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st: Re: dynamic panel models with fixed effects


From   "Rodrigo A. Alfaro" <[email protected]>
To   <[email protected]>
Subject   st: Re: dynamic panel models with fixed effects
Date   Sun, 9 Jul 2006 19:36:18 -0400

Tomislav,

In the following paper there is a rule of thumb for dynamic
panel data, that follows your intuitive analysis:

Hahn, J. and G. Kuersteiner (2002) "Asymptotically Unbiased 
Inference for a Dynamic Panel Model with Fixed Effects when 
both n and T are large," Econometrica, 70 (2002), 1639-1657

A draft version is available at
http://people.bu.edu/gkuerste/research/NTpanel.pdf

Section 3 is the case that you are looking for, equation 6.
Basically, the bias-corrected estimator (obtained in this paper) 
is b1 = (T+1)*b0 + 1/T, where b0 is MLE (OLS) estimator
or the estimator obtained by "brute force".

Rodrigo.



----- Original Message ----- 
From: "Tomislav Kovandzic" <[email protected]>
To: <[email protected]>
Sent: Saturday, July 08, 2006 2:22 PM
Subject: st: dynamic panel models with fixed effects


Dear List,

I'm working with state panel data for roughly 30 years and estimating a
fixed-effects model with a lagged dependent variable on the right-hand
side to address autocorrelation.  Several colleagues have informed me
that including a lagged dependent variables on the RHS when utilizing a
fixed-effects model is simply a no-no, i.e. such estimations yield
inconsistent estimates.  My question is whether the inconsistency dies
away as the number of time-periods goes off to infinity?  If so, are
there any rules of thumb as to how many time periods are needed to
mitigate the problems described above.  A reference would be much
appreciated.  If the estimates are inconsistent regardless of the number
of time-periods, can someone offer an alternative approach to correcting
for autocorrelation when using a fixed-effects model?  Would cluster
robust standard errors do the trick?  Thanks in advance.

Best,

Tom


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