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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/

**Follow-Ups**:**Re: st: RE: Difference in Difference vs. Fixed Effects***From:*Joerg Lang <[email protected]>

**References**:**st: Difference in Difference vs. Fixed Effects***From:*Joerg Lang <[email protected]>

**st: RE: Difference in Difference vs. Fixed Effects***From:*"Hussein, Mustafa (Mustafa Hussien)" <[email protected]>

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