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Re: st: fixed effects glm - fractional dependent variable
From
Anders Alexandersson <[email protected]>
To
[email protected]
Subject
Re: st: fixed effects glm - fractional dependent variable
Date
Thu, 29 Mar 2012 14:47:24 -0400
I do not have an answer to your question but -glm- ignores that you
have panel data.
For example, see http://www.stata.com/statalist/archive/2012-01/msg00595.html
Anders Alexandersson
[email protected]
On Mar 29,, joe j <[email protected]> wrote:
> I have a panel data with the dependent variable being a faction,
> including some zeros (about 1%) and ones (about 10%). These 0s and 1s
> are real outcomes indeed (that is, not the results of censoring).
>
> So I am going in favor of a glm model as proposed in the literature
> (e.g. Papke, Leslie E. and Jeffrey M. Wooldridge. 1996. Econometric
> Methods for Fractional Response Variables with an Application to
> 401(k) Plan Participation Rates. Journal of Applied Econometrics
> 11(6):619-632.):
>
> "glm dependent_variable independent_variable, family(binomial)
> link(logit) robust"
>
> What I would like to do is run a fixed effect model. However, there
> are too many dummy variables to create (over 16,000 in a sample of
> over 40,000 observations); moreover, I am not sure dummy variable
> approach is appropriate given the non-linear nature of the model.
>
> My first thought was to use:
>
> vce(cluster panel_variable)
>
> Is that the closest I could get to a fixed effect model?
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