1. The observations are country-election-years
2. The DV is the vote percent gap between the winning party and the first loser
3. I use a LDV in some specifications and not in others, but the main model does not contain a LDV
4. I have an average of 7.9 time points (elections) per country and 55 total observations.
For reasons that are aren't helpful for present purposes, the data set used to be larger and I used xtgee, i(id) robust with success. Now that the data set is smaller, xtgee does not converge. I can make it converge by changing the tolerance, although I'm not yet sure what that actually does and how best to play with it, if at all.
-Ken
Kenneth Greene wrote:
> I have a small TSCS data set with 7 panels (countries) and 55 observations (elections) in total. Elections occur in different years across countries, so no observations occur in the same year. There are no missing data.
>
> What estimator should I use? Xtpsce seems to require shared time values across the panels. Creating a fake time variable may artificially erase any contemporaneous correlation. Xtreg, i(id) re works but I don't think it allow corrections for heteroskedasticity. Any suggestions?
I might be able to make some suggestions if you are prepared to say more about:
(1) the data in general;
(2) about how your dependent variable is measured in particular;
(3) whether or not you are using lagged variables, and
(4) how many time points you have for each country on average.
--
Clive Nicholas
[Please DO NOT mail me personally here, but at
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"My colleagues in the social sciences talk a great deal about
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____________________________________
Kenneth F Greene
Assistant Professor
Department of Government
1 University Station - A1800
University of Texas at Austin
Austin TX 78712-0119
Tel. 512-232-7206
Fax 512-471-1061
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