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st: Maarten: quick follow-up


From   "Nihal Pitigala" <pi.gala@hotmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: Maarten: quick follow-up
Date   Wed, 01 Nov 2006 16:56:29 -0500

Thanks Maarten, Sorry to pester you on this. I have a brief follow-up question you'll see at the end of the paragraph. I certainly would refere to XT manual on xtmixed. Looks like you offered some tips on this topic to a few. My initial idea is to run a cross section regression i.e. bilateral equation as shown below for the year 2001...where Ai is a set of exporter fixed effects, to control for cross-section stability (this is to control for individual contry specific heterogeneity?) . uijk is normally distributed error term, estimated through OLS.

Can you give me a laymans explanation to estimations such as differencing 1997 and 2001. Thanks very much again. this will help my understanding of Stata and method os estimation.

LnVSikj = Ai+ 1LnTarOik + 2LnTarPikj + 3LnICTikj + 4LnInfrOijk+ 5LnInfPijk
+ 6LnResik + 7LnCapik + 8LnPolik +9LnFinik +10LnGDPik + 11LnRemotijk (4) + Uijk


Nihal Pitigala:
If the data is set up as in the example you show, than you are ready to go:
just type -reg LnTrade LnTariff LnTransports- (without the hyphens). You
might want to consider moving into crossed random effects here using
-xtmixed-, since each pair of countries is nested within its constituent
countries plus each pair consists of multiple entries, which are again nested
within sector. The entry for -xtmixed- in the XT manual is good in explaining
how to set that model up.
HTH,
Maarten

-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands

visiting adress:
Buitenveldertselaan 3 (Metropolitan), room Z434

+31 20 5986715

http://home.fsw.vu.nl/m.buis/
-----------------------------------------

--- Nihal Pitigala wrote:

Data is in the following format:

Country Partner GTAP SectorLn Trade LnTariff Ln Transports
Albania Australia 21 agro -3.178341688 2.546306314 1.941615225
Albania Australia 22 milk -4.937585181 3.714802733 2.385086315
<snip>

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