Hi! I am writing to ask whether an event studies analysis can only happen with a linear regression model. I am trying to look at the effect of fire occurence on visits to National Forests. My Y variable is thus a count variable, and I have panel data (for any given site, I have data for 20 years). Since fires occur at different times in different places, I was planning to conduct an event studies analysis to answer my question. I was toying with two ideas:
-- using xtreg, fe on Stata to regress log(visits) on X. I know this is not ideal since Y is a count variable, but this is my understanding of how event studies analyses are usually done.
-- Since it is count data, I was considering doing a negative binomial regression with fixed effects. On Stata this would mean doing nbreg with dummies for all the site IDs included. My understanding is this is better than using xtnbreg, fe. I would then be able to interpret the coefficient to say that a 1 unit increase in X leads to a (beta* 100)% change in Y when beta is small (correct)?
My question is:
- I am leaning towards the second option because I know it's usually better suited for count data. Would the results from the second be considered as an event studies analysis and/or a generalized difference in difference, or does it have to be a standard OLS regression to be considered an event studies analysis?
- Which model seems better given this information?
Thank you so much! I appreciate it.
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