For my research I'm analysing a panel data set of monthly actual share repurchases.
The goal is to compute CARs for both monthly stock and bond returns around these repurchases.
Estimation window = (-24 months, -3months)
Event windows: (-3mo,+3mo), (-2mo,+2mo), (-1mo,+1mo)
An example of the data I'm working with:
In Month 5 I see two things happening:
The goal is to compute CARs for both monthly stock and bond returns around these repurchases.
Estimation window = (-24 months, -3months)
Event windows: (-3mo,+3mo), (-2mo,+2mo), (-1mo,+1mo)
An example of the data I'm working with:
Date | Company | Event |
Month 1 | A | 1 |
Month 2 | A | 0 |
Month 3 | A | 0 |
Month 4 | A | 0 |
Month 5 | A | 1 |
Month 6 | A | 1 |
In Month 5 I see two things happening:
- The estimation window for the event in Month 5 will include the event in Month 1.
- The event windows for the event in Month 5 will include the event in Month 6
- Should I just eliminate observations that have overlapping event/estimation windows? (How would I go about coding this?)
- Should I continue my analysis on the full sample and then another with those observations eliminated to see if results are significantly different?
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