Bookmark and Share

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

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

st: fixed effects glm - fractional dependent variable

From   joe j <[email protected]>
To   [email protected]
Subject   st: fixed effects glm - fractional dependent variable
Date   Thu, 29 Mar 2012 16:10:04 +0200

Dear all,

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

"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?

*   For searches and help try:

© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index