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Re: st: Stata 9.2 versus Limdep
"Marc Goergen" <goergenm@Cardiff.ac.uk>
Re: st: Stata 9.2 versus Limdep
Thu, 26 Mar 2009 16:44:37 +0000
I would like to provide you with further information about my query (see below for Michael's comments/queries).
1. I have always used Limdep and have only recently switched to Stata as Stata seems to be the only package able to estimate the Blundell-Bond (1998) system GMM estimator for a dynamic panel data model.
2. Bond (2002) explains the typical approach in determining whether the first-differenced GMM estimator (Arellano and Bond (1991) or the system GMM estimator is preferable for a particular model and dataset. An AR(1) regression is run using a pooled OLS regression and a Within Groups regression. Without going into too much detail, due to the omitted variable bias, the coefficient on the lagged dependent variable obtained from the pooled OLS regression tends to be upward biased and serves as an upper bound. Conversely, Within Groups tends to produce downward biased estimators. This is the reason why I used REGRESS and estimated a simple, pooled OLS regression.
3. SKIP is a command used in Limdep to ignore missing values. This is not done automatically and can create avoc.
Prof. Marc Goergen
Cardiff Business School
Cardiff CF10 3EU
Tel: 029 2087 6450
My working papers are available at:
>>> "Michael I. Lichter" <MLichter@Buffalo.EDU> 26/03/2009 16:03 >>>
That's not enough information for you to get an answer. What's special
about your dependent variable that led you to use LIMDEP? You're using
regular OLS regression in Stata; were you doing something different
there? What does SKIP mean? You can't assume that anybody here knows
enough about LIMDEP to interpret this. If you have fewer cases in Stata,
it's because something is missing. Were you doing pairwise deletion in
LIMDEP? Also, if this is panel data, why are you using regress instead
of xtreg? Explain this on the list, not to me directly.
Marc Goergen wrote:
> Dear all
> I have been running a pooled OLS regression on the same dataset in both Limdep and Stata 9.2. However, the results I obtained are significantly different:
> 1. Limdep seems to include roughly 10% more observations than Stata does, despite using the skip command in Limdep.
> 2. Some of the variables that were highly significant in Limdep are no longer significant in Stata. This is especially true for a dummy variable which was significant at the 0.1% level in Limdep, but at best has a p-value of 0.39 in Stata.
> 3. While for the case of Limdep the results for OLS without group dummy variables are significantly different from those with group dummy variables, in Stata the differences are much less pronounced.
> The command I used in Limdep is:
> REGRESS; LHS= LNAF; RHS= LNAF[-1],LNTA[-1], ...; STR=CODE; PERIOD=YEAR; PANEL$
> The command I used in Stata is:
> regress lnaf l.lnaf l.lnta ... , robust cluster(code)
> Dropping the "robust" and "cluster" options in Stata does not bring the results more in line with those obtained from Limdep.
> Best wishes,
> Prof. Marc Goergen
> Cardiff Business School
> Cardiff University
> Colum Drive
> Cardiff CF10 3EU
> Tel: 029 2087 6450
> My working papers are available at:
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
Michael I. Lichter, Ph.D.
Research Assistant Professor & NRSA Fellow
UB Department of Family Medicine / Primary Care Research Institute
UB Clinical Center, 462 Grider Street, Buffalo, NY 14215
Office: CC 125 / Phone: 716-898-4751 / E-Mail: firstname.lastname@example.org
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