ECONOMETRIC THEORY

The purpose of the course is to provide the necessary tools for a thorough understanding of the theory of econometrics. The course goals are 1) to be able to perform estimation and testing in linear regression models, and to be comfortable with asymptotic theory for linear models, 2) to be able to implement basic cross-section and time-series methods as needed for an advanced quantitative analyses.

An econometric class similar to Applied Statistics and Econometrics + Matrix Algebra. Roughly corresponding to Appendices A-D of the Greene's book (see below)

Knowledge and understanding: The course will focus on the main econometric tools to perform quantitative analyses of economic data. This course provides analytical resources that will enable students to autonomously investigate the empirical validity of economic theory and to predict economic data. Applying knowledge and understanding: The students will be able to: • Carry out univariate and multivariate linear regression analyses • Determine the possible presence of causal relationships between economic variables • Adopt the most common estimation methods: linear projections, maximum likelihood, method of moments. Making judgements: We expect students to be able to set up and estimate econometric models and to interpret the outcomes in a sensible way. Students are asked to use the software MATLAB to gain insights on the econometric methodologies and their implementation. Learning skills: This course will contribute to empower learners giving them the theoretical, econometric and programming tools to autonomously study economic and financial data and test economic theories.

Some of the topics covered are: statistic foundations, single-equation linear model, and assumptions of the OLS estimator. Asymptotic properties of OLS and ML estimators. Testing (Likelihood-ratio, Wald, Lagrange Multipliers). Heteroskedasticity. Generalized least square estimator. Systems of equations. Measurement Error. Simultaneous equations model. Omitted variables. Instrumental variables estimation. Models for Panel Data. Generalized Method of Moments. Time Series modeling: univariate and multivariate

Greene, William, Econometric Analysis, Prentice Hall

Lectures and practice sections. The practice sessions are designed to cover more deeply the subjects introduced in class. The numerical/statistical software MATLAB will be extensively used in these sessions.

Final written exam : theory questions + exercise in MATLAB

None

yes, in some empirical examples on gender gap.