Upon successful completion of the course the student will be able to:

• understand the formal and practical aspects of important microeconometric methods.
• to apply an analytical method and to recognize its limitations.
• to adopt a model specification and to correctly interpret estimation results.
• to deal with the empirical literature in microeconometrics and to perform formal econometric analyses.
• perform analyses with economic data using Stata and to interpret Stata output.

• Introduction: Goals and structure of the course, learning aims & objectives, doing empirical analysis, process of project development
• Basic regression analysis (OLS): Basic tools for regression analysis, interaction effects
• Instrumental variables (IV): Endogeneity problem; instrumental variables; weak instruments; over identification tests; testing for endogeneity and GMM
• Panel data (A): Panel data structure: fixed and random effects models; Hausman test; Breusch- Pagan test; time dummies; clustering or panel-corrected standard errors
• Panel Data (B): Dynamic panel data models: GMM estimators of linear dynamic panel data models; testing for instrument validity; serial correlation test
• Discrete choice modelling: Binary probity and logit; computing marginal effects; goodness-of-fit; Multinomial choice models; independence of irrelevant alternatives; ordered probit and logit
• Count data models: Poisson model; over-dispersion test; negative binomial model diagnostics and measure of t; zero-inflated models
• Limited dependent variables models: Censored data; Tobit models; marginal effects of Tobit models; sample selection models
• Policy evaluation methods: Difference-In-Differences, Regression Discontinuity Design

Lectures (4 hours per week) and Tutorials (1 hour per week)

The assessment is based on student’s performance in the written final examination (60%), on nine weekly assignments (average score contributes with 20% in final grade) and on two mid-term examinations during the semester (each one contributes with 10% in final grade). Written final exams take place in a computer room where each student must use the Stata software to answer the questions and to prepare a report.

Use of Information and Communication Technologies (ICTs) (e.g. power point) in teaching. Use the statistical software Stata. The lectures for each chapter are uploaded on the e-class platform in the form of ppt files, which the enrolled students can freely download.