outline

Course Outline

I. Material Covered Before First Exam

Types of Data, Statistics Review: Random Variables, Marginal, Joint and Conditional Densities
- Stock and Watson, Chapters 1 and 2
- Downs Syndrome Example
- Stock and Watson, Exercise 2.3 Solved

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
- Stock and Watson,2.5, 3.1
- Powerpoint Show: Sampling Distributions
- Powerpoint Show: Law of Large Numbers and Central Limit Theorem
- Powerpoint Show: Unbiasedness and Consistency

Introduction to Econometric Methodology. The Simple Linear Regression Model. Conditional Mean Function. Estimation via Least Squares. The OLS estimator
- Stock and Watson, 4.1-4.3
- Powerpoint Show: Regression Introduction

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
- Stock and Watson, 3.2-3.3, 4.4-4.6
- Powerpoint Show: Confidence Intervals
- Confidence Interval Applet from The American Statistician

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
- Stock and Watson 5.1-5.6

Interpretation of Regression Coefficients Under Common Transformations
- 6.1-6.2

Joint Hypothesis Testing. Restricted and Unrestricted Regressions.
- Stock and Watson, 5.7-5.10

Dummy Variables and Interactions.

Stock and Watson, 6.3

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
- Stock and Watson 9.1-9.3

Mean-Independence Violations: Omitted Variables, Measurement Error (in X), Simultaneous Equation Models, Endogeneity
- Lecture Notes

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