Dear members,

Currently I am struggling with doing logit regression using panel data. Am using a panel of banks for 10 years.
I am regressing FSIIndex (1 if index is higher for all banks including foreign banks and 0 if index is higher for banks excluding foreign banks) Loans Loansgrowth non-performingloans GDP Interestrate.
FSI is financial stability index.
My questions are:
1. Do I use the binary outcomes logit or the ordinal outcomes logit?
  • If I carry out a fixed effect logit I get the following

xtlogit FSIIndex LnLOANS Loansgrowthall Loansgrowthforeign LD LnNPLs GDP r, fe
note: multiple positive outcomes within groups encountered.
  • . mfx
default predict() is unsuitable for marginal-effect calculation
  • When I do a random effect I get the following:

xtlogit FSIIndex LnLOANS Loansgrowthall Loansgrowthforeign LD LnNPLs GDP r, noconstant revce(robust)

Calculating robust standard errors:
conformability error

When I do an ordinal outcome logit

xtologit FSIIndex LnLOANS Loansgrowthall LnNPLs LD GDP r, vce(robust)

. mfx

Marginal effects after are exactly same as coefficients

2. How do I get the marginal effects after that?

3. Which logistic regression is more correct and what is the difference of each regarding the marginal effect postestimation