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RE: Re: st: RE: Difference in Difference vs. Fixed Effects


From   "Hussein, Mustafa (Mustafa Hussien)" <mhussei4@uthsc.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   RE: Re: st: RE: Difference in Difference vs. Fixed Effects
Date   Fri, 4 Oct 2013 18:23:38 +0000

Joerg,

Sorry, just noticed that "treatment" was dropped in both your FE regressions. Is it collinear with your 'followup"?

Mustafa
________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Hussein, Mustafa (Mustafa Hussien) [mhussei4@uthsc.edu]
Sent: Friday, October 04, 2013 1:18 PM
To: statalist@hsphsun2.harvard.edu
Subject: RE: Re: st: RE: Difference in Difference vs. Fixed Effects

Joreg,

I was just about to suggest that you use factor variables instead of the "did" term you made yourself, as Ariel just pointed out. The fact that "treatment" gets omitted in your fixed effects makes the coefficient estimate of your "did" problematic, since "did" is essentially an interaction term whose main effect, "treatment", was dropped. Another question, what does your "treatment" variable denote? if it's collinear with your DID setup, why was not it dropped when you ran DID-only FE regression? Is it collinear with any of your other x variables?

I hope this helps

Very Best,
Mustafa
________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Ariel Linden, DrPH [ariel.linden@gmail.com]
Sent: Friday, October 04, 2013 12:53 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: Re: st: RE: Difference in Difference vs. Fixed Effects

Joerg,

I've read through your post a couple times and I still don't understand what
you're asking. Please correct me if I am wrong but you get similar results
across all models, all indicating no treatment effect (based on the
covariate labeled "did"). You then ask why do you get different results when
you add additional covariates? Why would you think this is a problem with
the statistical model and not due to influences of the other covariates?

Also, as a matter of capitalizing on Stata's factor variable notation, you
should consider rerunning your regression as follows:

. regress gender_decision i.treatment##i.followup

This will allow you to run -margins- to get additional useful information,
such as:

. margins treatment, over(followup)
. margins treatment#followup, pwcompare(effects)

Ariel

Date: Thu, 3 Oct 2013 10:55:03 +0200
From: Joerg Lang <joerglang0@gmail.com>
Subject: Re: st: RE: Difference in Difference vs. Fixed Effects

I am sorry! This shouldn't have been sent in such a format. Here is
now the edited version of the tables. As you can see, they are -
despite some minor changes in the standard - pretty much the same when
there are no other covariates included. However, including these
covariates leads to more different results. If there is anyone that
could help me explaining what is either wrong with my Stata command or
point me in the right direction for the interpretiation that would be
really helpful.
The did denotes the difference in differece estimator and is thus the
one of interest. The treatment dummy is only included in the xtreg for
better "comparison". Obviously, one could have also construcet a
treatment dummy that varies between the time periods, i.e. 0 for both
treatment and control grouop in the baseline period and 1 for the
treatment group in the followup while 0 for the control group in the
followup. However, leaving the did estimator should yield the same
result since this is an interaction of treatment and time and thus 0
for both groups in the baseline period since time is 0. The value is 1
for the treatment group in the followup since both variables are then
1 but 0 for the case of the control group in the followup since the
control groups value is 0.


 reg gender_decision did treatment followup, cluster (h1)

Linear regression                                      Number of obs =
636
                                                               F(  3,
 317) =    5.77
                                                               Prob >
F      =  0.0007

R-squared     =  0.0233
                                                               Root
MSE      =   .3456

                                               (Std. Err. adjusted for
318 clusters in h1)
-
----------------------------------------------------------------------------
--
                                              Robust
   gender_dec~n |      Coef.       Std. Err.      t    P>|t|     [95%
Conf. Interval]
-
-------------+--------------------------------------------------------------
--
                    did |   .0913309   .0678396     1.35   0.179
- -.0421419    .2248037
          treatment |  -.0164835   .0396981    -0.42   0.678
- -.0945886    .0616215
            followup |   .0864469   .0292938     2.95   0.003
.028812    .1440818
              _cons |   .2387057   .0157684    15.14   0.000
.2076819    .2697296
-
----------------------------------------------------------------------------
--




 xtreg gender_decision treatment did followup, fe vce(cluster h1)
note: treatment omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =
636
Group variable: h1                                 Number of groups
=       318

R-sq:  within  = 0.0465                         Obs per group: min =
2
       between = 0.0016
avg =       2.0
       overall = 0.0230
  max =         2

                                                         F(2,317)
     =      8.59
corr(u_i, Xb)  = -0.0067                        Prob > F           =
0.0002

