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From |
Johannes Muck <Johannes.Muck@dice.uni-duesseldorf.de> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
AW: st: Standard error correction when using control function approach to endogeneity |

Date |
Wed, 19 Jun 2013 11:40:47 +0200 |

Dear Austin, thank you very much for your answer. As far as point (1) is concerned, I know that I could also use the 2SLS estimator by running ivregress or ivreg2. The reason for why I want to use the control function approach instead (where fitted residuals rather than fitted values are used in the second stage) is the following: I estimate a system of two simultaneous equations and need to test whether a combination of parameters from both equations is significantly different from zero (for further details see my earlier post to the statalist: http://www.stata.com/statalist/archive/2013-06/msg00566.html). By using the control function approach I circumvent the problem that combining two IV-estimations with the -suest- command does not work because I only use the -reg- command. However, before combining the two estimations, I want to make sure that the standard errors of my coefficients are correct. Nevertheless, I am glad that bootstrapping the whole procedure would also do the standard error correction. However, I guess it might be more elegant to use the analytic standard error correction? Best, Johannes -----Ursprüngliche Nachricht----- Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Austin Nichols Gesendet: Dienstag, 18. Juni 2013 20:27 An: statalist@hsphsun2.harvard.edu Betreff: Re: st: Standard error correction when using control function approach to endogeneity Johannes Muck <Johannes.Muck@dice.uni-duesseldorf.de>: 1) yes, just run these to get the same answers: ivreg y1 x1 x2 (y2 = z1 z2) ivregress 2sls y1 x1 x2 (y2 = z1 z2) ssc inst ivreg2 ivreg2 y1 x1 x2 (y2 = z1 z2) 2) yes, you can bootstrap the whole thing, but why would you? On Tue, Jun 18, 2013 at 11:31 AM, Johannes Muck <Johannes.Muck@dice.uni-duesseldorf.de> wrote: > Dear all, > > I am trying to fit a linear regression model with one endogenous variable > using the control function approach (two stage residual inclusion estimator) > as described in Wooldridge (2010, pp. 126-129). > > More specifically, I estimate something like: > > (1) reg y2 x1 x2 z1 z2 > (2) predict uhat, res > (3) reg y1 y2 x1 x2 uhat > > where y1 is my dependent variable of interest, y2 is the endogenous > variable, x1 and x2 are exogenous explanatory variables, and z1 and z2 are > valid instruments for y2. > > Since the fitted residual from the first stage is included in the second > stage regression as an additional regressor, the standard errors need be to > corrected. Wooldridge (2010, pp. 157-160) derives the formula for the > corrected standard errors in his book in Appendix 6A, equation (6.58). > > Now my two questions are: > > (1) Has someone already implemented this standard error correction in Stata > or do I have to calculate equation (6.58) in Appendix 6A manually? > > (2) Could I also obtain a "standard error correction" by bootstrapping > equations (1)-(3)? > > > Any help is greatly appreciated. > > Best, > > Johannes Muck > > References: > Wooldridge, J. M. (2010), Econometric Analysis of Cross Section and Panel > Data, 2nd edition, MIT Press, Cambridge MA. > * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Standard error correction when using control function approach to endogeneity***From:*Austin Nichols <austinnichols@gmail.com>

**References**:**st: Standard error correction when using control function approach to endogeneity***From:*Johannes Muck <Johannes.Muck@dice.uni-duesseldorf.de>

**Re: st: Standard error correction when using control function approach to endogeneity***From:*Austin Nichols <austinnichols@gmail.com>

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