If you feel more confortable with AB/GMM, you could be more "safe" working
with a TAB and using -xtabond2- to improve your inference for the case of
heteroskedastic errors using Windmeijer-robust standard errors.
Windmeijer-correction to the standard errors of the second-step should work
fine for the case of unbiased estimators.
An important warning about WG versus AB/GMM (or TAB) is the fact that for
the first you don't need to choose predetermined variables or additional
instruments, which for some applications could be important. I am thinking
in model where the objective of study is an Euler Equation and the
researcher tries to prove a theory.
Best regards, Rodrigo.
----- Original Message -----
From: <[email protected]>
To: <[email protected]>
Sent: Saturday, July 28, 2007 8:41 PM
Subject: Re: st: using xtabond and xtabond2
> Michael Binder (Dynamic panel data models with homogeneous slopes) shows
> that
> the bias in the dynamic FE models is equal to
>
>
> (Embedded image moved to file: pic25996.jpg) where � is the true
> coefficient,
> and AT and BT complicated expressions that tend respectively to 0 and 1
> when the
> time dimension T tends to infinity. Consequently, with a very large T
> (say, more
> than 50), the bias is quasi non-existent. However, I had T>150 and one of
> the
> referees strongly complained why I am using FE, and not Arellano-Bond.
>
>
> Branko
>
>
>
>
> Development Research, World Bank
> Email: [email protected] or branko_mi@yahoo.
> tel: 202-473-6968
> World Bank, Room MC 3-581
> 1818 H Street NW
> Washington D.C. 20433
>
> For "Worlds Apart" see
> http://www.pupress.princeton.edu/titles/7946.html
>
> Website:
> http://econ.worldbank.org/projects/inequality
>
> For papers see also:
> http://econpapers.hhs.se/
> http://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=149002
>
>
>
> Michael Hanson
> <[email protected]
> om>
> To
> Sent by: [email protected]
> owner-statalist
> cc
> @hsphsun2.harva
> rd.edu
> Subject
> Re: st: using xtabond and xtabond2
>
> 07/28/2007
> 07:55 PM
>
>
> Please respond
> to
> statalist@hsphs
> un2.harvard.edu
>
>
>
>
>
>
> On Jul 28, 2007, at 6:56 PM, natalie chan wrote:
>
>> Maybe this is a question more about econometrics than about Stata but
>> I can't find anywhere more appropriate to ask this question. Thanks in
>> advance.
>>
>> I am doing regressions on economic growth equations with a panel data
>> of 20 years for 48 countries. I wanted to use dynamic panel approach
>> with xtabond or xtabond2, however, the Arellano-Bond methods are
>> specified for data with small T and large N. On the other hand, I
>> have seen some researchers using Arellano-Bond methods on growth
>> models, including Bond himself. Could anyone give me some advice on
>> this? Thanks a lot.
>
> I would like to expand Natalie's question: I have an
> application
> of
> dynamic panel data in which T/N is nearly 3, with N = 50. In David
> Roodman's excellent discussion of -xtabond2- [1], he writes, "If T is
> large, dynamic panel bias becomes insignificant, and a more
> straightforward fixed effects estimator works." (p. 42) However, I
> have never been able to find a discussion of how "large" of a T is
> "large enough" in the literature (which I interpret is part of
> Natalie's question). In the only textbook reference I have found,
> Baltagi (2005) [2] writes, "FE, GMM, and LIML exhibit a bias term in
> their asymptotic distributions; the biases are of the order 1/T, 1/N,
> and 1/(2N-T), respectively." (p. 153)
>
> Would it be reasonable, therefore, to conclude that in
> Natalie's
> case (T/N < 1/2), GMM (i.e. AB-type estimators) or LIML would be
> preferred, whereas in my case (T/N > 2.5), FE would be preferred? (I
> realize that this claim is based on asymptotic arguments, and that
> the N & T discussed here are probably too small. Any information
> about the small-sample properties of these estimators in a dynamic
> panel context would be appreciated as well.)
>
> I also recognize that this question is at least as much about
> statistics (econometrics) as about Stata, and I appreciate any help
> or suggestions.
>
> [1] <http://repec.org/nasug2006/howtodoxtabond2.cgdev.pdf>
> [2] <http://www.stata.com/bookstore/eapd.html>
>
>
> -- Mike
>
>
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