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A Note on Parametric and Nonparametric Regression in the Presence of Endogenous Control Variables Author info | Abstract | Publisher info | Download info | Related research | Statistics Markus Frölich ()
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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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Paper provided by Department of Economics, University of St. Gallen in its series University of St. Gallen Department of Economics working paper series 2006 with number
2006-11.
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Length: 14 pages
Date of creation: May 2006Date of revision:
Handle: RePEc:usg:dp2006:2006-11Contact details of provider: Postal: Dufourstrasse 50, CH - 9000 St.Gallen Email: Web page: http://www.vwa.unisg.ch/ More information through EDIRC
For technical questions regarding this item, or to correct its listing, contact: (Joerg Baumberger).
Keywords: Endogeneity ; nonparametric regression ; instrumental variables ; Other versions of this item:
Find related papers by JEL classification: C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
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