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About Lecture 11: Alternatives To OLS With Limited Dependent Variables, Part 2
This document discusses alternatives to ordinary least squares (OLS) regression for modeling limited dependent variables, including Poisson, negative binomial, tobit, and sample selection models. It compares presenting results as partial effects at the average (PEA) versus average partial effects (APE). PEA and APE are equivalent for linear models but may differ for models with interaction or squared terms. The document provides an example of interpreting coefficients in a Poisson model and discusses incorporating exposure variables. It also covers testing model fit and using negative binomial models when the Poisson assumption is violated. Finally, it defines tobit models for censored outcomes.
Detailed Information
Author: | ['Ballentos, Paul Jeffrey'] |
---|---|
Publication Year: | 2019 |
Pages: | 42 |
Language: | English |
Format: | |
Price: | FREE |
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