MICROECONOMETRICS

This is a core course in the Ph.D. program in Economics and it is the natural follow-up of the Econometric Theory and Time Series Analysis modules.

This course is aimed at providing students with the methodological and quantitative skills required to undertake independent applied research using modern microeconometric methods. The course design balances theory and empirical applications. Students will be expected to gain a good command of advanced microeconometric techniques and will be asked to work with the STATA software.

a graduate-level course in Econometric Theory

- Endogeneity in cross-sectional models: Instrumental Variables and GMM
- Model specification: non-linear transformations in variables, selecting regressors, testing model specification, multicollinearity, aggregate regressors, bootstrap
- Panel data estimations, basics: pooled OLS, First Differences, Fixed Effects, Random Effects, Mundlak approach
- Endogeneity in panel data models.
- Dynamic panel data models
- Binary choice models: latent variables and Random Utility Theory; Linear probability models; Probit and Logit
- Truncated and Censored Data: Tobit I and II
- Binary choice models with endogenous regressors
- Binary choice models with panel data
- Multinomial conditional and mixed logit

Cameron and Trivedi (2005) “Microeconometrics: Methods and Applications” Cambridge Univ Press, Cambridge, UK.

Wooldridge (2010) “Econometric Analysis of Cross Section and Panel Data”, 2nd edition, MIT Press, USA.

Greene (2008) "Econometric Analysis", 6th edition, Pearson, USA.

Grading will be based on two pieces of homework. The homework will contain theoretical questions and empirical exercises to be solved in STATA. Additional details on the assessment will be provided during the first lecture, as well as the indicative submission deadlines for the homework

lectures and practical sessions

written