                                   (Std. Err. adjusted for 318 clusters in
h1)
-
----------------------------------------------------------------------------
--
             |                          Robust
gender_dec~n |      Coef.      Std. Err.      t       P>|t|
[95% Conf. Interval]
-
-------------+--------------------------------------------------------------
--
       treatment |          0  (omitted)
                did |   .0913309    .067786     1.35   0.179
- -.0420364    .2246982
         followup |   .0864469   .0292707     2.95   0.003
.0288575    .1440363
            _cons |   .2363732   .0132882    17.79   0.000
.210229    .2625174
-
-------------+--------------------------------------------------------------
--
        sigma_u |  .25124096
        sigma_e |  .33511619
               rho |  .35982364   (fraction of variance due to u_i)
-
----------------------------------------------------------------------------
--



With more controls:




 reg gender_decision did treatment followup log_hhsize h16_hoh
h16_hohsp hohdum_edu_no_imp sphohdum
> _edu_no_imp asset_Index_imp women_groupmember log_hexp, cluster (h1)

Linear regression                                      Number of obs =
636
                                                              F( 11,
317) =    2.64
                                                              Prob > F
     =  0.0030

R-squared     =  0.0379
                                                             Root MSE
    =  .34518

                                          (Std. Err. adjusted for 318
clusters in h1)
-
----------------------------------------------------------------------------
---------
                                     |               Robust
            gender_decision |      Coef.   Std. Err.      t    P>|t|
  [95% Conf. Interval]
-
--------------------+-------------------------------------------------------
---------
                               did |   .0775325   .0689252     1.12
0.261    -.0580762    .2131412
                     treatment |  -.0422406   .0423164    -1.00
0.319     -.125497    .0410158
                       followup |   .0816601   .0315261     2.59
0.010     .0196332     .143687
                   log_hhsize |  -.0050365      .0308    -0.16   0.870
   -.0656347    .0555617
                      h16_hoh |   .0002403   .0019649     0.12   0.903
   -.0036256    .0041061
                   h16_hohsp |   -.000707   .0023795    -0.30   0.767
  -.0053886    .0039746
    hohdum_edu_no_imp |    .015657   .0364541     0.43   0.668
- -.0560656    .0873795
s phohdum_edu_no_imp |   .0712825   .0410581     1.74   0.084
- -.0094982    .1520633
           asset_Index_imp |   .0650232   .0761579     0.85   0.394
- -.0848155     .214862
    women_groupmember |   .0290404     .03097     0.94   0.349
- -.0318924    .0899731
                       log_hexp |   .0190211   .0207127     0.92
0.359    -.0217307    .0597728
                           _cons |   .0026582   .2046481     0.01
0.990    -.3999819    .4052984
-
----------------------------------------------------------------------------
---------



xtreg gender_decision treatment did followup log_hhsize h16_hoh
h16_hohsp hohdum_edu_no_imp sphohd
> um_edu_no_imp asset_Index_imp women_groupmember log_hexp, fe vce(cluster
h1)
note: treatment omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =
636
Group variable: h1                              Number of groups   =
318

R-sq:  within  = 0.0723                         Obs per group: min =
2
       between = 0.0005                                        avg =
2.0
       overall = 0.0140                                        max =
2

                                                F(10,317)          =
2.80
corr(u_i, Xb)  = -0.2809                        Prob > F           =
0.0024

                                          (Std. Err. adjusted for 318
clusters in h1)
-
----------------------------------------------------------------------------
---------
                                     |               Robust
           gender_decision |      Coef.   Std. Err.      t    P>|t|
 [95% Conf. Interval]
-
--------------------+-------------------------------------------------------
---------
                    treatment |          0  (omitted)
                             did |   .0944656   .0685701     1.38
0.169    -.0404444    .2293756
                      followup |   .0637825   .0348781     1.83
0.068    -.0048393    .1324043
                  log_hhsize |  -.0601096   .0553426    -1.09   0.278
  -.1689948    .0487756
                     h16_hoh |  -.0014844   .0055086    -0.27   0.788
  -.0123225    .0093537
                  h16_hohsp |    .005337   .0047125     1.13   0.258
 -.0039347    .0146088
   hohdum_edu_no_imp |   .1778034   .0849698     2.09   0.037
.0106275    .3449793
sphohdum_edu_no_imp |   .0998635   .0816447     1.22   0.222
- -.0607705    .2604975
         asset_Index_imp |   .0307611   .1463719     0.21   0.834
- -.257222    .3187443
  women_groupmember |   .0098729   .0503457     0.20   0.845
- -.0891811    .1089268
                     log_hexp |  -.0025051   .0278105    -0.09   0.928
   -.0572215    .0522113
                         _cons |   .1998801   .3670395     0.54
0.586    -.5222612    .9220215
-
--------------------+-------------------------------------------------------
---------
            sigma_u |  .26714979
            sigma_e |  .33481165
                rho |  .38900009   (fraction of variance due to u_i)
-
----------------------------------------------------------------------------
---------






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