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RE: st: fixed effects with multicollinearity
From
"Reddy, Colin" <[email protected]>
To
"[email protected]" <[email protected]>
Subject
RE: st: fixed effects with multicollinearity
Date
Fri, 29 Jul 2011 09:19:03 +0000
Yes, drop from the model.
The FE estimation in Stata does mean centering in any case but apparently it removes the effects of other time invariant variables in the model if any. Should one then use the OLS plus dummies? Can one simply add the "robust" to the code for OLS plus dummies to account for any heteroskedacity? I guess a post-estimation normality check is also in order?
Colin
________________________________________
From: [email protected] [[email protected]] on behalf of Nick Cox [[email protected]]
Sent: 29 July 2011 11:13 AM
To: [email protected]
Subject: Re: st: fixed effects with multicollinearity
Yes, if by drop you mean omit from the model (not -drop- from the
dataset). Best to do it on scientific, substantive or practical
grounds if there is a choice.
On Fri, Jul 29, 2011 at 10:07 AM, Reddy, Colin <[email protected]> wrote:
> Thanks Daniel
> So I guess the best is to drop one of the collinear variables.?
>
> Colin ________________________________________
>
> From: [email protected] [[email protected]] on behalf of daniel klein [[email protected]]
> Sent: 29 July 2011 11:01 AM
> To: [email protected]
> Subject: Re: st: fixed effects with multicollinearity
>
> Colin,
>
> please note that mean centring does nothing to solve the underlying
> problem of collinarity (if there is something like that)., see e.g.
> Echambadi and Hess (2007) or Shieh, G. (2011).
>
> However, in another post
> (http://www.stata.com/statalist/archive/2011-04/msg01204.html) Maarten
> Buis pointed out that in the special case, where a variable is
> interacted with itself, to model non-linearities, centering can help.
>
>
> Echambadi and Hess (2007). Mean-Centering Does Not Alleviate
> Collinearity Problems in Moderated Multiple Regression Models.
> Marketing Science, 26: 438-445
>
> Shieh, G. (2011). Clarifying the role of mean centring in
> multicollinearity of interaction effects. British Journal of
> Mathematical and Statistical Psychology, 64: 1-12
>
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