Am 28.03.2019 um 02:56 schrieb Allin Cottrell:
There's a colleague in my department who uses gretl for all his empirical work, and does a lot of logistic regressions. He's a political economy guy and in many cases the dependent variable is the percentage vote in some legislative body for some bill or other.

We have logistic regression in gretl but it hasn't had much attention in a long time. At my colleague's prompting I've recently enabled the --robust and --cluster options for "logistic". But in addition he also wants to use logistic regression in a panel context. We have fixed effects (binary) logit already -- any thoughts on what it would take to extend that to cover fixed effects logistic?

After looking at the help for 'logistic', spontaneously I'd say it's much simpler than felogit. The LHS of the regression is some transformation of a variable, but the same is true for example for a simple log-transform. So I don't see why in terms of estimation a standard FE specification with a transformed regressand wouldn't work -- of course always sticking to the (sometimes overlooked) assumption that the regressors are strictly exogenous, so in particular no lagged endogenous terms and so on.

(Note that for nonlinear transformations there's also a literature on getting predicted values properly, because the expected transformed value will not be the same as the transformed expectation. This could also apply here AFAICS, but this would already affect the 'logistic' command as-is, without panel fixed effects.)

My 2ct