I am running a difference in differences regression, where my treatment variable is called beneficiaria_dum and I have data for 2010, 2011, 2012, 2013, 2015, 2016, 2017 and 2018. The program was implemented in 2014 (and there are no test scores for that year, since the test was in the process of being redesigned). My regression looks like this:
As you can see many interactions are dropped because of collinearity, but I do not know the variables they are collinear with.. Is there a way (a command) to know exactly which variables are they collinear with? In particular, I am interested in the 1.beneficiaria_dum#1.dummy2018 interaction, since that is one of the coefficients of interest in my work.
Thanks a lot in advance.
Code:
#delimit;
delimiter now ;
. reghdfe logro_mate_porcentajealum_nivel4 1.beneficiaria_dum#1.dummy2010
> 1.beneficiaria_dum#1.dummy2011 1.beneficiaria_dum#1.dummy2012 1.beneficiaria_dum#1.dummy2015
> 1.beneficiaria_dum#1.dummy2016 1.beneficiaria_dum#1.dummy2017 1.beneficiaria_dum#1.dummy2018
> 1.pizarron_dum#1.dummy2010 1.wc_dum#1.dummy2010 1.sin_agua_dum#1.dummy2010 1.tipo_inmueble_dum#1.dummy2010
> 1.piso_tierra_dum#1.dummy2010 1.turno_dum1#1.dummy2010 1.turno_dum2#1.dummy2010
> 1.silla_alumnos_dum#1.dummy2010 1.mesa_alumnos_dum#1.dummy2010 1.silla_profesores_dum#1.dummy2010 1.mesa_profesores_
> dum#1.dummy2010
> 1.pizarron_dum#1.dummy2011 1.wc_dum#1.dummy2011 1.sin_agua_dum#1.dummy2011 1.tipo_inmueble_dum#1.dummy2011
> 1.piso_tierra_dum#1.dummy2011 1.turno_dum1#1.dummy2011 1.turno_dum2#1.dummy2011
> 1.silla_alumnos_dum#1.dummy2011 1.mesa_alumnos_dum#1.dummy2011 1.silla_profesores_dum#1.dummy2011 1.mesa_profesores_
> dum#1.dummy2011
> 1.pizarron_dum#1.dummy2012 1.wc_dum#1.dummy2012 1.sin_agua_dum#1.dummy2012 1.tipo_inmueble_dum#1.dummy2012
> 1.piso_tierra_dum#1.dummy2012 1.turno_dum1#1.dummy2012 1.turno_dum2#1.dummy2012
> 1.silla_alumnos_dum#1.dummy2012 1.mesa_alumnos_dum#1.dummy2012 1.silla_profesores_dum#1.dummy2012 1.mesa_profesores_
> dum#1.dummy2012
> 1.pizarron_dum#1.dummy2015 1.wc_dum#1.dummy2015 1.sin_agua_dum#1.dummy2015 1.tipo_inmueble_dum#1.dummy2015
> 1.piso_tierra_dum#1.dummy2015 1.turno_dum1#1.dummy2015 1.turno_dum2#1.dummy2015
> 1.silla_alumnos_dum#1.dummy2015 1.mesa_alumnos_dum#1.dummy2015 1.silla_profesores_dum#1.dummy2015 1.mesa_profesores_
> dum#1.dummy2015
> 1.pizarron_dum#1.dummy2016 1.wc_dum#1.dummy2016 1.sin_agua_dum#1.dummy2016 1.tipo_inmueble_dum#1.dummy2016
> 1.piso_tierra_dum#1.dummy2016 1.turno_dum1#1.dummy2016 1.turno_dum2#1.dummy2016
> 1.silla_alumnos_dum#1.dummy2016 1.mesa_alumnos_dum#1.dummy2016 1.silla_profesores_dum#1.dummy2016 1.mesa_profesores_
> dum#1.dummy2016
> 1.pizarron_dum#1.dummy2017 1.wc_dum#1.dummy2017 1.sin_agua_dum#1.dummy2017 1.tipo_inmueble_dum#1.dummy2017
> 1.piso_tierra_dum#1.dummy2017 1.turno_dum1#1.dummy2017 1.turno_dum2#1.dummy2017
> 1.silla_alumnos_dum#1.dummy2017 1.mesa_alumnos_dum#1.dummy2017 1.silla_profesores_dum#1.dummy2017 1.mesa_profesores_
