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From |
"Joseph J. Bakker" <joe.stata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: fixed effects glm - fractional dependent variable |

Date |
Tue, 31 Jul 2012 14:59:43 +0200 |

point taken. On Mon, Jul 30, 2012 at 4:03 PM, Steve Samuels <sjsamuels@gmail.com> wrote: > > Please note: > > "You are asked to post on Statalist using your full real name. This is a long-standing practice on Statalist. Giving full names is one of the ways in which we show respect for others." > > > > > > On Jul 30, 2012, at 4:09 AM, joe j wrote: > > Thank you very much Jeff, > > Somehow I missed your message, but nevertheless I ended up using the > solution you suggested (thanks to the paper, Papke, L.E., J.M. > Wooldridge (2008) Panel data methods for fractional response variables > with an application to test pass rates Journal of Econometrics 145: > 121–133). I used time averages, as well as time dummies. As you > indicate, the results from both glm and xtgee were quite similar. > > However, my data is unbalanced. Are your solutions for unbalanced data > available yet? > > Best, > Joe. > > On Sun, May 13, 2012 at 11:10 PM, Jeffrey Wooldridge > <jmwooldridge60@gmail.com> wrote: >> proposes a correlated random effects approach. As you suspect, putting >> in cross-sectional dummies introduces an incidental parameters problem >> (not to mention the computational problem). If you have a balanced >> panel you put in the time averages. With unbalanced panels it is >> trickier but I have recently worked on some solutions. >> >> We used xtgee and glm in our panel data work and found that, even >> though glm does not exploit the panel structure, it was almost as >> efficient. The important decision was including the time averages to >> control for the heterogeneity being correlated with the time-varying >> covariates. >> >> Jeff >> >> On Fri, Mar 30, 2012 at 4:26 AM, joe j <joe.stata@gmail.com> wrote: >>> Thanks for the link. There is indeed some discussion on this topic. >>> Joe. >>> >>> On Thu, Mar 29, 2012 at 8:47 PM, Anders Alexandersson >>> <andersalex@gmail.com> wrote: >>>> 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 >>>> andersalex@gmail.com >>>> >>>> >>>> >>>> >>>> On Mar 29,, joe j <joe.stata@gmail.com> 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? >>>> >>>> * >>>> * For searches and help try: >>>> * http://www.stata.com/help.cgi?search >>>> * http://www.stata.com/support/statalist/faq >>>> * http://www.ats.ucla.edu/stat/stata/ >>> >>> * >>> * For searches and help try: >>> * http://www.stata.com/help.cgi?search >>> * http://www.stata.com/support/statalist/faq >>> * http://www.ats.ucla.edu/stat/stata/ >> >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**Re: st: fixed effects glm - fractional dependent variable***From:*joe j <joe.stata@gmail.com>

**Re: st: fixed effects glm - fractional dependent variable***From:*Steve Samuels <sjsamuels@gmail.com>

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