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Structural Measurement Errors in Nonseparable Models

  • Hoderlein, Stefan
  • Winter, Joachim

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 is- sues 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 University of Munich, Department of Economics in its series Discussion Papers in Economics with number 9192.

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Date of creation: 29 Jan 2009
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Handle: RePEc:lmu:muenec:9192
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  1. 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.
  2. repec:dgr:kubcen:199745 is not listed on IDEAS
  3. 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.
  4. Stefan Hoderlein, 2009. "How many consumers are rational?," CeMMAP working papers CWP32/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  5. Michael Hurd & Susann Rohwedder, 2008. "Methodological Innovations in Collecting Spending Data: The HRS Consumption and Activities Mail Survey," Working Papers 646, RAND Corporation Publications Department.
  6. Philipson, Tomas, 2001. "Data Markets, Missing Data, and Incentive Pay," Econometrica, Econometric Society, vol. 69(4), pages 1099-1111, July.
  7. Charles F. Manski, 2004. "Measuring Expectations," Econometrica, Econometric Society, vol. 72(5), pages 1329-1376, 09.
  8. Erich Battistin & Raffale Miniaci & Guglielmo Weber, 2000. "What do we learn from recall consumption data?," IFS Working Papers W00/10, Institute for Fiscal Studies.
  9. 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.
  10. Datta, Somnath, 1995. "On a modified bootstrap for certain asymptotically nonnormal statistics," Statistics & Probability Letters, Elsevier, vol. 24(2), pages 91-98, August.
  11. 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.
  12. 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, 09.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. Philipson, Tomas, 1997. "Data Markets and the Production of Surveys," Review of Economic Studies, Wiley Blackwell, vol. 64(1), pages 47-72, January.
  18. Stefan Hoderlein & Joachim Winter, 2009. "Structural Measurement Errors in Nonseparable Models," Boston College Working Papers in Economics 750, Boston College Department of Economics.
  19. 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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