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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

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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