MICROECONOMETRICS

This is a core course in the PhD 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 microeconometrics 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 course

- 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.

Students will be asked to hand in homeworks and one final take home exam.

lectures and practical sessions

written

This subject deals with topics related to the macro-area "Human capital, health, education" and contributes to the achievement of one or more goals of U. N. Agenda for Sustainable Development