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st: xi: reg or xi: areg - yield different results in the constant term
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From |
Kaspar Dardas <[email protected]> |
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To |
[email protected] |
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Subject |
st: xi: reg or xi: areg - yield different results in the constant term |
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Date |
Thu, 14 Jan 2010 11:55:36 +0100 |
Hi statalisters,
I wan to run a multivariate regression on panel data with dummy
variables which control for years & sectors. Some sectors repeat
multiple times in the same year (thus
I am not able to tsset this panel data set- Stata give me an error message).
To control for the year and sector (firm) effects I tried all of the
approaches below. In (1) I simply use dummies for years and sectors,
in (2) I absorb sectors, in (3) I absorb years.
My problem is that the "constant" , as well as its t-value for each
of the three approaches is totally different (please see below). Why
is this? (Sorry, for this naive question but I am
extremely confused by this)? Shouldn't "areg XXXXXX, absorb()" yield
in the same results as xi with two dummy variables?
My second question:
Is there maybe any other method that I could use to absorb both year
and sector? My goal is actually not to show any of the regression
results for year AND sector.
I couldn't find anything on statalist.
(1) xi: reg CAR1 INSIDER_B INSIDER_C INSIDER_D MULTIPLE_TRADE
TRANSACTION_SIZE MARKET_CAPITALIZATION i.year i.sector , robust
(2) xi: areg CAR1 INSIDER_B INSIDER_C INSIDER_D MULTIPLE_TRADE
TRANSACTION_SIZE MARKET_CAPITALIZATION i.year, absorb(sector) robust
(3) xi: areg CAR1 INSIDER_B INSIDER_C INSIDER_D MULTIPLE_TRADE
TRANSACTION_SIZE MARKET_CAPITALIZATION i.sector, absorb(year) robust
Cheers,
Kaspar
. xi: reg CAR1 INSIDER_B INSIDER_C INSIDER_D MULTIPLE_TRADE
TRANSACTION_SIZE MARKET_CAPITALIZATION i.year i.sector , robust
i.year _Iyear_2003-2009 (naturally coded; _Iyear_2003 omitted)
i.sector _Isector_10-55 (naturally coded; _Isector_10 omitted)
Linear regression Number of obs = 1159
F( 21, 1137) = 6.14
Prob > F = 0.0000
R-squared = 0.1283
Root MSE = .12156
------------------------------------------------------------------------------
| Robust
CAR1 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
INSIDER_B | .0497534 .0168007 2.96 0.003 .0167895 .0827173
INSIDER_C | -.00264 .0078899 -0.33 0.738 -.0181203 .0128403
INSIDER_D | -.0178614 .014155 -1.26 0.207 -.0456343 .0099115
MULTIPLE_T~E | .0284563 .0079939 3.56 0.000 .0127718 .0441408
TRANSACTIO~E | .0185318 .0048029 3.86 0.000 .0091082 .0279554
MARKET_CAP~N | -.0012736 .0002546 -5.00 0.000 -.001773 -.0007741
_Iyear_2004 | -.0336727 .0227413 -1.48 0.139 -.0782923 .0109469
_Iyear_2005 | -.0238509 .0191565 -1.25 0.213 -.061437 .0137352
_Iyear_2006 | .0167628 .0196738 0.85 0.394 -.0218383 .0553639
_Iyear_2007 | -.0168189 .0184682 -0.91 0.363 -.0530545 .0194167
_Iyear_2008 | -.0097824 .0182258 -0.54 0.592 -.0455423 .0259776
_Iyear_2009 | .0543204 .0216637 2.51 0.012 .0118152 .0968256
_Isector_15 | -.0082766 .0159886 -0.52 0.605 -.039647 .0230939
_Isector_20 | .0013996 .0153361 0.09 0.927 -.0286907 .0314899
_Isector_25 | -.0389013 .0129421 -3.01 0.003 -.0642944 -.0135082
_Isector_30 | -.0495209 .0181734 -2.72 0.007 -.085178 -.0138637
