Econometrics

The aim of the course is to provide students with the basic principles of econometrics. All the aspects of econometric models treated during the course will be investigated through modern empirical applications in order to motivate students and respond to important problems coming from the real world with appropriate and specific numerical answers. Specifically, the first aim of the course is to extend the simple linear regression model, already thought in the course of Statistics, in different directions: extend the number of regressors, consider potential departures from the standard assumptions of the model, develop a theoretical framework for making inference on the parameters of the model, both for small sample and asymptotically. The second specific aim, concerns the introduction to non-linear regression models like models for binary dependent variables or non-linear specifications among the regressors.

At the end of the course students will have received the introductory notions of econometrics. In particular, they will be able to specify a linear regression model, estimate the coefficients and perform tests of hypothesis on them. Moreover, students will be able to read and critically comment on the results of econometric analyses based on linear regression models or on regression models presenting some nonlinearities, like logit and probit ones. These expected outcomes should help students in understanding empirical analysis introduced in different courses, as well as provide them with quantitative tools for the development of the final thesis.