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Lecture 10: Logistical Regression II— Multinomial Data

Lecture 10: Logistical Regression II Multinomial DataProf. Sharyn O Halloran Sustainable Development U9611 Econometrics IILogit vs. Probit Review Use with a dichotomous dependent variable Need a link function F(Y) going from the original Y to continuous Y Probit: F(Y) = -1(Y) Logit: F(Y) = log[Y/(1-Y)] Do the Regression and transform the findings back from Y to Y, interpreted as a probability Unlike linear Regression , the impact of an independent variable X depends on its value Andthe values of all other independent variablesClassical vs. Logistic Regression data Structure: continuous vs. discrete Logistic/Probit Regression is used when the dependent variable is binary or dichotomous.

Classical vs. Logistic Regression Data Structure: continuous vs. discrete Logistic/Probit regression is used when the dependent variable is binary or dichotomous. Different assumptions between traditional regression and logistic regression

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