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Re: st: Regression with about 5000 (dummy) variables

From   John Antonakis <>
Subject   Re: st: Regression with about 5000 (dummy) variables
Date   Fri, 20 Apr 2012 16:06:17 +0200

OK; I did call it a trick, didn't I? :-)

Though, what matters is that the estimator is consistent, and computationally efficient. That is the problem that this estimator can address in high-dimensional fixed-effect data. It takes a second to estimate something that take hours with dummy variables. So I take back the comment on the DFs.



Prof. John Antonakis
Faculty of Business and Economics
Department of Organizational Behavior
University of Lausanne
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The Leadership Quarterly

On 20.04.2012 15:33, Christopher Baum wrote:
On Apr 20, 2012, at 2:33 AM, John wrote:

The estimator still seems good. Notice, though, that the F-test
numerator DFs are only 3.  So that's what I meant when I said we save on
DF (as compared to the OLS fixed-effects estimator).
You're cheating, John, by overlooking that theorem about the absence of a free lunch.
The number of DF is not 3. When you gave the commands

bys idcode : egen double cl_age_id = mean(age)
bys south : egen double cl_age_south = mean(age)

you computed a large number of sample means, so the cluster-mean regressors in the Mundlak
model must be considered as not single DF, but as many DF as it took to compute them,
following the logic of the FE model.

I could make the same mistake by applying the within transformation to Y and X and
running OLS, which would have one DF for the one slope estimated. But if I used the
FE estimator it would properly account for the fact that the within transformation is not
free, as this is just the LSDV (dummy-variable) model, and putting in all those dummies is not free.
Neither is this method. Your DF should be adjusted to reflect the creation of those
cl_* variables.


Kit Baum   |   Boston College Economics&  DIW Berlin   |
                              An Introduction to Stata Programming  |
   An Introduction to Modern Econometrics Using Stata  |

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