Hi everyone,
This is the first time I try to post a question on the Statalist, and I
hope someone out there can help me to understand my perhaps somewhat
naive question.
I have an unbalanced dataset, covering 15 countries over 20 years. As
usually with time-series data, there is significant autocorrelation that
I somehow need to take into account. One option for analyzing this data
would be what I would call "pooled time series regression", or the xtgls
option in STATA. These models would allow me to take into account the
autocorrelation. Another option would be a multilevel mixed-effects
model (xtmixed), which I understand have some nice features: it can
accommodate unbalanced data, and it will estimate variance components at
different levels (over time and between countries).
Now to my question: How should I think about, and understand, the
autocorrelation in the mixed effects model? With my (somewhat limited)
experience with time-series data, I need to somehow take the
autocorrelation into account. How is this done in a mixed-effect model?
Since years are nested within countries, will the estimated standard
errors be valid?
I hope someone can just give some hints on how to thick about this, or
perhaps give me some suggestions on readings.
Thanks
Ola
--
Ola Sj�berg, Associate Professor of Sociology
Swedish Institute for Social Research
Stockholm University
106 91 Stockholm
Sweden
Tel.: +46 8 162150
Fax: +46 8 154670
Home page: http://www.sofi.su.se/~osj/
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