TOPIC 2: The Classical Linear Regression Model
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Model specification. Assumptions. Mechanics and interpretation of Ordinary Least Squares. Properties of estimators. Goodness-of-fit. Hypotheses testing. Confidence intervals. Prediction. Dummy variables. Specification and data problems (omitted variable bias; inclusion of irrelevant variables; proxy variables; multicollinearity). |
