are from a logit or probit model. I describe a relatively simple method of performing a decomposition that uses estimates … from a logit or probit model. Expanding on the original application of the technique in Fairlie (1999), I provide a more …

are from a logit or probit model. I describe a relatively simple method of performing a decomposition that uses estimates … from a logit or probit model. Expanding on the original application of the technique in Fairlie (1999), I provide a more …

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. …

parameter. We contrast this with a model that directly incorporates a logit discrete-choice approach into a AGE framework. On … logit approach is preferable. …

turns out to include a logit formulation as a special case. In general, it has a rich set of implications both for exogenous …

Logit model and the signal approach are two analysis methods being commonly used to forecast and explain currency … crises. Logit model is successful to determine explaining variables of crisis and to calculate the probability of crisis in … model for currency crisis, using common set of findings of logit model and the signal approach to explain Turkish experience …

way. Our results can be applied to the most common limited dependent variable models such as probit, logit and tobit …

) transactions and demon-strates the implementation of a new rating method based on a logistic regression (logit func-tion), a rating …