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A Note on Parametric and Nonparametric Regression in the Presence of Endogenous Control Variables

  • Frölich, Markus

    ()

    (University of Mannheim)

This note argues that nonparametric regression not only relaxes functional form assumptions vis-a-vis parametric regression, but that it also permits endogenous control variables. To control for selection bias or to make an exclusion restriction in instrumental variables regression valid, additional control variables are often added to a regression. If any of these control variables is endogenous, OLS or 2SLS would be inconsistent and would require further instrumental variables. Nonparametric approaches are still consistent, though. A few examples are examined and it is found that the asymptotic bias of OLS can indeed be very large.

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File URL: http://ftp.iza.org/dp2126.pdf
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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 2126.

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Length: 13 pages
Date of creation: May 2006
Date of revision:
Publication status: published in: International Statistical Review, 2008, 76 (2), 214-227
Handle: RePEc:iza:izadps:dp2126
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  1. Michael Lechner, 2005. "Some practical issues in the evaluation of heterogeneous labour market programmes by matching methods," Labor and Demography 0505006, EconWPA.
  2. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
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  5. Eric Zitzewitz & Michael Kremer & Paul Glewwe & Sylvie Moulin, 2004. "Retrospective vs. prospective analyses of school inputs: The case of flip charts in kenya," Natural Field Experiments 00256, The Field Experiments Website.
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  8. James J. Heckman & Jeffrey A. Smith, 1999. "The Pre-Program Earnings Dip and the Determinants of Participation in a Social Program: Implications for Simple Program Evaluation Strategies," NBER Working Papers 6983, National Bureau of Economic Research, Inc.
  9. Black, Dan A. & Smith, J.A.Jeffrey A., 2004. "How robust is the evidence on the effects of college quality? Evidence from matching," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 99-124.
  10. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," NBER Working Papers 6699, National Bureau of Economic Research, Inc.
  11. Hanushek, Eric A, 1986. "The Economics of Schooling: Production and Efficiency in Public Schools," Journal of Economic Literature, American Economic Association, vol. 24(3), pages 1141-77, September.
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  13. Victor Lavy, 2002. "Evaluating the Effect of Teachers' Group Performance Incentives on Pupil Achievement," Journal of Political Economy, University of Chicago Press, vol. 110(6), pages 1286-1317, December.
  14. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," Review of Economic Studies, Oxford University Press, vol. 65(2), pages 261-294.
  15. Lorraine Dearden & Javier Ferri & Costas Meghir, 2002. "The Effect Of School Quality On Educational Attainment And Wages," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 1-20, February.
  16. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, 01.
  17. Markus Frölich, 2004. "Finite-Sample Properties of Propensity-Score Matching and Weighting Estimators," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 77-90, February.
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