Course Description
The theoretical properties of maximum likelihood estimators and their use in overcoming shortcomings of the classical linear model. Computer algorithms are developed and used to compute maximum-likelihood estimators for logit, probit, tobit, sample-selectivity, and failure time models.
Athena Title
ECONOMETRICS II
Prerequisite
ECON 8080
Semester Course Offered
Offered every year.
Grading System
A - F (Traditional)
Course Objectives
The course will cover a number of important areas related to the theory and estimation of maximum likelihood models: small-sample and asymptotic properties, computer algorithms, qualitative and limited dependent variables, duration analysis, and non-parametric estimation. Students will use TSP for software.
Topical Outline
Small and Large Sample Properties of Ordinary Least Squares and Generalized Method of Moments Properties of Maximum Likelihood Estimators and Maximum Likelihood Methods Algorithms Transformations to Normality and Duration Models Qualitative and Limited Dependent Variables Semiparametric Models
Syllabus