I'm looking at the effect of fires on visits to national parks and national forests. My dataset consists of ~500 geographical units over 10 years, and I'm using an FE Poisson model with year fixed effects too. Different units in the dataset have fires in different years, so I have the option of using either pre fire periods from places that eventually have fires as my control units or that + places that never have fires as my control units. I'm leaning towards the former because it seems plausible that places that do and don't have fires are different in ways I don't understand and can't control for; a cursory look at the data confirms that that is indeed the case.

The estimates are quite different when I do and don't include the places that never have fires as controls. I'm trying to understand why/how places that never have fires affect the results at all given that I have unit and time fixed effects. My understanding is that these fixed effects mean that the result is computed by comparing the change in visits because of fire within a given unit to the change in visits because of fire in all the other units. How then would the visit levels from places that don't have fires even matter?

Thank you!