_Isector_35 | .0050161 .0194823 0.26 0.797 -.0332093 .0432415
_Isector_40 | -.048742 .0138493 -3.52 0.000 -.075915 -.021569
_Isector_45 | -.0007909 .0151398 -0.05 0.958 -.0304959 .0289142
_Isector_50 | .0048057 .04511 0.11 0.915 -.0837026 .093314
_Isector_55 | -.0679753 .0213536 -3.18 0.001 -.1098721 -.0260784
_cons | .0499989 .0220629 2.27 0.024 .0067103 .0932874
. xi: areg CAR1 INSIDER_B INSIDER_C INSIDER_D MULTIPLE_TRADE
TRANSACTION_SIZE MARKET_CAPITALIZATION i.year, absorb(sector) robust
i.year _Iyear_2003-2009 (naturally coded; _Iyear_2003 omitted)
Linear regression, absorbing indicators Number of obs = 1159
F( 12, 1137) = 7.22
Prob > F = 0.0000
R-squared = 0.1283
Adj R-squared = 0.1122
Root MSE = .12156
------------------------------------------------------------------------------
| Robust
CAR1 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
INSIDER_B | .0497534 .0168007 2.96 0.003 .0167895 .0827173
INSIDER_C | -.00264 .0078899 -0.33 0.738 -.0181203 .0128403
INSIDER_D | -.0178614 .014155 -1.26 0.207 -.0456343 .0099115
MULTIPLE_T~E | .0284563 .0079939 3.56 0.000 .0127718 .0441408
TRANSACTIO~E | .0185318 .0048029 3.86 0.000 .0091082 .0279554
MARKET_CAP~N | -.0012736 .0002546 -5.00 0.000 -.001773 -.0007741
_Iyear_2004 | -.0336727 .0227413 -1.48 0.139 -.0782923 .0109469
_Iyear_2005 | -.0238509 .0191565 -1.25 0.213 -.061437 .0137352
_Iyear_2006 | .0167628 .0196738 0.85 0.394 -.0218383 .0553639
_Iyear_2007 | -.0168189 .0184682 -0.91 0.363 -.0530545 .0194167
_Iyear_2008 | -.0097824 .0182258 -0.54 0.592 -.0455423 .0259776
_Iyear_2009 | .0543204 .0216637 2.51 0.012 .0118152 .0968256
_cons | .0321451 .0183156 1.76 0.080 -.003791 .0680812
-------------+----------------------------------------------------------------
sector | absorbed (10 categories)
. xi: areg CAR1 INSIDER_B INSIDER_C INSIDER_D MULTIPLE_TRADE
TRANSACTION_SIZE MARKET_CAPITALIZATION i.sector, absorb(year) robust
i.sector _Isector_10-55 (naturally coded; _Isector_10 omitted)
Linear regression, absorbing indicators Number of obs = 1159
F( 15, 1137) = 5.87
Prob > F = 0.0000
R-squared = 0.1283
Adj R-squared = 0.1122
Root MSE = .12156
------------------------------------------------------------------------------
| Robust
CAR1 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
INSIDER_B | .0497534 .0168007 2.96 0.003 .0167895 .0827173
INSIDER_C | -.00264 .0078899 -0.33 0.738 -.0181203 .0128403
INSIDER_D | -.0178614 .014155 -1.26 0.207 -.0456343 .0099115
MULTIPLE_T~E | .0284563 .0079939 3.56 0.000 .0127718 .0441408
TRANSACTIO~E | .0185318 .0048029 3.86 0.000 .0091082 .0279554
MARKET_CAP~N | -.0012736 .0002546 -5.00 0.000 -.001773 -.0007741
_Isector_15 | -.0082766 .0159886 -0.52 0.605 -.039647 .0230939
_Isector_20 | .0013996 .0153361 0.09 0.927 -.0286907 .0314899
_Isector_25 | -.0389013 .0129421 -3.01 0.003 -.0642944 -.0135082
_Isector_30 | -.0495209 .0181734 -2.72 0.007 -.085178 -.0138637
_Isector_35 | .0050161 .0194823 0.26 0.797 -.0332093 .0432415
_Isector_40 | -.048742 .0138493 -3.52 0.000 -.075915 -.021569
_Isector_45 | -.0007909 .0151398 -0.05 0.958 -.0304959 .0289142
_Isector_50 | .0048057 .04511 0.11 0.915 -.0837026 .093314
_Isector_55 | -.0679753 .0213536 -3.18 0.001 -.1098721 -.0260784
_cons | .0519569 .0128407 4.05 0.000 .0267628 .077151
-------------+----------------------------------------------------------------
year | absorbed (7 categories)
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