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


From   "Jon O'Brien" <jobrien2@nd.edu>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Fixed effects and stable variables: xtivreg or ivreg2?
Date   Sun, 4 Jun 2006 23:51:46 -0400

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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