Exponential regression of panel data fractional response models ∗
نویسنده
چکیده
New panel data estimators are proposed for logit and complementary loglog fractional regression models. The standard specifications of these models are transformed into a form of exponential regression with multiplicative individual effects and time-variant heterogeneity, from which six alternative estimators that do not require assumptions on the distribution of the unobservables are developed. Most of the proposed estimators are robust to both time-variant and time-invariant heterogeneity, can be applied to dynamic panel data models and accommodate endogenous explanatory variables without requiring the specification of a reduced form model.
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