Should I include year effects in my logistic regression?

#1
I made the following logistic regression model for my master's thesis.
FAIL= LATE + SIZE + AGE + EQUITY + PROF + SOLV + LIQ + IND.
Where I take a look if late filing of financial statements (independent variable) is an indicator of failure of small companies (dependent variable). FAIL is a dummy variable that is equal to 1 when a company failed during one of the researched years. I use data covering 3 years (2017, 2018 en 2019). Should I include a dummy variable YEAR, to account for year effects, or not. I have searched online but I don't understand what it exactly means and that is why I don't know if it is necessary to include it in this regression model. I hope you guys can help me.
Thank you in advance!
 

hlsmith

Less is more. Stay pure. Stay poor.
#2
If you don't know if you may need it - you either need to do more research or you don't need it. A simple thing you could do, is run the model for each year and see if there is much difference between the model estimates. If differences are trivial, then you are likely fine not including it. It's utility is if there is a change across years that you want to know about or an exogenous shock - recession, pandemic, something to make a year different form others.