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Instrumental variables quantile regression for panel data with measurement errors

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Author Info

  • Galvao Jr, A. F.
  • Montes-Rojas, G.

Abstract

This paper develops an instrumental variables estimator for quantile regression in panel data with fixed effects. Asymptotic properties of the instrumental variables estimator are studied for large N and T when Na/T ! 0, for some a > 0. Wald and Kolmogorov-Smirnov type tests for general linear restrictions are developed. The estimator is applied to the problem of measurement errors in variables, which induces endogeneity and as a result bias in the model. We derive an approximation to the bias in the quantile regression fixed effects estimator in the presence of measurement error and show its connection to similar effects in standard least squares models. Monte Carlo simulations are conducted to evaluate the finite sample properties of the estimator in terms of bias and root mean squared error. Finally, the methods are applied to a model of firm investment. The results show interesting heterogeneity in the Tobin’s q and cash flow sensitivities of investment. In both cases, the sensitivities are monotonically increasing along the quantiles.

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File URL: http://openaccess.city.ac.uk/1496/1/Instrumental_Variables_Quantile_Regression.pdf
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Bibliographic Info

Paper provided by Department of Economics, City University London in its series Working Papers with number 09/06.

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Date of creation: 2009
Date of revision:
Handle: RePEc:cty:dpaper:09/06

Contact details of provider:
Postal: Department of Economics, Social Sciences Building, City University London, Whiskin Street, London, EC1R 0JD, United Kingdom,
Phone: +44 (0)20 7040 8500
Web page: http://www.city.ac.uk
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Related research

Keywords: quantile regression; panel data; measurement errors; instrumental variables;

References

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  1. Lorenzoni, Guido & Walentin, Karl, 2007. "Financial Frictions, Investment and Tobin’s q," Working Paper Series 208, Sveriges Riksbank (Central Bank of Sweden).
  2. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
  3. Chernozhukov, Victor & Hansen, Christian, 2008. "Instrumental variable quantile regression: A robust inference approach," Journal of Econometrics, Elsevier, vol. 142(1), pages 379-398, January.
  4. Schennach, Susanne M., 2008. "Quantile Regression With Mismeasured Covariates," Econometric Theory, Cambridge University Press, vol. 24(04), pages 1010-1043, August.
  5. Griliches, Zvi & Hausman, Jerry A., 1986. "Errors in variables in panel data," Journal of Econometrics, Elsevier, vol. 31(1), pages 93-118, February.
  6. Abrevaya, Jason & Dahl, Christian M, 2008. "The Effects of Birth Inputs on Birthweight," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 379-397.
  7. Wansbeek, Tom, 2001. "GMM estimation in panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 104(2), pages 259-268, September.
  8. Joshua Angrist & Victor Chernozhukov & Ivan Fernandez-Val, 2004. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," NBER Working Papers 10428, National Bureau of Economic Research, Inc.
  9. Blundell, Richard & Bond, Stephen & Devereux, Michael & Schiantarelli, Fabio, 1992. "Investment and Tobin's Q: Evidence from company panel data," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 233-257.
  10. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
  11. Jinyong Hahn & Guido Kuersteiner, 2002. "Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects when Both "n" and "T" Are Large," Econometrica, Econometric Society, vol. 70(4), pages 1639-1657, July.
  12. Bester, C. Alan & Hansen, Christian, 2009. "A Penalty Function Approach to Bias Reduction in Nonlinear Panel Models with Fixed Effects," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 131-148.
  13. Susanne M. Schennach, 2004. "Estimation of Nonlinear Models with Measurement Error," Econometrica, Econometric Society, vol. 72(1), pages 33-75, 01.
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Citations

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Cited by:
  1. Alessia Matano & Paolo Naticchioni, 2009. "Wage distribution and the spatial sorting of workers and firms," Working Papers - Dipartimento di Economia 8-DEISFOL, Dipartimento di Economia, Sapienza University of Rome, revised 2009.
  2. Alessia Matano & Paolo Naticchioni, 2011. "Rent Sharing as a Driver of the Glass Ceiling Effect," Working Papers - Dipartimento di Economia 12-DEISFOL, Dipartimento di Economia, Sapienza University of Rome, revised 2011.

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