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From |
"Dithmer, Jan" <jdithme@food-econ.uni-kiel.de> |

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

Subject |
AW: st: xtivreg2 or new Stata12 command sem? |

Date |
Mon, 23 Jan 2012 17:07:23 +0100 |

Thanks very much to Stas and Maarten! I will have a look at gllamm, which seems to be quite flexible. Maarten, the link you posted is very interesting, but does it also imply that I may use xtmixed, because in the example it does the same more easily? However, am I right with my intuition? I mean, I can estimate the direct effect of B on Y (equation 1), but with a single equation I miss the indirect effects, or am I missing s.th. here? Is there a way to use the sureg command, when I somehow account for the panel structure of the data? Best, Jan -----Ursprüngliche Nachricht----- Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Stas Kolenikov Gesendet: Monday, January 23, 2012 4:02 PM An: statalist@hsphsun2.harvard.edu Betreff: Re: st: xtivreg2 or new Stata12 command sem? -sem- does not support panel data, either. So don't rest your hope on it. May be -gllamm- might help you, although it only runs random effect multi-equation models. On Mon, Jan 23, 2012 at 9:23 AM, Dithmer, Jan <jdithme@food-econ.uni-kiel.de> wrote: > Dear Statalisters, > > I want to estimate a system of equations with panel data, where there are several interrelationships between the variables. > I estimated the first equation (1) with GMM using xtabond2, treating > variable B as endogenous. However, I fear that I might lose some potential indirect effects that B has on some explanatory variables in (1). I would use the sureg command, but it does not support panel data. My intuition tells me that, when B positively influences D and E, and they themselves have a positive coefficient in (1), the effect of B on Y in (1) should be greater than I have estimated, or I am wrong here? > > (1) Y_it = a + bY_it-1 + cB_it + dC_it + eD_it + fE_it + error > > (2) B_it = gY_it + hC_it + iF_it + error > > (3) D_it = jB_it + kG_it+lH_it +error > > (4) E_it = mB_it + nJ_it + error > > So, my question is: how can I estimate the whole system of equations > to capture all indirect effects? Might this be a task for the Structural equation modeling "sem" command in Stata12 (which I not have) Or should I just estimate the equations separately using xtabond2 for the first and xtivreg2 for the rest? But then I already have the result of the first equation, in which I am mainly interested in... > > Thanks for any suggestions! > > Best, Jan > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ -- Stas Kolenikov, also found at http://stas.kolenikov.name Small print: I use this email account for mailing lists only. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/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/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: xtivreg2 or new Stata12 command sem?***From:*Stas Kolenikov <skolenik@gmail.com>

**References**:**st: xtivreg2 or new Stata12 command sem?***From:*"Dithmer, Jan" <jdithme@food-econ.uni-kiel.de>

**Re: st: xtivreg2 or new Stata12 command sem?***From:*Stas Kolenikov <skolenik@gmail.com>

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