Topic 1: Random Variables and Vectors (Greene, Chapter 3)

Probability; Random Variables; Bivariate Distributions; Bivariate Distributions; Regression; Multivariate Distributions

Topic 2: Statistical Inference (Greene, Chapter 4)

Sample statistics; Large Sample Properties; Maximum Likelihood Estimation; Method of Moments Estimation; Linear Hypothesis Tests: Likelihood Ratio, Lagrange Multiplier, Wald Test; Non-Linear Hypothesis Tests; Moderate-Sample Tests

Topic 3: Classical Regression (Greene, Chapter 6.1-6.4)

Assumptions of the Regression Framework; the Gauss-Markov Theorem and Related Results

Topic 4: Asymptotic Results of the Classical Regression Framework (Greene, Chapter 9.1-9.3)

Asymptotic Assumptions; Asymptotic Distribution of the estimate of ß; consistency of s²; Consistency of the Estimated Variance of ß; Hypothesis Testing; Maximum Likelihood Estimation of ß; More Hypothesis Testing

Topic 5: Small-Sample Results of the Classical Regression Framework (Greene, Chapter 6.5-6.6)

An Additional Assumption; Results with Normal Errors; Small-Sample Hypothesis Tests; Goodness of Fit

Topic 6: Specification of the Regression Equation (Greene, Chapter 8)

Intrinsic Linearity; Deviations from Linearity: Dummy Variables, Interaction Effects, Piecewise Linearity, Structural Breaks, Polynomial Terms; Deciding on a Specification; Omission of Relevant Variables; Inclusion of Irrelevant Variables

Topic 7: Data Problems (Greene, Chapters 6.7, 6.8, 9.5)

Multicollinearity; Randomly Missing Variables; Measurement Error; Hausman Tests

Topic 8: Generalized Least Squares (Greene, Ch. 11)

The GLS Framework; OLS with General Errors; Generalized Least Squares; Maximum Likeliood Estimation; Hypothesis Testing; The Generalized Method of Moments

Topic 9: Estimating the Error Covariance Matrix (Greene, Chapters 12-14)

Heteroschedasticity; Autocorrelation; Longitudinal Data; The Sandwich Estimator

Topic 10: Systems of Simultaneous Equations (Greene, Chapters 15-16)

Identification; Single-Equation Estimation: Two-Stage Least Squares, Indirect Least Squares, Limited-Information Maximum Likelihood; System-Wide Estimation: Three-Stage Least Squares, Full-Information Maximum Likeliood; Specification Tests

Topic 11: Time Series Data (Greene, Chapters 17-18)

Distributed Lags; Autoregression; Moving Averages; ARMA Processes; Estimating Arma Processes; Vector Autoregression; Stationarity, Time Trends, and Unit Roots; Cointegration

Topic 12: Limited Dependent Variables (Greene, Chapters 19-20)

The Problem with OLS; The Logit Model; The Probit Model; Truncated Dependent Variables; Censored Dependent Variables; Sample Selectivity