Sorry Mr. Elsner, this is my first time to learn scm. i still don't get it how can we determine the unit (country) for being our sintetic ? maybe for example in this case is the writers choose spain for being syntatic basque country? do we have any procedure for choosing it or we can choose any country freely? and is it limited for 1,2,3 or more country? or one is also enough? also what level unit analysist is it? province? region or country?
Hello! The idea behind SC is quite simple: one unit got treated, and we let the computer choose units that had not been treated but had similar outcomes before the treatment kicked in. So, in the case of Spanish regions, we had one unit that was affected by terrorism (the Basque Country). Then, we let the algorithm choose regions with a similar GDP path to the Basque country before the start of the terror. The weighted average of GDP of these control regions -- in this case only two, Madrid and Catalunya -- is the synthetic Basque Country. It gives you the path of GDP that the Basque Country would have had in absence of the terror. The weights are determined by the algorithm. As a researcher you have to make a few choices: 1) what is the treated region -- that's usually determined by your research question, 2) what are potential control regions (donor pool), 3) based on what variables do I want the algorithm to construct the synthetic control. The rest is done by the algorithm.
@@ben_elsner do potential control regions also determined by the algorithm? or we can include regions that have similiar outcome with treated before the treatment just like in DiD? is the similiar outcome enough or need another characteristic too? for example i want to evaluate a special policy in a province in Indonesia, should i include all of another province (indonesia has 34 provinces) become the donor pool? or just need some (similiar outcome, and control variabel).
@@ervinamunthe4797 no it is up to the researcher to choose which potential control units enter the donor pool. There are no set rules for how to do that. If you choose potential control units that are fundamentally different from the treated unit, the algorithm will not choose that as a control unit.
GREAT VIDEO!!! Looking forward to watch the other ones. Thank you so much for sharing!!
Great step by step lecture! I have a very clear understanding after only listening once.
It is easy to follow. Thank you!
Sorry Mr. Elsner, this is my first time to learn scm. i still don't get it how can we determine the unit (country) for being our sintetic ? maybe for example in this case is the writers choose spain for being syntatic basque country? do we have any procedure for choosing it or we can choose any country freely? and is it limited for 1,2,3 or more country? or one is also enough? also what level unit analysist is it? province? region or country?
Hello! The idea behind SC is quite simple: one unit got treated, and we let the computer choose units that had not been treated but had similar outcomes before the treatment kicked in. So, in the case of Spanish regions, we had one unit that was affected by terrorism (the Basque Country). Then, we let the algorithm choose regions with a similar GDP path to the Basque country before the start of the terror. The weighted average of GDP of these control regions -- in this case only two, Madrid and Catalunya -- is the synthetic Basque Country. It gives you the path of GDP that the Basque Country would have had in absence of the terror. The weights are determined by the algorithm. As a researcher you have to make a few choices: 1) what is the treated region -- that's usually determined by your research question, 2) what are potential control regions (donor pool), 3) based on what variables do I want the algorithm to construct the synthetic control. The rest is done by the algorithm.
@@ben_elsner ah i see! this explanations mean a lot to me, thankyou so much Mr. Elsner.
@@ben_elsner do potential control regions also determined by the algorithm? or we can include regions that have similiar outcome with treated before the treatment just like in DiD? is the similiar outcome enough or need another characteristic too? for example i want to evaluate a special policy in a province in Indonesia, should i include all of another province (indonesia has 34 provinces) become the donor pool? or just need some (similiar outcome, and control variabel).
@@ervinamunthe4797 no it is up to the researcher to choose which potential control units enter the donor pool. There are no set rules for how to do that. If you choose potential control units that are fundamentally different from the treated unit, the algorithm will not choose that as a control unit.
@@ervinamunthe4797 I would include all to begin with and let the algorithm choose which ones are getting included