Timeline for How can we explain the meaning of some specific coefficients in generalized Difference-in-Difference?
Current License: CC BY-SA 4.0
12 events
| when toggle format | what | by | license | comment | |
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| Jun 10, 2021 at 2:52 | history | bounty ended | Phil Nguyen | ||
| Jun 10, 2021 at 2:51 | vote | accept | Phil Nguyen | ||
| Jun 10, 2021 at 2:51 | comment | added | Phil Nguyen | Thank you so much, Ariel, it is clear to me now | |
| Jun 10, 2021 at 2:50 | comment | added | Ariel | Not quite, it is the average difference between pre- and post for the treated population. Because the ATT is the effect on the treated population of the intervention. Remember, DID is using the common trends assumption to try to tell us what would have happened to the treated population had they not been treated. It then compares the realized treated outcomes to the predicted untreated counterfactual. | |
| Jun 10, 2021 at 2:46 | comment | added | Phil Nguyen | Thank you so much, Ariel. Can I explain 0.073 as the average difference between pre- and post-event for treated and control populations, if we held all other variables constant ? | |
| Jun 10, 2021 at 2:39 | comment | added | Ariel | The coefficient on Leniency Law may be treated as you would normally treat your indicator of treatment. This is the ATT. Covariates refer to the variables denoted by $X$. The difference in the two equations is the level at which covariates are added. Adding covariates at the individual level has no effect on the identification of the treatment effect but may reduce standard errors which is desirable in most cases. The notes I linked by Pischke might be useful in understanding this. | |
| Jun 10, 2021 at 2:34 | comment | added | Phil Nguyen | (3) "Adding in covariates helps to explain some of the variation in Y and so reduces the variance in our residuals". Whether covariates here is independent variable. Because at the end of this discussion, you said "The independent covariates do not really matter though unless we are interested in them", so I am not sure what actually covariates stands for here. | |
| Jun 10, 2021 at 2:33 | comment | added | Phil Nguyen | (2) So, the main difference between your two equations are the $X_{igt}$. meaning that adding the firm-level independent variables apart from group-level (country-level) independent variable to reduce std.err? And it seems that , adding firm-level independent variables mean reducing within-group variation? | |
| Jun 10, 2021 at 2:29 | comment | added | Phil Nguyen | Hi @Ariel, thank you for your help, my main focus is explaining the coefficients, (1)can you please help me, for example, explain the meaning of 0.073 in this picture then ? | |
| Jun 8, 2021 at 18:28 | history | edited | Ariel | CC BY-SA 4.0 |
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| Jun 8, 2021 at 18:22 | history | edited | Ariel | CC BY-SA 4.0 |
added 202 characters in body
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| Jun 8, 2021 at 18:16 | history | answered | Ariel | CC BY-SA 4.0 |