Sumários
Lecture 4
12 Outubro 2020, 10:30 • Paulo Parente
Multiple Regression Analysis: Inference.
Part 2, Wooldridge (2013), Chapter 6 (section 6.4)
∙ Prediction for the conditional mean of y in the multiple regression model
∙ Prediction for y in the multiple regression model
∙ Predicting y in a log model
Multiple Regression Analysis: Asymptotic Properties. Wooldridge (2013), Chapter 5
∙ Consistency - Introduction
∙ Consistency of the OLS estimator
∙ Inconsistency when we ignore one regressor.
∙ Asymptotic Normality-Introduction
∙ Asymptotic Normality of the OLS estimator
∙ Lagrange Multiplier statistic
Doubts clearing session.
Lecture 3
28 Setembro 2020, 10:30 • Paulo Parente
Multiple Regression Analysis: Inference.
Part 1, Wooldridge (2013), Chapter 4
∙ Introduction
∙ Assumptions of the Classical Linear Model
∙ The t Test
∙ Hypothesis testing - one-sided alternatives
∙ Hypothesis testing - two-sided alternatives
∙ Confidence Intervals
∙ Testing a Linear Combination
∙ Multiple Linear Restrictions
∙ Testing Exclusion Restrictions
∙ The F statistic
∙ Overall Significance
Doubts clearing session.
Lecture 2
22 Setembro 2020, 08:00 • Nuno Sobreira
8 (Wooldridge, Chapter 2), 1, 4 e C1 (Wooldridge, Chapter 3)
Lecture 2
21 Setembro 2020, 10:30 • Paulo Parente
Multiple Regression Analysis: Estimation. Wooldridge (2013), Chapter 3
∙ The R-squared
∙ Unbiasedness of the OLS estimator
∙ Too Many or Too Few Variables
∙ Variance of the OLS Estimators
∙ The Gauss-Markov Theorem
∙ Variance of the OLS Estimators - Misspecified Models
∙ Estimating the Error Variance
∙ Incorporating Non-linearities
Doubts clearing session.