Econometrics I

Teaching assistanship. Revisiting key concepts from the lectures, using real life examples for thorough understanding, and walking through empirical exercises.

CORE TEXT: Jeffrey M. Wooldridge (2012): Introductory Econometrics. A Modern Approach. CENGAGE Learning Custom Publishing, 5th Edition

Seminar software: R/R Studio

Syllabus

• Course information
• Statistics review
• Steps Empirical Economic Analysis
• Structure of Economic Data

• Causality and Ceteris Paribus Notion

• Simple regression analysis
• Multiple Regression
• Derivation of the Ordinary Least Squares (OLS) Estimates
• Properties of OLS
• Units of Measurement and Functional Form
• Expected Values and Variances of the OLS Estimators
• Interpretation of OLS

• Efficiency of OLS: The Gauss-Markov Theorem

• Sampling Distribution of the OLS Estimators
• Testing Hypotheses: The t Test
• Confidence Intervals
• Testing Multiple Linear Restrictions: The F Test
• Reporting Regression Results
• Consistency
• Asymptotic Normality and Large Sample Inference

• Asymptotic Efficiency of OLS

• Effects of Data Scaling on OLS Statistics
• More on Functional Form
• Goodness-of-Fit and Selection of Regressors
• Prediction and Residual Analysis
• A Single Dummy Independent Variable
• Using Dummy Variables for Multiple Categories
• Interactions Involving Dummy Variables
• A Binary Dependent Variable: The Linear Probability Model

• Interpreting Regression Results with Discrete Dependent Variables

• Consequences of Heteroskedasticity for OLS
• Heteroskedasticity-Robust Inference after OLS Estimation
• Testing for Heteroskedasticity
• Weighted Least Squares (WLS) Estimation
• Functional Form Misspecification
• Using Proxy Variables for Unobserved Explanatory Variables
• Models with Random Slopes
• Properties of OLS under Measurement Error
• Missing Data, Nonrandom Samples, and Outlying Observations
• Least Absolute Deviations (LAD) Estimation