> dum#1.dummy2017
> 1.pizarron_dum#1.dummy2018 1.wc_dum#1.dummy2018 1.sin_agua_dum#1.dummy2018 1.tipo_inmueble_dum#1.dummy2018
> 1.piso_tierra_dum#1.dummy2018 1.turno_dum1#1.dummy2018 1.turno_dum2#1.dummy2018
> 1.silla_alumnos_dum#1.dummy2018 1.mesa_alumnos_dum#1.dummy2018 1.silla_profesores_dum#1.dummy2018 1.mesa_profesores_
> dum#1.dummy2018 if nivel=="PRIMARIA",
> absorb(beneficiaria_dum dummy2010 dummy2011 dummy2012 dummy2015 dummy2016 dummy2017 dummy2018
> estado_dum1 estado_dum2 estado_dum3 estado_dum4 estado_dum5 estado_dum6 estado_dum7 estado_dum8
> estado_dum9 estado_dum10 estado_dum11 estado_dum12 estado_dum13 estado_dum14 estado_dum15 estado_dum16
> estado_dum17 estado_dum18 estado_dum19 estado_dum20 estado_dum21 estado_dum22 estado_dum23 estado_dum24
> estado_dum25 estado_dum26 estado_dum27 estado_dum28 estado_dum29 estado_dum30 estado_dum31 pizarron_dum
> wc_dum sin_agua_dum tipo_inmueble_dum piso_tierra_dum turno_dum1 turno_dum2 silla_alumnos_dum mesa_alumnos_dum silla
> _profesores_dum mesa_profesores_dum);
(warning: absorbing 50 dimensions of fixed effects; check that you really want that)
(dropped 1 singleton observations)
note: 1bn.turno_dum1#1bn.dummy2010 is probably collinear with the fixed effects (all partialled-out values are close t
> o zero; tol = 1.0e-09)
note: 1bn.turno_dum1#1bn.dummy2011 is probably collinear with the fixed effects (all partialled-out values are close t
> o zero; tol = 1.0e-09)
note: 1bn.turno_dum1#1bn.dummy2012 is probably collinear with the fixed effects (all partialled-out values are close t
> o zero; tol = 1.0e-09)
note: 1bn.turno_dum1#1bn.dummy2018 is probably collinear with the fixed effects (all partialled-out values are close t
> o zero; tol = 1.0e-09)
(MWFE estimator converged in 12 iterations)
note: 1.beneficiaria_dum#1.dummy2018 omitted because of collinearity
note: 1.turno_dum1#1.dummy2010 omitted because of collinearity
note: 1.turno_dum1#1.dummy2011 omitted because of collinearity
note: 1.turno_dum1#1.dummy2012 omitted because of collinearity
note: 1.turno_dum1#1.dummy2016 omitted because of collinearity
note: 1.pizarron_dum#1.dummy2018 omitted because of collinearity
note: 1.wc_dum#1.dummy2018 omitted because of collinearity
note: 1.tipo_inmueble_dum#1.dummy2018 omitted because of collinearity
note: 1.turno_dum1#1.dummy2018 omitted because of collinearity
note: 1.silla_alumnos_dum#1.dummy2018 omitted because of collinearity
note: 1.mesa_alumnos_dum#1.dummy2018 omitted because of collinearity
note: 1.silla_profesores_dum#1.dummy2018 omitted because of collinearity
note: 1.mesa_profesores_dum#1.dummy2018 omitted because of collinearity
HDFE Linear regression Number of obs = 1,009
Absorbing 50 HDFE groups F( 41, 930) = 1.14
Prob > F = 0.2505
R-squared = 0.1418
Adj R-squared = 0.0698
Within R-sq. = 0.0480
Root MSE = 14.3655
