Microeconometrics
Code
2165
Academic unit
null
Department
null
Credits
7
Teacher in charge
Luís Campos e Cunha
Teaching language
English
Objectives
This class will cover a range of advanced econometric techniques frequently employed in the analysis of micro data (at the household, individual level). The class combine theory and empirical applications and the lectures will include examples and discussions of empirical papers that employ the diferent techniques.
Prerequisites
N/A
Subject matter
1. Introduction: brief review of OLS
2. Beyond OLS: Generalized Least Squares (GLS),Instrumental Variables and Quantile Regression.
3. Maximum Likelihood Estimation
4. Discrete choice models: Linear probability model. Latent variable models: the Probit and the Logit. Interpretation. Marginal E!ects. Multinomial response models. Ordered response models.
5. Corner Solutions, Censored Regression and Sample Selection Models. The Tobit. Truncated regression. Heckman´s model of selection.
6. Panel Data Models. Between and within variation.
7. Estimating Average Treatment E!ects. Experiments and Quasi-experiments. Diferences in Differences, Propensity Score Matching and Regression Discontinuity Design.
8. Bootstrap: Parametric and Non-parametric Kernel density estimates.
Bibliography
Cameron, A. Collin and Pravin K. Triverdi (2005) Microeconometrics: Methods and Applications, Cambridge University Press.
Jeffrey M. Wooldridge (2002), Econometric Analysis of Cross Section and Panel Data, MIT Press, Cambridge, MA.
Manuel Arellano (2004), Panel Data Econometrics, Oxford University Press.
Myoung-Jae Lee (2005), Micro-Econometrics for Policy, Program, and Treatment Effects, Oxford University Press.
Kenneth Train (2003), Discrete Choice Methods with Simulation, Cambridge University Press, Cambridge, MA.
Joshua D. Angrist and Jörn-Steffen Pischke (2008) Mostly Harmless Econometrics: An Empiricist´s Companion, Princeton University Press.
Cameron, A. Collin and Pravin K. Triverdi (2009) Microeconometrics using Stata, Stata Stata Press.
Teaching method
Lectures will cover the core theoretical materials and discussions of empirical papers that employ the diferent techniques. Background reading is expected.
Evaluation method
Final exam (80%) and take-home (20%).
Research note (35%), final exam (50%) and take-home (15%).