Planeamento
Aulas
Introduction
1.
Introduction
1.1.
Econometric Methodology
1.2.
The Structure of Economic Data
1.3.
Dependent Variables and Econometric Models
1.4.
Types of Explanatory Variables
2. Linear Regression Analysis with Cross-Sectional Data
2.1. Model Specification
2.2. Estimation: Ordinary Least Squares
Introduction to Stata
Introduction
to Stata
Illustration 1 (questions 1-6)
Linear Regression Analysis with Cross-Sectional Data
2.2. Estimation: Ordinary Least Squares (cont.)
2.3. Partial Effects
Practical Exercises
Illustration 1 (cont.)
Inference and Model Evaluation
2.4. Inference
2.5. Model Evaluation
Illustration 1
(questions 7-9)
Practical Exercises
Illustration 2
Practical Exercises
Illustration 3
Practical Exercises
Illustration 3 (cont.)
Econometric Models with Endogenous Explanatory Variables
3.
Econometric Models with Endogenous Explanatory Variables
3.1.
Endogeneity
3.1.1.
Definition and Consequences
3.1.2.
Motivation: Omitted Variables, Measurement Errors, Simultaneous Equations
3.1.3.
Solutions: Instrumental Variables, Panel Data
3.2.
Instrumental Variable Estimation
3.2.1.
Two-stage Least Squares (2SLS)
3.2.2.
Generalized Method of Moments (GMM)
3.3.
Specification Tests
3.3.1. Test
for the Exogeneity of an Explanatory Variable
3.3.2. Test
for the Exogeneity of the Instrumental Variables
3.3.3.
Tests for Correlation between Instrumental Variables and Explanatory Variables
Practical Exercises
Illustration 4
Panel Data Models
4. Static
and Dynamic Panel Data Models
4.1. Panel
Data
4.2.
Alternative Estimators
4.3.
Inference and Model Evaluation
Practical Exercises
Illustration 5
Practical Exercises
Illustration 6
Dynamic Panel Data Models
4.4. Dynamic Panel Data Models
Illustration 7To be defined
To be defined
Nonlinear Regression Models
5.
Nonlinear Regression Models
Models for Binary Choices
5.2.
Limited Dependent Variable Models
5.2.1.
Models for Binary Choices
Practical Exercises
Illustration 8
Models for Ordered Choices
5.2.2.
Models for Ordered Choices
Illustration
9
Models for Multinomial Choices
5.2.3.
Models for Multinomial Choices