I am new to this forum. I've been working on province and year fixed effects and have to determine the following:
- Baseline (current regression)
- Baseline + province FEs
- Baseline + year FEs
- Baseline + province and year FEs
The command I've used for year fixed effect is as follows:
xtreg giniaftertax wage debt edu unempl i.year, fe
The Stata (17) output for time fixed effects:
Fixed-effects (within) regression Number of obs = 290
Group variable: province2 Number of groups = 10
R-squared: Obs per group:
Within = 0.5965 min = 29
Between = 0.2444 avg = 29.0
Overall = 0.1041 max = 29
F(32,248) = 11.46
corr(u_i, Xb) = -0.2288 Prob > F = 0.0000
------------------------------------------------------------------------------
giniaftertax | Coefficient Std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
wage | -.015787 .0045584 -3.46 0.001 -.024765 -.0068089
debt | -.0047514 .0024122 -1.97 0.050 -.0095023 -4.69e-07
edu | -.0230065 .015932 -1.44 0.150 -.0543858 .0083727
unempl | -.0003568 .0005727 -0.62 0.534 -.0014848 .0007712
|
year |
1991 | .001659 .0036165 0.46 0.647 -.0054639 .0087819
1992 | .0059149 .0037789 1.57 0.119 -.0015279 .0133576
1993 | -.0047124 .0038415 -1.23 0.221 -.0122785 .0028538
1994 | -.0035752 .0038273 -0.93 0.351 -.0111134 .0039631
1995 | -.0008383 .0037379 -0.22 0.823 -.0082003 .0065237
1996 | .0014287 .0039361 0.36 0.717 -.0063238 .0091811
1997 | .0025584 .0040056 0.64 0.524 -.0053309 .0104478
1998 | .014094 .003906 3.61 0.000 .0064008 .0217872
1999 | .0135665 .0038861 3.49 0.001 .0059125 .0212204
2000 | .019438 .0040101 4.85 0.000 .0115399 .0273361
2001 | .0208594 .003976 5.25 0.000 .0130284 .0286905
2002 | .0250461 .0040201 6.23 0.000 .0171283 .032964
2003 | .0215969 .0040066 5.39 0.000 .0137056 .0294882
2004 | .0244702 .0041125 5.95 0.000 .0163704 .0325699
2005 | .0237914 .0040532 5.87 0.000 .0158083 .0317746
2006 | .0265157 .004132 6.42 0.000 .0183775 .0346539
2007 | .0258257 .0042889 6.02 0.000 .0173784 .0342729
2008 | .0243988 .0042888 5.69 0.000 .0159517 .032846
2009 | .0274427 .0042705 6.43 0.000 .0190316 .0358538
2010 | .0266284 .0043256 6.16 0.000 .0181088 .0351479
2011 | .026752 .0045462 5.88 0.000 .0177979 .035706
2012 | .0274172 .0047169 5.81 0.000 .0181269 .0367075
2013 | .0350216 .0050894 6.88 0.000 .0249976 .0450456
2014 | .0295932 .0052916 5.59 0.000 .0191711 .0400154
2015 | .0344198 .0054243 6.35 0.000 .0237363 .0451034
2016 | .0266727 .0056189 4.75 0.000 .0156058 .0377396
2017 | .0333765 .006044 5.52 0.000 .0214723 .0452807
2018 | .0286212 .0062414 4.59 0.000 .0163283 .0409142
|
_cons | .3445261 .0237769 14.49 0.000 .2976957 .3913565
-------------+----------------------------------------------------------------
sigma_u | .01656777
sigma_e | .00778372
rho | .81918717 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(9, 248) = 62.28 Prob > F = 0.0000
The command I've used for province and year fixed effect is as follows:
xtreg giniaftertax wage debt edu unempl i.year i.province2 , fe
The Stata output for province and year fixed effect:
note: 2.province2 omitted because of collinearity.
note: 3.province2 omitted because of collinearity.
note: 4.province2 omitted because of collinearity.
note: 5.province2 omitted because of collinearity.
note: 6.province2 omitted because of collinearity.
note: 7.province2 omitted because of collinearity.
note: 8.province2 omitted because of collinearity.
note: 9.province2 omitted because of collinearity.
note: 10.province2 omitted because of collinearity.
