Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]
Re: st: RE: Difference in Difference vs. Fixed Effects
From
Joerg Lang <[email protected]>
To
[email protected]
Subject
Re: st: RE: Difference in Difference vs. Fixed Effects
Date
Thu, 3 Oct 2013 10:41:11 +0200
Hey Mustafa,
thanks for your response. I think that my sentence with the treatment
was kind of misleading. Treatment is the dummy for treatment but what
I really want to know is the Difference in Difference dummy (did).
I have the results below:
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)
------------------------------------------------------------------------------
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
sphohdum_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)
-------------------------------------------------------------------------------------
2013/10/2 Hussein, Mustafa (Mustafa Hussien) <[email protected]>:
> Hi Joerg,
>
> Can you post your results? You say that "treatment" was omitted from xtreg output. So what are you comparing your reg coefficients to then? In fixed effects I think you should be able specify a dummy for treatment.
>
> Mustafa
>
> ________________________________________
> From: [email protected] [[email protected]] on behalf of Joerg Lang [[email protected]]
> Sent: Wednesday, October 02, 2013 1:26 AM
> To: [email protected]
> Subject: st: Difference in Difference vs. Fixed Effects
>
> Dear Stalist users,
>
> currently writing my Master thesis and working with
> Stata 12, I have the following problem.
>
> I have a dataset on two time periods (2010 and 2012) and two groups
> (treatment and control). There is no treatment in the baseline and the
> treatment group uptakes the treatment between 2010 and 2012. The uptake is
> non-random.
> Now, I want to estimate the impact in a difference in difference design.
> At first, I estimate the following model:
> y b0+b1Time+b2Treatment+b3Time*Treatment+u
>
> using the -reg command:
>
> -reg y time treatment time*treatment, cluster (h1)
>
> while y is the outcome variable that is between 0 and 1 and h1 is the
> household identifier. I use the cluster option to account for the problem
> of serial correlation. In a second estimation I also include some other
> covariates.
>
> I always thought that this setting and a setting with fixed effects
> yield exactly the same result as long as one has only two points in time
> (in my case 2010 and 2012).
>
> However, estimating the same model with:
>
> - xtreg y Time Treatment Time*Treatment, fe vce(cluster h1)
>
> gives slightly different results. The difference increases when including
> more covariates, which are the same in both cases. As well, there is no
> variation in the households. Thus, the same households and the same
> variables are used in both estimations.
> Obviously, treatment is omitted in the xtreg case since it does not vary
> between time.
> However, I think that this should not change anything.
> My question is:
> Is my model correctly specified or did I overlook something?
> And, if my estimation is correct: Why this difference? Is this "normal"? If
> so, what does it tell me then, i.e. what is the reason for it?
>
> Since I have already been stuck with this problem for quite a while, any
> help or literature suggestions would be very much appreciated. Hope
> this question is not too trivial for you.
>
> Best regards,
>
> Joerg
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/faqs/resources/statalist-faq/
> * http://www.ats.ucla.edu/stat/stata/
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/faqs/resources/statalist-faq/
> * http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/faqs/resources/statalist-faq/
* http://www.ats.ucla.edu/stat/stata/