st: Fixed effects and stable variables: xtivreg or ivreg2?

["Jon O'Brien" <jobrien2@nd.edu>]

Hello Statalist members,



I tried this message 2x before and it didn't go through - hopefully 3rd 
times a charm! I have 2 related questions. First question:



When using fixed effects, variables that are invariant over time will get 
washed out by the firm/subject level fixed effect. I've read that variables 
that are highly stable (i.e., show very little variation over time) may also 
largely get washed out by the fixed effect. However, I cannot find any 
references that provide guidelines for determining when a [key theoretical] 
variable is "too stable" to be accurately estimated via fixed effects. For 
example, if I have 10 years of annual data and a key variable is correlated 
0.91 with it's lag, is that "too stable"?



Second, if a Hausman test suggests that random effects are inappropriate, 
what might be a reasonable alternative to xtivreg with the fe option (note: 
the stable variable is not the endogenous one)? Would ivreg2 with gmm and 
cluster options be reasonable in this case ?



Thanks for any suggestions you can offer,

Jon O'Brien

Assistant Professor

University of Notre Dame



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