--- "[ISO-8859-1] Natália Barbosa" <[email protected]> wrote:
> (1) a QMLE Poisson estimator using Stata's glm command with link(log)
> exp(total number of firms) and robust
> (2) the WLS estimator applied to the arcsine-root transformation of
> the proportion of innovative firms
> (3) the fractional logit model proposed by Papke and Wooldridge
> (1996) using Stata's glm command with link(logit) family (binomial)
> and robust
Just a language remark: Models (1) and (3) are very very similar, the
only difference is the link function, but by giving very different
sounding discriptions you are suggesting that there are much more
differences between these models than is actually the case.
> A referee asks me for the effect sizes. How can I measure "effect
> sizes" using STATA and the above alternative procedures?
After -glm- (i.e. for models (1) and (3)) you can use -mfx-. I don't
know how you implemented model (2) but that sounds harder as you seem
to be modeling the average of the transformed proportion rather than
the average of the proportion.
-- Maarten
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room N515
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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