of Human Resources, University of Wisconsin Press, vol. 48(3), pages 628-658.
    12. Barry Reilly & Puja Vasudeva Dutta, 2005. "The Gender Pay Gap and Trade Liberalisation: Evidence for India," PRUS Working Papers 32, Poverty Research Unit at Sussex, University of Sussex.
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    14. Lee, Nayoung & Moon, Hyungsik Roger & Weidner, Martin, 2012. "Analysis of interactive fixed effects dynamic linear panel regression with measurement error," Economics Letters, Elsevier, vol. 117(1), pages 239-242.
    15. Timothy Grieder & Hashmat Khan, 2017. "The Collateral Channel: How Real Estate Shocks Affect Corporate Investment:Comment," Carleton Economic Papers 17-03, Carleton University, Department of Economics.
    16. Mika Maliranta & Pekka Ilmakunnas, 2005. "Decomposing productivity and wage effects of intraestablishment labor restructuring," Labor and Demography 0511003, EconWPA.
    17. Michiel Bijlsma & Ferry Haaijen & Casper van Ewijk, 2014. "Economic growth and funded pension systems," CPB Discussion Paper 279, CPB Netherlands Bureau for Economic Policy Analysis.

    More about this item

    Keywords

    winsorizing; measurement error models; trimming;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • J1 - Labor and Demographic Economics - - Demographic Economics

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