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Nonclassical Measurement Error in a Nonlinear (Duration) Model

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  • Gutknecht, Daniel

Abstract

In this paper, we study nonclassical measurement error in the continuous dependent variable of a semiparametric transformation model. The latter is a popular choice in practice nesting various nonlinear duration and censored regression models. The main complication arises because we allow the (additive) measurement error to be correlated with a (continuous) component of the regressors as well as with the true, unobserved dependent variable itself. This problem has not yet been studied in the literature, but we argue that it is relevant for various empirical setups with mismeasured, continuous survey data like earnings or durations. We develop a framework to identify and consistently estimate (up to scale) the parameter vector of the transformation model. Our estimator links a two-step control function approach of Imbens and Newey (2009) with a rank estimator similar to Khan (2001) and is shown to have desirable asymptotic properties. We prove that ‘m out of n’ bootstrap can be used to obtain a consistent approximation of the asymptotic variance and study the estimator’s finite sample performance in a Monte Carlo Simulation. To illustrate the empirical usefulness of our procedure, we estimate an earnings equation model using annual data from the Health and Retirement Study (HRS). We find some evidence for a bias in the coefficients of years of education and age, emphasizing once again the importance to adjust for potential measurement error bias in empirical work.

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  • Gutknecht, Daniel, 2011. "Nonclassical Measurement Error in a Nonlinear (Duration) Model," Economic Research Papers 270763, University of Warwick - Department of Economics.
  • Handle: RePEc:ags:uwarer:270763
    DOI: 10.22004/ag.econ.270763
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    1. Glewwe, Paul & Patrinos, Harry Anthony, 1999. "The Role of the Private Sector in Education in Vietnam: Evidence From the Vietnam Living Standards Survey," World Development, Elsevier, vol. 27(5), pages 887-902, May.
    2. Lu, Xuewen & Cheng, Tsung-Lin, 2007. "Randomly censored partially linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 98(10), pages 1895-1922, November.
    3. Rosa L. Matzkin, 2007. "Nonparametric Survey Response Errors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1411-1427, November.
    4. Guido W. Imbens & Whitney K. Newey, 2009. "Identification and Estimation of Triangular Simultaneous Equations Models Without Additivity," Econometrica, Econometric Society, vol. 77(5), pages 1481-1512, September.
    5. Julian Cristia & Jonathan A. Schwabish, 2007. "Measurement Error in the SIPP: Evidence from Matched Administrative Records: Working Paper 2007-03," Working Papers 18322, Congressional Budget Office.
    6. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    7. 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.
    8. Lai, T. L. & Ying, Z. L. & Zheng, Z. K., 1995. "Asymptotic Normality of a Class of Adaptive Statistics with Applications to Synthetic Data Methods for Censored Regression," Journal of Multivariate Analysis, Elsevier, vol. 52(2), pages 259-279, February.
    9. Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, January.
    10. O. Ashenfelter & D. Card (ed.), 1999. "Handbook of Labor Economics," Handbook of Labor Economics, Elsevier, edition 1, volume 3, number 3.
    11. Newey, Whitney K, 1994. "The Asymptotic Variance of Semiparametric Estimators," Econometrica, Econometric Society, vol. 62(6), pages 1349-1382, November.
    12. Card, David, 1999. "The causal effect of education on earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 30, pages 1801-1863, Elsevier.
    13. Goncalves, Silvia & White, Halbert, 2004. "Maximum likelihood and the bootstrap for nonlinear dynamic models," Journal of Econometrics, Elsevier, vol. 119(1), pages 199-219, March.
    14. Xiaohong Chen & Han Hong & Elie Tamer, 2005. "Measurement Error Models with Auxiliary Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(2), pages 343-366.
    15. Whitney K. Newey & James L. Powell & Francis Vella, 1999. "Nonparametric Estimation of Triangular Simultaneous Equations Models," Econometrica, Econometric Society, vol. 67(3), pages 565-604, May.
    16. Jesse Bricker & Gary V. Engelhardt, 2007. "Measurement Error in Earnings Data in the Health and Retirement Study," Working Papers, Center for Retirement Research at Boston College wp2007-16, Center for Retirement Research, revised Oct 2007.
    17. Srinivasan, C. & Zhou, M., 1994. "Linear Regression with Censoring," Journal of Multivariate Analysis, Elsevier, vol. 49(2), pages 179-201, May.
    18. Powell, James L & Stock, James H & Stoker, Thomas M, 1989. "Semiparametric Estimation of Index Coefficients," Econometrica, Econometric Society, vol. 57(6), pages 1403-1430, November.
    19. repec:adr:anecst:y:1999:i:55-56:p:09 is not listed on IDEAS
    20. Khan, Shakeeb, 2001. "Two-stage rank estimation of quantile index models," Journal of Econometrics, Elsevier, vol. 100(2), pages 319-355, February.
    21. Kristin F. Butcher & Anne Case, 1994. "The Effect of Sibling Sex Composition on Women's Education and Earnings," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(3), pages 531-563.
    22. Han, Aaron K., 1987. "Non-parametric analysis of a generalized regression model : The maximum rank correlation estimator," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 303-316, July.
    23. Abrevaya, Jason, 1999. "Rank regression for current-status data: asymptotic normality," Statistics & Probability Letters, Elsevier, vol. 43(3), pages 275-287, July.
    24. Lu, Xuewen & Burke, M.D., 2005. "Censored multiple regression by the method of average derivatives," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 182-205, July.
    25. Jason Abrevaya & Jerry A. Hausman, 1999. "Semiparametric Estimation with Mismeasured Dependent Variables: An Application to Duration Models for Unemployment Spells," Annals of Economics and Statistics, GENES, issue 55-56, pages 243-275.
    26. Karim Chalak & Halbert White, 2007. "An Extended Class of Instrumental Variables for the Estimation of Causal Effects," Boston College Working Papers in Economics 692, Boston College Department of Economics, revised 30 Nov 2009.
    27. Chesher, Andrew & Dumangane, Montezuma & Smith, Richard J., 2002. "Duration response measurement error," Journal of Econometrics, Elsevier, vol. 111(2), pages 169-194, December.
    28. Sherman, Robert P, 1993. "The Limiting Distribution of the Maximum Rank Correlation Estimator," Econometrica, Econometric Society, vol. 61(1), pages 123-137, January.
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    1. repec:wrk:warwec:991 is not listed on IDEAS
    2. Gutknecht, Daniel, 2012. "Do Reservation Wages Decline Monotonically? A Novel Statistical Test," Economic Research Papers 270635, University of Warwick - Department of Economics.

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