Probit and Logit Models
Probit and logit models are among the most popular models. The dependent variable is a binary response, commonly coded as a 0 or 1 variable. The decision/choice is whether or not to have, do, use, or adopt. Examples include whether a consumer makes a purchase or not, and whether an individual participates in the labor market or not.
Probit and logit models: topics covered
Linear regression model, probit, and logit models functional forms and properties
Model coefficients and interpretations
Marginal effects (and odds ratios) and interpretations
Goodness of fit statistics (percent correctly predicted and pseudo R-squared)
Choice between probit and logit
Economic models that lead to use of probit and logit models
Panel data models: topics covered
Panel data characteristics, panel data types
Variation types (overall, within, and between variation)
Panel data models (pooled model, fixed effects model, and random effects model)
Estimator properties (consistency and efficiency)
Estimators (pooled OLS, between, fixed effects, first differences, random effects)
Tests for choosing between models (Breusch-Pagan LM test, Hausman test)
Probit and Logit Models
Probit and logit models are among the most popular models. The dependent variable is a binary response, commonly coded as a 0 or 1 variable. The decision/choice is whether or not to have, do, use, or adopt. Examples include whether a consumer makes a purchase or not, and whether an individual participates in the labor market or not.
Probit and logit models: topics covered
Linear regression model, probit, and logit models functional forms and properties
Model coefficients and interpretations
Marginal effects (and odds ratios) and interpretations
Goodness of fit statistics (percent correctly predicted and pseudo R-squared)
Choice between probit and logit
Economic models that lead to use of probit and logit models
Panel data models: topics covered
Panel data characteristics, panel data types
Variation types (overall, within, and between variation)
Panel data models (pooled model, fixed effects model, and random effects model)
Estimator properties (consistency and efficiency)
Estimators (pooled OLS, between, fixed effects, first differences, random effects)
Tests for choosing between models (Breusch-Pagan LM test, Hausman test)
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