Joel Miller wrote:
> I�ve been working on TSCS data involving 41 police force areas, and about
> 7
> time periods (soon I hope to be 8). I�m theoretically interested in a
> fixed
> effects model, because I want to see how variation within police forces is
> impacting arrest rates over time (and Hausman tests suggest a fixed
> effects
> model is appropriate).
>
> However, is OLS fixed effects my only choice here? I have played a little
> with a panel adjusted standard error (the Beck and Katz model). But while
> I
> have seen published articles which use the PCSE model with a similar data
> structure to mine (N a lot greater than T), I have since been advised that
> this is not appropriate. This puzzles me a little, because I have also
> read
> further that the Beck/Katz is actually more suited to N>T than other
> approaches.
>
> In short I�m confused. Help!
Directly from Beck (2001: 274):
"...TSCS methods are justified by asymptotics in T and typically require a
reasonably large T to be useful. ... (T)here is no hard and fast minimum T
for TSCS methods for work, but one ought to be suspicious of TSCS methods
used for, say, T < 10. On the other hand, TSCS methods do not require a
large a large N, although a large N is typically not harmful. ... (P)anel
methods are designed for and work with very small Ts (three, perhaps even
two) but require a large N for the theoretical properties of the
estimators to have any practical consequences."
Since this comes from the doyen of applying TSCS models to
political/social data, my recommendation would be to run -xtpcse- models
on your data anyway, but present and interpret them with huge caveats.
CLIVE NICHOLAS |t: 0(044)7903 397793
Politics |e: [email protected]
Newcastle University |http://www.ncl.ac.uk/geps
Reference:
Beck N (2001) "Time-Series Cross Section Data: What Have We Learned in the
Past Few Years", ANNUAL REVIEW OF POLITICAL SCIENCE 4: 271-93.
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