| Re: fixed effects and inflation factors [message #477 is a reply to message #474] |
Sun, 26 May 2013 16:03  |
Reduced-For(u)m
Messages: 292
Registered: March 2013
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Senior Member |
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I think it probably depends on how you are trying to interpret your coefficients and what kind of variation you are hoping to use. Disclaimer out of the way, I generally do use V101 (region of residence) as a regional fixed-effect. You say you are losing a lot of observations, but the only way the regional fixed effect is causing that problem is if you have only 1 observation in that region, which seems pretty unlikely. Otherwise, you'd be losing all the observations anyway since the women weren't tested. Am I missing something?
How many women do you have who have been tested. Maybe make a "tested" variable, and "bysort V101: tab tested"... if you have more than 10 or 20 women per region, it's not the regional fixed-effects which are the problem. But I've never worked with the HIV testing data, so maybe there are just so few tested observations that you are not going to be able to run the FE estimator.
Are you doing it by reg Y `X' i.region? or xtreg Y `X', fe (or something like that)? Maybe you've defined your panel/time vars wrong in your xtset somehow? It seems odd to me that V101 wouldn't have enough observations to handle a fixed-effect.
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