Course Outline
I. Material Covered Before First Exam
- Types of Data, Statistics Review: Random Variables, Marginal, Joint and Conditional Densities
- Means, Variances and Other Moments, Properties of Expectation Operator. Expectations from Marginal and Joint Distributions.
- Stock and Watson, Chapter 2.2 and 2.3
- Conditional Means, Variance, Standard Deviation, Correlation:
- Stock and Watson, Chapter 2.3
- Special Distributions: A Brief Introduction to Distribution Theory
- Stock and Watson, Chapter 2.4
- Estimators and Criteria for Estimators: Sampling Distributions, Asymptotic Distributions, Unbiasedness, Consistency, Law of Large Numbers, Central Limit Theorem, CDF of Normal Random Variable
- Introduction to Econometric Methodology. The Simple Linear Regression Model. Conditional Mean Function. Estimation via Least Squares. The OLS estimator
- Fitted Values, estimated residuals. Estimation of Error Variance. Properties of OLS estimator. R-squared.
- Stock and Watson, 4-1-4.3, 4.8.
II. Material Covered Before Second Exam
-
Scalar Hypothesis Testing with Known Variance, Confidence Intervals and their Interpretation
- Scalar Hypothesis Testing with Unknown Variance. t-statistics, p-values, One-sided testing
- Stock and Watson, 3.2-3.3, 4.4-4.6
- Multiple Regression Analysis and Omitted Variables
- Interpretation of Regression Coefficients Under Common Transformations
- Joint Hypothesis Testing. Restricted and Unrestricted Regressions.
- Stock and Watson, 5.7-5.10
- Dummy Variables and Interactions.
III. Material Covered Before Final Exam
-
Assessing Regression Studies: Threats to Internal and External Validity
- Stock and Watson, Chapter 7
- Panel Data and Fixed Effects
- Stock and Watson, Chapter 8
- Binary Choice Models: The Linear Probability Model, Probit and Logit. Estimation via Maximum Likelihood
- Mean-Independence Violations: Omitted Variables, Measurement Error (in X), Simultaneous Equation Models, Endogeneity
- Instrumental Variables Estimation and Two Stage Least Squares .
- Stock and Watson, Chapter 10
- An Introduction to Time Series
- Stock and Watson, Chapter 12.1-12.6