------------------------------------------------------------------------------------------------
logro_mate_porcentajealum_ni~4 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------------------------+----------------------------------------------------------------
beneficiaria_dum#dummy2010 |
1 1 | 2.698296 4.431904 0.61 0.543 -5.999396 11.39599
|
beneficiaria_dum#dummy2011 |
1 1 | 3.10533 4.40877 0.70 0.481 -5.546961 11.75762
|
beneficiaria_dum#dummy2012 |
1 1 | 4.525858 4.716639 0.96 0.338 -4.730633 13.78235
|
beneficiaria_dum#dummy2015 |
1 1 | 3.681236 6.558894 0.56 0.575 -9.190711 16.55318
|
beneficiaria_dum#dummy2016 |
1 1 | 11.71693 4.996448 2.35 0.019 1.911312 21.52255
|
beneficiaria_dum#dummy2017 |
1 1 | 0 (empty)
|
beneficiaria_dum#dummy2018 |
1 1 | 0 (omitted)
|
pizarron_dum#dummy2010 |
1 1 | .895366 4.461714 0.20 0.841 -7.860829 9.651561
|
wc_dum#dummy2010 |
1 1 | .432189 4.201146 0.10 0.918 -7.812637 8.677015
|
sin_agua_dum#dummy2010 |
1 1 | 0 (empty)
|
tipo_inmueble_dum#dummy2010 |
1 1 | .240102 3.273016 0.07 0.942 -6.183251 6.663455
|
piso_tierra_dum#dummy2010 |
1 1 | 0 (empty)
|
turno_dum1#dummy2010 |
1 1 | 0 (omitted)
|
turno_dum2#dummy2010 |
1 1 | 0 (empty)
|
silla_alumnos_dum#dummy2010 |
1 1 | -.3236809 4.702296 -0.07 0.945 -9.552022 8.90466
|
mesa_alumnos_dum#dummy2010 |
1 1 | -.432012 4.964168 -0.09 0.931 -10.17428 9.310257
|
silla_profesores_dum#dummy2010 |
1 1 | .3931254 4.302207 0.09 0.927 -8.050034 8.836284
|
mesa_profesores_dum#dummy2010 |
1 1 | .0323175 4.432294 0.01 0.994 -8.666139 8.730774
|
pizarron_dum#dummy2011 |
1 1 | -.2159164 4.444212 -0.05 0.961 -8.937762 8.50593
|
wc_dum#dummy2011 |
1 1 | .7360053 4.189108 0.18 0.861 -7.485196 8.957206
|
sin_agua_dum#dummy2011 |
1 1 | 0 (empty)
|
tipo_inmueble_dum#dummy2011 |
1 1 | .7868183 3.22659 0.24 0.807 -5.545422 7.119059
|
piso_tierra_dum#dummy2011 |
1 1 | 0 (empty)
|
turno_dum1#dummy2011 |
1 1 | 0 (omitted)
|
turno_dum2#dummy2011 |
1 1 | 0 (empty)
|
silla_alumnos_dum#dummy2011 |
1 1 | -.0911574 4.629084 -0.02 0.984 -9.175818 8.993503
|
mesa_alumnos_dum#dummy2011 |
1 1 | -.1454528 4.9077 -0.03 0.976 -9.776902 9.485996
|
silla_profesores_dum#dummy2011 |
1 1 | .9533241 4.215804 0.23 0.821 -7.320267 9.226915
|
mesa_profesores_dum#dummy2011 |
1 1 | -.284886 4.361899 -0.07 0.948 -8.845191 8.275419
|
pizarron_dum#dummy2012 |
1 1 | 2.758431 4.637395 0.59 0.552 -6.342541 11.8594
|
wc_dum#dummy2012 |
1 1 | 1.569684 4.386536 0.36 0.721 -7.038973 10.17834
|
sin_agua_dum#dummy2012 |
1 1 | 0 (empty)
|
tipo_inmueble_dum#dummy2012 |
1 1 | 1.323632 3.459004 0.38 0.702 -5.464727 8.111991
|
piso_tierra_dum#dummy2012 |
1 1 | 0 (empty)
|
turno_dum1#dummy2012 |
1 1 | 0 (omitted)
|
turno_dum2#dummy2012 |
1 1 | 0 (empty)
|
silla_alumnos_dum#dummy2012 |
1 1 | 2.647935 4.883502 0.54 0.588 -6.936026 12.2319
|
mesa_alumnos_dum#dummy2012 |
1 1 | .0860184 5.167437 0.02 0.987 -10.05517 10.22721
|
silla_profesores_dum#dummy2012 |
1 1 | -2.162783 4.330258 -0.50 0.618 -10.66099 6.335427
