Part 1: Introduction
1 Problems of Measuring Effects and Causes  
2 Multivariate Regression  
Part 2: Matrix Algebra
3 Matrix Algebra - Vectors and Matrices, Addition, Multiplication  
4 Matrix Algebra - Determinants and Inverses  
5 Matrix Algebra - Inverses and Quadratics  
6 Matrix Algebra - Differentiation and Optimization  
Part 3: Regression Model

Model and Interpretation 
Projections and Partial Regression Plots

Properties: Unbiasedness and Bias

8 Properties of Estimates  
9 Variance and Confidence Intervals  
10 Prediction  
11 Hypothesis Tests and Model Selection  
12 Maximum Likelihood Estimation  
13 Qualitative Dependent Variables: Probit and Logit  
    Mid-term exam
14 Sources of Inefficiency: Heteroskedasticity and Weighting  
15 Bootstrapping and Quantile Regression  
Part 4: Quasi-Experiments
16 Panel Models  
17 Panel Models (cont.)  
18 Instrumental Variables  
19 Instrumental Variables (cont.)  
20 Research Design  

Course Info

Learning Resource Types

assignment Problem Sets
grading Exams
notes Lecture Notes