Hi all, I am relative new to STATA and to panel data. I have a dataset with observations of 26 states, distributed in five socioeconomic macro-regions, from 2004 to 2015. The panel is strongly balanced and as I have multilevel time variant fixed effects, I run the reghdfe command and I guess my results are good for my proposal, desire to confirm the association between the dependent variable (imrr) and my independent variables. I clustered by factor variable (idh_f), for macro-region (mr_id) and for year. My results seem to be ok, I guess, but I am a little concerned about the loss of degrees of freedom (119) and about the quality of the parameters estimated and of the model as well. I guess that Root MS is ok and my R and R-adjusted statistics are fine as well?!? As far as I know I used a fair number of clusters (120), but I am not sure if this loss of DoF affects the quality of the model.
Anyone could help me to evaluate my model?
. reghdfe imrr occ_1 pib pbf gi ta tf prenat int_sinv, absorb(idh_f mr_id) vce(cluster idh_f#mr_id#year)
(MWFE estimator converged in 3 iterations)
HDFE Linear regression Number of obs = 312
Absorbing 2 HDFE groups F( 8, 119) = 58.12
Statistics robust to heteroskedasticity Prob > F = 0.0000
R-squared = 0.8063
Adj R-squared = 0.7979
Within R-sq. = 0.6538
Number of clusters (idh_f#mr_id#year) = 120Root MSE = 1.6719
(Std. Err. adjusted for 120 clusters in idh_f#mr_id#year)
------------------------------------------------------------------------------
| Robust
imrr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
occ_1 | -.213045 .0614771 -3.47 0.001 -.3347758 -.0913143
pib | -.0000948 .0000188 -5.04 0.000 -.000132 -.0000576
pbf | -.0844561 .0278709 -3.03 0.003 -.1396433 -.029269
gi | -.1085079 .0285647 -3.80 0.000 -.1650688 -.0519469
ta | .2166834 .1631563 1.33 0.187 -.1063824 .5397491
tf | 4.887433 .4666264 10.47 0.000 3.963466 5.8114
prenat | -1.33e-06 5.71e-07 -2.33 0.021 -2.46e-06 -2.00e-07
int_sinv | .0000319 7.36e-06 4.34 0.000 .0000174 .0000465
_cons | 38.29141 6.988698 5.48 0.000 24.45309 52.12973
------------------------------------------------------------------------------
Absorbed degrees of freedom:
-----------------------------------------------------+
Absorbed FE | Categories - Redundant = Num. Coefs |
-------------+---------------------------------------|
idh_f | 2 0 2 |
mr_id | 5 1 4 |
-----------------------------------------------------+
Thanks all.
Alexandre Bugelli
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