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From |
"Metcalfe, Paul" <Paul.Metcalfe@nera.com> |

To |
"'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: RE: RE: RE: RE: nested parameters |

Date |
Thu, 24 Jul 2003 17:24:39 +0100 |

That's excellent, and a useful command for future reference too. I knew Stata wouldn't let me down! Many thanks, Paul -----Original Message----- From: Brian P. Poi -- StataCorp [mailto:bpoi@stata.com] Sent: Thursday, July 24, 2003 5:20 PM To: 'statalist@hsphsun2.harvard.edu' Subject: Re: st: RE: RE: RE: RE: nested parameters Dear Paul As Nick suggested, we can write your model as Y1t = a + h(Y2t - bXt)+cZt+et = a + hY2t + gXt + cZt + et We can recover b as -g/h and then use the delta method to get the standard error of b. In Stata that is easy to do using the -nlcom- command: regress Y1t Y2t Xt Zt nlcom -1*_b[Xt] / _b[Y2t] -- Brian bpoi@stata.com On Thu, 24 Jul 2003, Metcalfe, Paul wrote: > It would be less problematic if the software calculated the standard errors > itself rather than having to work out how to do it manually. But I guess > that if Nick knows of no straightforward solution in Stata then, much to my > chagrin, I will be forced to use E-views, where it is easy to estimate this > sort of model including the standard errors. > > > -----Original Message----- > From: Nick Cox [mailto:n.j.cox@durham.ac.uk] > Sent: Thursday, July 24, 2003 4:11 PM > To: statalist@hsphsun2.harvard.edu > Subject: st: RE: RE: RE: nested parameters > > > That's a nicety I would happily ignore myself, > but I defer to sharper minds on these matters. > > Turn and turn about, I am not clear that getting > standard errors from your first formulation is any > less or any more unproblematic. > > Nick > n.j.cox@durham.ac.uk > > > -----Original Message----- > > From: owner-statalist@hsphsun2.harvard.edu > > [mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of > > Metcalfe, Paul > > Sent: 24 July 2003 15:48 > > To: 'statalist@hsphsun2.harvard.edu' > > Subject: st: RE: RE: nested parameters > > > > > > Thanks for the reply Nick. > > I may be missing something myself, namely a braincell or two, but my > > understanding is that there is a problem in calculating the > > standard error > > of the parameter b, which in Nick's suggested > > parameterisation is -g/h. I > > don't think the standard errors for g and h cannot be used > > directly to > > derive the standard error for b. But I may be wrong and if so I'd be > > grateful to know. > > > > > > > > -----Original Message----- > > From: Nick Cox [mailto:n.j.cox@durham.ac.uk] > > Sent: Thursday, July 24, 2003 1:36 PM > > To: statalist@hsphsun2.harvard.edu > > Subject: st: RE: nested parameters > > > > > > I may be missing somethig, but the nesting here seems benign. > > You could reparameterise to > > > > Y1t = a + h Y2t + gXt + cZt + et > > > > after which it looks like a standard regression model. > > > > Nick > > n.j.cox@durham.ac.uk > > > > > -----Original Message----- > > > From: owner-statalist@hsphsun2.harvard.edu > > > [mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of > > > Metcalfe, Paul > > > Sent: 24 July 2003 13:11 > > > To: 'statalist@hsphsun2.harvard.edu' > > > Subject: st: nested parameters > > > > > > > > > I would like to estimate a model of the form: Y1t = a + > > > h(Y2t - bXt)+cZt+et > > > where a, h, b and c are the parameters to estimate and et > > > is the error term. > > > Is there a way to estimate this in stata? > > > > > > > > > * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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