I have any issue regarding comparing the fixed-effect model and mundlak effect in controlling the means of time-variant variables as additional regressors.
Here are the results. I am wondering why the coefficient of fixed and random effect is slightly different. Might it be due to missing data?
thanks and regards,
PHP Code:
xtreg lremit $xlist0 i.year, vce(cluster pairid) fe
note: comlang_off omitted because of collinearity
note: colony omitted because of collinearity
note: contig omitted because of collinearity
Fixed-effects (within) regression Number of obs = 1102
Group variable: pairid Number of groups = 271
R-sq: within = 0.1197 Obs per group: min = 1
between = 0.5477 avg = 4.1
overall = 0.5723 max = 7
F(10,270) = 5.71
corr(u_i, Xb) = 0.0948 Prob > F = 0.0000
(Std. Err. adjusted for 271 clusters in pairid)
------------------------------------------------------------------------------
| Robust
lremit | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lgdpc | .4199601 .1413403 2.97 0.003 .141691 .6982293
lgdpc_hos | .2482984 .3412649 0.73 0.467 -.4235802 .9201771
lcost2 | -.1912492 .0978837 -1.95 0.052 -.3839617 .0014632
lmig_st | .3740764 .1592843 2.35 0.020 .0604792 .6876735
comlang_off | 0 (omitted)
colony | 0 (omitted)
contig | 0 (omitted)
|
year |
2012 | .0043988 .0190377 0.23 0.817 -.0330823 .04188
2013 | -.0265595 .0471652 -0.56 0.574 -.1194178 .0662988
2014 | -.0332107 .0542274 -0.61 0.541 -.1399731 .0735516
2015 | .1402847 .055213 2.54 0.012 .0315819 .2489875
2016 | .0661839 .0598106 1.11 0.269 -.0515705 .1839384
2017 | .0920051 .0592864 1.55 0.122 -.0247174 .2087276
|
_cons | -6.884898 5.217741 -1.32 0.188 -17.15753 3.387733
-------------+----------------------------------------------------------------
sigma_u | 1.2156288
sigma_e | .34090766
rho | .92708901 (fraction of variance due to u_i)
------------------------------------------------------------------------------
PHP Code:
xtreg lremit $xlist0 $vlist0 i.year, vce(cluster pairid)
Random-effects GLS regression Number of obs = 1102
Group variable: pairid Number of groups = 271
R-sq: within = 0.1197 Obs per group: min = 1
between = 0.6579 avg = 4.1
overall = 0.6785 max = 7
Wald chi2(17) = 847.77
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
(Std. Err. adjusted for 271 clusters in pairid)
--------------------------------------------------------------------------------
| Robust
lremit | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------------+----------------------------------------------------------------
lgdpc | .4439019 .1406352 3.16 0.002 .1682619 .7195418
lgdpc_hos | .2524156 .3360553 0.75 0.453 -.4062407 .9110718
lcost2 | -.2028169 .0977656 -2.07 0.038 -.3944339 -.0111998
lmig_st | .3689689 .1583542 2.33 0.020 .0586004 .6793375
comlang_off | .0681932 .1503237 0.45 0.650 -.2264358 .3628223
colony | -.135961 .1806898 -0.75 0.452 -.4901066 .2181845
contig | .0056654 .3514274 0.02 0.987 -.6831196 .6944504
lgdpc_mean | -.1943218 .1454022 -1.34 0.181 -.4793049 .0906614
lgdpc_hos_mean | -.0928574 .34678 -0.27 0.789 -.7725336 .5868189
lcost2_mean | -.3658746 .2326023 -1.57 0.116 -.8217667 .0900174
lmig_st_mean | .399029 .1679837 2.38 0.018 .0697869 .728271
|
year |
2012 | .0038119 .0192994 0.20 0.843 -.0340142 .0416381
2013 | -.02782 .0471031 -0.59 0.555 -.1201403 .0645004
2014 | -.0348137 .0541059 -0.64 0.520 -.1408593 .0712318
2015 | .1384236 .0552425 2.51 0.012 .0301503 .246697
2016 | .0623224 .0595451 1.05 0.295 -.0543839 .1790286
2017 | .089855 .0592783 1.52 0.130 -.0263284 .2060383
|
_cons | -7.467168 .8463628 -8.82 0.000 -9.126009 -5.808328
---------------+----------------------------------------------------------------
sigma_u | 1.0303308
sigma_e | .34090766
rho | .90132614 (fraction of variance due to u_i)
-------------------------------------------------------------------------------
0 Response to Why Mundlak and Fixed effect regression coefficient are not exactly same
Post a Comment