I am a bit confused about how to interpret the regression results in the following scenario:
I compare observations within countries by including fixed effects in my regression. The distribution of the sample in control and treatment group is similar to the following:
Country |
# observation C |
# observation T |
Type of Treatment |
A |
200 |
300 |
1 |
B |
300 |
200 |
2 |
C |
250 |
250 |
3 |
D |
250 |
600 |
1 |
... |
... |
... |
... |
C = control group
T = treatment.
I run the following regressions:
Code:
xtset country
gen treatment1=0
replace treatment1=1 if treatment==1
*regression type 1
xtreg y treatment1 ,fe vce (robust)
*regression type 2
xtreg y treatment1 treatment2 treatment3 ,fe vce (robust)
My confusion is caused by the fact that each country is actually treated only by ONE treatment. With the inclusion of country fixed effects, we would compare observations within each country. Would this mean, given how we have defined the treatment variable (treatment1), all countries are included in the regression and the interpretation of the estimate for treatment1 can be interpreted as the effect "comparing respondents in the treatment1 group with all other respondents (including whose who were not treated at all + those who are in treatment2 and treatment3)". Or is it "comparing control and treatment1 group
without considering any observations from the countries that are not treated with treatment 1 (treatment1=0 for all observations in these countries)?
And how would one interpret the different coefficients resulting from regression type 2?
0 Response to Interpreting regression results if some clusters are not treated
Post a Comment