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Structural Measurement Errors in Nonseparable Models

  • Stefan Hoderlein

    (Boston College)

  • Joachim Winter


    (University of Munich)

This paper considers measurement error from a new perspective. In surveys, response errors are often caused by the fact that respondents recall past events and quantities imperfectly. We explore the consequences of recall errors for such key econometric issues as the identification of marginal effects or economic restrictions in structural models. Our identification approach is entirely nonparametric, using Matzkin-type nonseparable models that nest a large class of potential structural models. We establish that measurement errors due to poor recall are generally likely to exhibit nonstandard behavior, in particular be nonclassical and differential, and we provide means to deal with this situation. Moreover, our findings suggest that conventional wisdom about measurement errors may be misleading in many economic applications. For instance, under certain conditions left-hand side recall errors will be problematic even in the linear model, and quantiles will be less robust than means. Finally, we apply the main concepts put forward in this paper to real world data, and find evidence that underscores the importance of focusing on individual response behavior.

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Paper provided by Boston College Department of Economics in its series Boston College Working Papers in Economics with number 750.

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Date of creation: 29 Jan 2009
Date of revision:
Handle: RePEc:boc:bocoec:750
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  1. Charles F. Manski, 2004. "Measuring Expectations," Econometrica, Econometric Society, vol. 72(5), pages 1329-1376, 09.
  2. Hoderlein, Stefan & Winter, Joachim, 2009. "Structural Measurement Errors in Nonseparable Models," Discussion Papers in Economics 9192, University of Munich, Department of Economics.
  3. Philipson, Tomas, 1997. "Data Markets and the Production of Surveys," Review of Economic Studies, Wiley Blackwell, vol. 64(1), pages 47-72, January.
  4. Martin Browning & Thomas F. Crossley & Guglielmo Weber, 2003. "Asking consumption questions in general purpose surveys," Economic Journal, Royal Economic Society, vol. 113(491), pages F540-F567, November.
  5. Michael Hurd & Susann Rohwedder, 2009. "Methodological Innovations in Collecting Spending Data: The HRS Consumption and Activities Mail Survey," Fiscal Studies, Institute for Fiscal Studies, vol. 30(Special I), pages 435-459, December.
  6. Erich Battistin & Raffale Miniaci & Guglielmo Weber, 2000. "What do we learn from recall consumption data?," IFS Working Papers W00/10, Institute for Fiscal Studies.
  7. 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.
  8. Whitney Newey & Guido Imbens, 2004. "Identification and Estimation of Triangular Simultaneous Equations Models without Additivity," Econometric Society 2004 North American Summer Meetings 594, Econometric Society.
  9. 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.
  10. Hoderlein, Stefan, 2011. "How many consumers are rational?," Journal of Econometrics, Elsevier, vol. 164(2), pages 294-309, October.
  11. Jerry Hausman, 2001. "Mismeasured Variables in Econometric Analysis: Problems from the Right and Problems from the Left," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 57-67, Fall.
  12. Datta, Somnath, 1995. "On a modified bootstrap for certain asymptotically nonnormal statistics," Statistics & Probability Letters, Elsevier, vol. 24(2), pages 91-98, August.
  13. J. A. Hausman & W. K. Newey & J. L. Powel, 1988. "Nonlinear Errors in Variables: Estimation of Some Engel Curves," Working papers 504, Massachusetts Institute of Technology (MIT), Department of Economics.
  14. Philipson, Tomas, 2001. "Data Markets, Missing Data, and Incentive Pay," Econometrica, Econometric Society, vol. 69(4), pages 1099-1111, July.
  15. Ait-Sahalia, Yacine & Bickel, Peter J. & Stoker, Thomas M., 2001. "Goodness-of-fit tests for kernel regression with an application to option implied volatilities," Journal of Econometrics, Elsevier, vol. 105(2), pages 363-412, December.
  16. 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.
  17. Joseph G. Altonji & Rosa L. Matzkin, 2005. "Cross Section and Panel Data Estimators for Nonseparable Models with Endogenous Regressors," Econometrica, Econometric Society, vol. 73(4), pages 1053-1102, 07.
  18. Yingyao Hu & Susanne Schennach, 2006. "Identification and estimation of nonclassical nonlinear errors-in-variables models with continuous distributions using instruments," CeMMAP working papers CWP17/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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