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Re: st: Unbalanced Panel analysis with systemaic attrition


From   Austin Nichols <[email protected]>
To   "[email protected]" <[email protected]>
Subject   Re: st: Unbalanced Panel analysis with systemaic attrition
Date   Fri, 15 Jul 2011 15:24:44 -0400

Not reg or xtreg.
Survival, or hazard models-- look up Stephen Jenkins book and programs
on discrete time hazard models, all on the web

On Friday, July 15, 2011, Patrick Fahrun <[email protected]> wrote:
> Dear Statalister,
>
> I am currently investigating startup performance in terms of whether they
> reached a next round of funding (binary coded dependent variable) as well as
> how long it takes them to reach the next round of funding (continuous
> dependent variable). The number of observations per startup ranges from only
> one to five rounds of funding (see below).
>
>      Freq.  Percent    Cum. |  Pattern
> ---------------------------+---------
>      2055     61.53   61.53 |  1....
>       896     26.83   88.35 |  11...
>       302      9.04   97.40 |  111..
>        75      2.25   99.64 |  1111.
>        12      0.36  100.00 |  11111
> ---------------------------+---------
>      3340    100.00         |  XXXXX
> AVG: ~ 1.5 observations per startup
>
> In addition, the period between founding rounds varies widely (e.g. from a
> couple of days to several years). I adjusted the time variable by coding the
> first observed round with t =1, the second observed round of funding with
> t=2 and so on to use it as my time id.  However, I am not sure whether this
> accompanies problems for a panel analysis?
>
> I read anywhere that unbalanced panels are usually not a problem in terms of
> biases, as long as the attrition is random. However, in my specific case the
> attrition is systematically as companies, which not survive (do not reach a
> new round of funding) drop out of my panel. How to take this into account in
> an analysis? Or can I just ignore it?
>
> What I have done so far`?
> For my binary dependent variable (reached next funding round?) I used
> xtlogit (RE), however I couldn’t test whether a FE model is more appropriate
> through the Hausman test as the degrees of freedom are not sufficient  for
> the estimation. For my continuous dependent variable (period to next round)
> the Hausman test indicates a FE-model. However the FE model shows a negative
> adjusted R-square as long as I do not restrict my panel to startups with > 2
> observations.
>
> In a nutshell, I am pretty unsure whether it is advisable to use a panel in
> my specific case. I was already wondering if it might be better just to
> select one observation per company (randomly vs. first observed round) and
> estimate a normal logit and regression.
>
> What type of analysis would you recommend? Is there a solution for this kind
> of unbalanced (panel) dataset with systematic attrition? I didn’t find any
> literature by now which solves my issues…
>
> Thank you very much in advance.
>
> All the best
> Patrick Fahrun
>
> Master Student Entrepreneurship & New Business Venturing
> Rotterdam School of Management
>
>
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