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Re: st: Dynamic count data panels


From   Tirthankar Chakravarty <[email protected]>
To   [email protected]
Subject   Re: st: Dynamic count data panels
Date   Sat, 18 Apr 2009 20:17:38 +0100

I would suggest Frank Windmeijer's Gauss codes - ExpEnd:
http://cemmap.ifs.org.uk/wps/cwp0214.pdf

It provides estimation routines for the Linear Feedback Model (LFM) as
described in Blundell, Griffith and Windmeijer (2002) to model dynamic
panel counts - and a host of other panel and cross-section GMM
estimators for count data.

T

--- References ---
@article{blundell2002iea,
  title={{Individual effects and dynamics in count data models}},
  author={Blundell, R. and Griffith, R. and Windmeijer, F.},
  journal={Journal of Econometrics},
  volume={108},
  number={1},
  pages={113--131},
  year={2002},
  publisher={Elsevier}
}

On Sat, Apr 18, 2009 at 6:34 PM, [ISO-8859-1] Fernando Terrés
<[email protected]> wrote:
> I'm trying to fit dynamic count data panels. My data is epidemiologycal
> (number of deaths, around 20% 0's and over) with an exposure, two
> continuous explicative variables, and several dummies. The series of the
> independent variable is highly persistent, and this also happens with
> one of the explicative variables. The data structure seems similar to
> data in the literature of patents and R&D, wich is tipically fitted with
> panel GMM estimators.
> My questions are:
> 1. Is it possible to fit this kind of model with Stata 10?
> 2. If yes, how?
> 3. If not, do you have any suggestion?
> I've read that there are users developing GMM routines for stata
> (ivpois), but they aren't for panels.
> Thanks in advance,
>
> Fernando
> --
> Fernando Terres
> Lecturer. PhD candidate
> CERPIE/Research
> Universitat Politecnica de Catalunya
> Diagonal, 647 - 10
> 08028 Barcelona (Spain)
> +34.934.010.708
> [email protected]
> http://cerpie.upc.edu
>
>
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>



-- 
To every ω-consistent recursive class κ of formulae there correspond
recursive class signs r, such that neither v Gen r nor Neg(v Gen r)
belongs to Flg(κ) (where v is the free variable of r).

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