Fixed-effects (within) regression Number of obs = 290
Group variable: province2 Number of groups = 10
R-squared: Obs per group:
Within = 0.5965 min = 29
Between = 0.2444 avg = 29.0
Overall = 0.1041 max = 29
F(32,248) = 11.46
corr(u_i, Xb) = -0.2288 Prob > F = 0.0000
------------------------------------------------------------------------------
giniaftertax | Coefficient Std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
wage | -.015787 .0045584 -3.46 0.001 -.024765 -.0068089
debt | -.0047514 .0024122 -1.97 0.050 -.0095023 -4.69e-07
edu | -.0230065 .015932 -1.44 0.150 -.0543858 .0083727
unempl | -.0003568 .0005727 -0.62 0.534 -.0014848 .0007712
|
year |
1991 | .001659 .0036165 0.46 0.647 -.0054639 .0087819
1992 | .0059149 .0037789 1.57 0.119 -.0015279 .0133576
1993 | -.0047124 .0038415 -1.23 0.221 -.0122785 .0028538
1994 | -.0035752 .0038273 -0.93 0.351 -.0111134 .0039631
1995 | -.0008383 .0037379 -0.22 0.823 -.0082003 .0065237
1996 | .0014287 .0039361 0.36 0.717 -.0063238 .0091811
1997 | .0025584 .0040056 0.64 0.524 -.0053309 .0104478
1998 | .014094 .003906 3.61 0.000 .0064008 .0217872
1999 | .0135665 .0038861 3.49 0.001 .0059125 .0212204
2000 | .019438 .0040101 4.85 0.000 .0115399 .0273361
2001 | .0208594 .003976 5.25 0.000 .0130284 .0286905
2002 | .0250461 .0040201 6.23 0.000 .0171283 .032964
2003 | .0215969 .0040066 5.39 0.000 .0137056 .0294882
2004 | .0244702 .0041125 5.95 0.000 .0163704 .0325699
2005 | .0237914 .0040532 5.87 0.000 .0158083 .0317746
2006 | .0265157 .004132 6.42 0.000 .0183775 .0346539
2007 | .0258257 .0042889 6.02 0.000 .0173784 .0342729
2008 | .0243988 .0042888 5.69 0.000 .0159517 .032846
2009 | .0274427 .0042705 6.43 0.000 .0190316 .0358538
2010 | .0266284 .0043256 6.16 0.000 .0181088 .0351479
2011 | .026752 .0045462 5.88 0.000 .0177979 .035706
2012 | .0274172 .0047169 5.81 0.000 .0181269 .0367075
2013 | .0350216 .0050894 6.88 0.000 .0249976 .0450456
2014 | .0295932 .0052916 5.59 0.000 .0191711 .0400154
2015 | .0344198 .0054243 6.35 0.000 .0237363 .0451034
2016 | .0266727 .0056189 4.75 0.000 .0156058 .0377396
2017 | .0333765 .006044 5.52 0.000 .0214723 .0452807
2018 | .0286212 .0062414 4.59 0.000 .0163283 .0409142
|
province2 |
BC | 0 (omitted)
MB | 0 (omitted)
NB | 0 (omitted)
NL | 0 (omitted)
NS | 0 (omitted)
ON | 0 (omitted)
PEI | 0 (omitted)
QC | 0 (omitted)
SK | 0 (omitted)
|
_cons | .3445261 .0237769 14.49 0.000 .2976957 .3913565
-------------+----------------------------------------------------------------
sigma_u | .01656777
sigma_e | .00778372
rho | .81918717 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(9, 248) = 62.28 Prob > F = 0.0000
Is it normal to have same coefficients for the 'year fixed effects' and 'year + province fixed effects'?
I've been trying to figure out this, but have not found any YouTube video/article discussing specifically about this issue.
Thanks in advance
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