Hello Statalist,

I'm currently analyzing cross-section data of individual loans originated by 2 banks in 2017-2018 years in the country. (each individual loan appear once only). My goal is to estimate the effect of a relief lending program to loan outcomes (overdue/default).
Dependent variable Outcome: binary 1 if overdue/default within 2 years from the origination date, and 0 otherwise
I would like to add bank fixed effects and time fixed effects and zip-code fixed effects (note that the time variable is the quarter when the loan is issued so it repeated within bank and zip code). Because my data is not a time series there for function xtset is not applicable. Please help to advise me:
1. Is there any way to add fixed effects into a logit/probit model when xtset cannot be used? I tried:
Code:
xtlogit outcome i.relief loan_control borrower_control i.bank i.zip i.date, vce(cluster bank)
where relief is dummy variable indicates whether the loan is qualified for the relief lending program or not. But because there are more than 900 zipcodes in my data, so Stata showed errors of matsize too small.
I also tried:
Code:
egen zip_date = group(zip date)
areg outcome i.relief loan_control borrower_control, absorb(gse zip_date)
however absord does not allow me to add 2 variables in.
2. One of the 2 banks in my sample issues an overwhelming numbers of loans compared to the other. I wonder if I need to do anything with this unbalance?
Thank you in advance.