An Empiricist’s Companion. First ed., Princeton, NJ:Princeton University

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Argomenti del programma: 1. Introduction to the course. Conditional expectations and their features 2. Multiple linear regression analysis: Ordinary Least Squares (OLS) estimator 3. Finite Sample properties of OLS estimator 4. Finite Sample inference 5. OLS asymptotics and large sample inference 6. Specification tests and model selection 7. Incorporating non-linearities in multiple linear regression models

Argomenti del programma: Part 1) Introduction: scope and toolbox of microeconometrics Part 2) A framework to define causality Part 3) A recap: the Population Regression Function 3.1 What is the Population Regression Function (PRF) and why are we interested in it 3.2 Sample Regression Function (SRF) and estimation of the PRF 3.2.1 Methods of Moments 3.2.2 Ordinary Least Squares 3.2.3 Maximum Likelihood 3.3 Properties of estimators 3.3.1…