Probit and logit models typically require a normalization on the error variance for model identification. This paper … shows that in the context of sample mean probability decompositions, error variance normalizations preclude estimation of …

generates discrete choice outcomes. Pregibit nests logit, approximately nests probit, loglog, cloglog and gosset models, and … yields a linear probability model that is solidly founded on the discrete choice framework that underlies logit and probit. …The pregibit discrete choice model is built on a distribution that allows symmetry or asymmetry and thick tails, thin …

models should be utilized to solve these problems. Nonlinear models include logit and probit models. Therefore, logit and … probit models are discussed in detail in this chapter of the book. Macroeconomic factors affecting the return on the BIST-100 … Index (Gold price per ounce, TL Deposit Interest, Euro-Dollar Currency Basket Return) have been investigated using logit and …

-Oaxaca decomposition analysis for wage differentials. The decomposition method is first developed for a single probit model and later …

from credit files taken from six large German universal banks. The paper focuses on (i) binary and ordered probit/logit … Mittelpunkt stehen dabei (i) binäre bzw. geordnete Logit- und Probitmodelle, mit deren Hilfe die Ausfallwahrscheinlichkeit eines …