|
mesa_profesores_dum#dummy2012 |
1 1 | -.3624333 4.597509 -0.08 0.937 -9.385128 8.660261
|
pizarron_dum#dummy2015 |
1 1 | 7.81126 5.760071 1.36 0.175 -3.492982 19.1155
|
wc_dum#dummy2015 |
1 1 | 3.107634 5.732913 0.54 0.588 -8.143311 14.35858
|
sin_agua_dum#dummy2015 |
1 1 | 0 (empty)
|
tipo_inmueble_dum#dummy2015 |
1 1 | 3.829595 4.303029 0.89 0.374 -4.615176 12.27437
|
piso_tierra_dum#dummy2015 |
1 1 | 0 (empty)
|
turno_dum1#dummy2015 |
1 1 | -8.687047 20.84659 -0.42 0.677 -49.59886 32.22477
|
turno_dum2#dummy2015 |
1 1 | 0 (empty)
|
silla_alumnos_dum#dummy2015 |
1 1 | 4.045762 6.133607 0.66 0.510 -7.991552 16.08308
|
mesa_alumnos_dum#dummy2015 |
1 1 | -8.565857 6.539092 -1.31 0.191 -21.39894 4.26723
|
silla_profesores_dum#dummy2015 |
1 1 | 5.846915 5.161505 1.13 0.258 -4.282632 15.97646
|
mesa_profesores_dum#dummy2015 |
1 1 | -5.318803 5.289155 -1.01 0.315 -15.69887 5.06126
|
pizarron_dum#dummy2016 |
1 1 | -7.246384 4.65018 -1.56 0.120 -16.37245 1.879678
|
wc_dum#dummy2016 |
1 1 | .1846986 4.481944 0.04 0.967 -8.611197 8.980594
|
sin_agua_dum#dummy2016 |
1 1 | 0 (empty)
|
tipo_inmueble_dum#dummy2016 |
1 1 | 4.045632 3.41752 1.18 0.237 -2.661313 10.75258
|
piso_tierra_dum#dummy2016 |
1 1 | 0 (empty)
|
turno_dum1#dummy2016 |
1 1 | 0 (omitted)
|
turno_dum2#dummy2016 |
1 1 | 0 (empty)
|
silla_alumnos_dum#dummy2016 |
1 1 | -.3680558 4.812211 -0.08 0.939 -9.812106 9.075995
|
mesa_alumnos_dum#dummy2016 |
1 1 | 5.100953 5.083678 1.00 0.316 -4.875858 15.07776
|
silla_profesores_dum#dummy2016 |
1 1 | 7.050462 4.564797 1.54 0.123 -1.908034 16.00896
|
mesa_profesores_dum#dummy2016 |
1 1 | 6.226236 4.609409 1.35 0.177 -2.819812 15.27228
|
pizarron_dum#dummy2017 |
1 1 | 0 (empty)
|
wc_dum#dummy2017 |
1 1 | 0 (empty)
|
sin_agua_dum#dummy2017 |
1 1 | 0 (empty)
|
tipo_inmueble_dum#dummy2017 |
1 1 | 0 (empty)
|
piso_tierra_dum#dummy2017 |
1 1 | 0 (empty)
|
turno_dum1#dummy2017 |
1 1 | 0 (empty)
|
turno_dum2#dummy2017 |
1 1 | 0 (empty)
|
silla_alumnos_dum#dummy2017 |
1 1 | 0 (empty)
|
mesa_alumnos_dum#dummy2017 |
1 1 | 0 (empty)
|
silla_profesores_dum#dummy2017 |
1 1 | 0 (empty)
|
mesa_profesores_dum#dummy2017 |
1 1 | 0 (empty)
|
pizarron_dum#dummy2018 |
1 1 | 0 (omitted)
|
wc_dum#dummy2018 |
1 1 | 0 (omitted)
|
sin_agua_dum#dummy2018 |
1 1 | 0 (empty)
|
tipo_inmueble_dum#dummy2018 |
1 1 | 0 (omitted)
|
piso_tierra_dum#dummy2018 |
1 1 | 0 (empty)
|
turno_dum1#dummy2018 |
1 1 | 0 (omitted)
|
turno_dum2#dummy2018 |
1 1 | 0 (empty)
|
silla_alumnos_dum#dummy2018 |
1 1 | 0 (omitted)
|
mesa_alumnos_dum#dummy2018 |
1 1 | 0 (omitted)
|
silla_profesores_dum#dummy2018 |
1 1 | 0 (omitted)
|
mesa_profesores_dum#dummy2018 |
1 1 | 0 (omitted)
|
_cons | -2.460428 3.867313 -0.64 0.525 -10.0501 5.129245
------------------------------------------------------------------------------------------------
Thanks a lot in advance.
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