I am currently conducting a synthetic control (sc) model and would now like to use my sc's in a diff in diff, hence a synthetic diff in diff (sdid). I cannot find code or help on how to run this in stata and am now looking for help here. Further on I am presenting one of my sc regressions and the output I received so you get a better understanding of my data.
I am using panel data which I collapsed to district level. I have three units (districts) and 5 time periods (1993, 1998, 2003, 2008, 2014). My pre-treatment units are 1993-2003 and 2008-2014 are post-treatment units. The treatmentperiod is between 2003 and 2008 hence I am using 2008 as my treatment period. The treated unit is unit 1.
The synth command I ran for my outcome variable age1birth (age at first birth):
Code:
synth age1birth inschool highestyeared edsingleyears age age1marr pregnevermarr marrneverpreg evermarried everpregnant evertested age1birth(1993) age1birth(1998) age1birth(2003), trunit(1) trperiod(2008) fig
HTML Code:
. synth age1birth inschool highestyeared edsingleyears age age1marr pregnevermarr marrneverpreg everma
> rried everpregnant evertested age1birth(1993) age1birth(1998) age1birth(2003), trunit(1) trperiod(20
> 08) fig //BEST
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Synthetic Control Method for Comparative Case Studies
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First Step: Data Setup
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control units: for 2 of out 2 units missing obs for predictor evertested in period 1993 -ignored for a
> veraging
treated unit: for 1 of out 1 units missing obs for predictor evertested in period 1993 -ignored for av
> eraging
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Data Setup successful
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Treated Unit: bungoma
Control Units: busia, kakamega
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Dependent Variable: age1birth
MSPE minimized for periods: 1993 1998 2003
Results obtained for periods: 1993 1998 2003 2008 2014
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Predictors: inschool highestyeared edsingleyears age age1marr pregnevermarr
marrneverpreg evermarried everpregnant evertested age1birth(1993)
age1birth(1998) age1birth(2003)
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Unless period is specified
predictors are averaged over: 1993 1998 2003
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Second Step: Run Optimization
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Optimization done
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Third Step: Obtain Results
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Loss: Root Mean Squared Prediction Error
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RMSPE | .4353367
---------------------
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Unit Weights:
-----------------------
Co_No | Unit_Weight
----------+------------
busia | .34
kakamega | .66
-----------------------
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Predictor Balance:
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| Treated Synthetic
-------------------------------+----------------------
inschool | .3921929 .3514998
highestyeared | 5.372596 5.27328
edsingleyears | 7.351375 6.917235
age | 19.25699 18.94241
age1marr | 17.64313 17.53984
pregnevermarr | .0714234 .0922194
marrneverpreg | .0400861 .0424411
evermarried | .415141 .3941894
everpregnant | .4464783 .4439676
evertested | .0751843 .0947261
age1birth(1993) | 18.05814 17.52789
age1birth(1998) | 18.48276 18.02413
age1birth(2003) | 17.98 17.70164
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.
end of do-fileCode:
reg age1birth treatment post impact, r
Many thanks for your help and I am happy to go more in detail if needed for an answer.
Best,
Anja
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