diff Y, t(treated) period(post) cov(controls) cluster(ID)
where Y is the dependent variable, post is a dummy equal to one after the event, controls is a set of control variables and standard errors are clustered at firm ID level. I obtain the following output:
DIFFERENCE-IN-DIFFERENCES WITH COVARIATES | ||||
DIFFERENCE-IN-DIFFERENCES ESTIMATION RESULTS | ||||
Number of observations in the DIFF-IN-DIFF: 726 | ||||
Before | After | |||
Control | 230 | 210 | 440 | |
Treated | 147 | 139 | 286 | |
377 | 349 | |||
Outcome var. | Y | S. Err. | |t| | P>|t| |
Before | ||||
Control | 0.051 | |||
Treated | 0.046 | |||
Diff (T-C) | -0.005 | 0.003 | -1.47 | 0.147 |
After | ||||
Control | 0.053 | |||
Treated | 0.065 | |||
Diff (T-C) | 0.012 | 0.009 | 1.39 | 0.168 |
diff-in-diff | 0.017 | 0.007 | 2.28 | 0.025** |
R-square: 0.15 | ||||
* Means and Standard Errors are estimated by linear regression | ||||
**Clustered Std. Errors | ||||
**Inference: *** p<0.01; ** p<0.05; * p<0.1 |
My difference after and my difference before are not significant but my diff-in-diff term is. How can I interpret this result ?
I thank you for your help.
References
Villa, J.M., 2016. diff: Simplifying the estimation of difference-in-differences treatment effects. Stata Journal 16, pp. 52-71
0 Response to DIFF command results interpretation
Post a Comment