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Regression Coefficient Identification Decay in the Presence of Infrequent Classification Errors

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  • Kreider, Brent

Abstract

Recent evidence from Bound et al. (2001) and Black et al. (2003) suggests that reporting errors in survey data routinely violate all of the classical measurement error assumptions. The econometrics literature has not considered the consequences of arbitrary measurement error for identification of regression coefficients. This paper highlights the severity of the identification problem given the presence of even infrequent arbitrary errors in a binary regressor. In the empirical component, health insurance misclassification rates of less than 1.3 percent generate double-digit percentage point ranges of uncertainty about the variable's true marginal effect on the use of health services.

Suggested Citation

  • Kreider, Brent, 2007. "Regression Coefficient Identification Decay in the Presence of Infrequent Classification Errors," Staff General Research Papers Archive 12822, Iowa State University, Department of Economics.
  • Handle: RePEc:isu:genres:12822
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    Cited by:

    1. Lorenzo Almada & Ian McCarthy & Rusty Tchernis, 2016. "What Can We Learn about the Effects of Food Stamps on Obesity in the Presence of Misreporting?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(4), pages 997-1017.
    2. Patrick Hullegie & Tobias J. Klein, 2010. "The effect of private health insurance on medical care utilization and self‐assessed health in Germany," Health Economics, John Wiley & Sons, Ltd., vol. 19(9), pages 1048-1062, September.
    3. Engzell, Per, 2017. "What Do Books in the Home Proxy For? A Cautionary Tale," Working Paper Series 1/2016, Stockholm University, Swedish Institute for Social Research.
    4. Charles J. Courtemanche & Augustine Denteh & Rusty Tchernis, 2018. "Estimating the Associations between SNAP and Food Insecurity, Obesity, and Food Purchases with Imperfect Administrative Measures of Participation," NBER Working Papers 24412, National Bureau of Economic Research, Inc.
    5. Gundersen, Craig & Kreider, Brent & Pepper, John, 2012. "The impact of the National School Lunch Program on child health: A nonparametric bounds analysis," Journal of Econometrics, Elsevier, vol. 166(1), pages 79-91.
    6. Gundersen, Craig & Kreider, Brent, 2009. "Bounding the effects of food insecurity on children's health outcomes," Journal of Health Economics, Elsevier, vol. 28(5), pages 971-983, September.

    More about this item

    Keywords

    nonclassical measurement error; classification error; health insurance; corrupt sampling; binary regressor;

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