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st: Cross-sectional multivariate regression which accounts for years and (repeated) sectors


From   Kaspar Dardas <[email protected]>
To   [email protected]
Subject   st: Cross-sectional multivariate regression which accounts for years and (repeated) sectors
Date   Mon, 11 Jan 2010 20:52:00 +0100

Dear all,

I have a question regarding a cross-sectional multivariate regression
with panal data (see below). My dependent variable is CAR1. I have
about 10 independent variables (not shown in the data set below).
I need to control for years and sectors (my data contains 10 years and
about 30 different sectors) in the regression. Sectors repeat multiple
times in the same year. I would like to know which method would be
best/ appropriate to run a regression on such a panel data set?
I have used sectors and years as dummies, however I would like know
wether there are any other options:

xi: reg CAR1 INSIDER_B INSIDER_C INSIDER_D MULTIPLE_TRADE
TRANSACTION_SIZE FIRM_SIZE i.sector i.year, robust

I understand "xtreg" to be an alternative to the above approach. Is
this correct? Is it possible to use xtreg with my "repeated time
variable" data set?
To sum it up, my question is how can I run the below regression in
such a way that years and sectors are "reflected" correctly? Any
comments would help!


CAR1            year            sector  gvkey        MULTIPLE_TRADE
.
.
.
0.0186186               2007            30              220550          0
0.0280388               2007            30              237421          0
0.1256196               2008            15              271390          0
0.0590132               2008            15              282561          1
0.0292866               2008            15              281720          0
0.0054281               2008            15              277495          0
0.1226206               2008            15              272627          0
0.0073848               2008            30              271598          1
0.0105465               2008            30              271390          0
0.2073587               2008            30              277495          0
0.0201788               2008            30              277495          0
.
.
.

Many thanks.
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