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Re: st: Panel mixed-effects models

From   Jeph Herrin <[email protected]>
To   [email protected]
Subject   Re: st: Panel mixed-effects models
Date   Thu, 08 Mar 2012 16:19:59 -0500

If your panel id is panelID, try:

 xtmixed y || panelID: x, nocons

which specifies that x is random across panels but the intercept is not.


On 3/8/2012 1:13 PM, Downey, Patrick wrote:
Hi David,

Thanks for your response. As you suggested, I misspoke. I meant that I
expect the individual effects to be correlated with the covariates (X), as
you said, which violates the assumptions required for random individual

I agree with you that it is a bit odd to have random slopes and fixed
intercepts, but I can't think of anything that would be wrong with it. It
feels strange, but I haven't found any reason why it shouldn't be possible.


-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of David Hoaglin
Sent: Thursday, March 08, 2012 1:04 PM
To: [email protected]
Subject: Re: st: Panel mixed-effects models

The random-effects model does not assume absence of correlation between
individual effects (e.g., random intercepts) and Y.  Indeed, such effects
are often the main source of the correlation structure for Y.  Did you have
in mind the assumption that the random effects are not correlated with the
covariates (here, X_it)?  It seems a little odd to have random slopes but
fixed intercepts.

David Hoaglin

On Thu, Mar 8, 2012 at 12:12 PM, Downey, Patrick<[email protected]>  wrote:

I am trying to estimate a panel model of the form:
Y_it = a_i + a_t + B_i * X_it + e_it

I would like to use fixed effects for both of the 'a' coefficients
because I believe that the individual-effects are correlated with Y
(so the assumptions for random effects are not met). That would be a
simple two-way fixed effects model. However, I would like to use
random effects for the B coefficient. Thus, I want to assume B_i = B +
n_i, where n_i is a normally distributed random variable.

I cannot figure out how to estimate this model in Stata. It seems that
xtmixed should be able to handle it, but with large N or large T, I
think there are complications. I couldn't find examples (for xtmixed
or xtrc) that use fixed effects for individual- or time- effects but
random slope coefficients, although I think this is possible.
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