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st: time-dependence and serial correlation in event history models
I am running an event history analysis, using logit. The unit of analysis
is the 50 United States and an observation is taken for each state for a
period of 50 months. I am estimating the probability that a state will
experience an event, so a state is censored once the event occurs.
One of my predictors is the cumulative number (or a function of that
number) of states that has previously experienced the event. I am concered
about time dependence and serial correlation (does the effect I find
persist if I control for these?)
I can see three ways of doing this:
1) use robust standard errors for the logit estimation
2) Include a time-counter as one of the coefficients
3) use the "cluster" option to cluster observations by state.
I am unclear about which of these to use, and whether it makes any sense to
use more than one of them at the same time.
Any pointers would be greatly appreciated.
Dept. of Political Science
Rhode Island College
600 Mount Pleasant Ave. Providence, RI 02908
Phone: (401) 456-8722
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