Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

xtdpd n L.n x z, div(x z) dgmmiv(n , lag(2.)) lgmm(n, lag(1)) hascons where n is the dependent variable, x is a set of time-varyng exogenous regressors and z is a set of time-invariant exogenous regressors. When I estimate this type of model on data the coefficients on z are counter-intuitive and do not resemble what I would expect to see (for example, they diverge greatly from OLS on the above model, or a static version of the above). I find this very puzzling. Surely estimation in levels (which identifies the coefs on z) should not have a dramatic impact on the coefs of z. I am also puzzled why one doesn't specify something like the following: xtdpd n L.n x z, div(x z) liv(x z) dgmmiv(n , lag(2.)) lgmm(n, lag(1)) hascons or xtdpd n L.n x z, iv(x z) dgmmiv(n , lag(2.)) lgmm(n, lag(1)) hascons or perhaps xtdpd n L.n x z, div(x z) liv(z) dgmmiv(n , lag(2.)) lgmm(n, lag(1)) hascons The output of the latter lists first-differenced xs as standard instruments for estimation in 1st-differences, and levels of z as standard instruments for the levels equation. Isn't this as required? The coefficients on z look far more convincing with this version of the command. If these are not correct, then why - i.e. what are they doing that they shouldn't be doing? The manual fails to talk about the estimation of time-invariant regressors within xtdpd. Any help/explanation gratefully received. Many thanks Nigel * * 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/

- Prev by Date:
**st: xtdpd** - Next by Date:
**Re: st: margins on continuous interactions.** - Previous by thread:
**st: xtdpd** - Next by thread:
**st: Substituting an expression into an -IF- conditional statement** - Index(es):