32626 - ECONOMETRICS

Scheda insegnamento

  • Docente Sergio Pastorello

  • Crediti formativi 6

  • SSD SECS-P/01

  • Modalità di erogazione In presenza (Convenzionale)

  • Lingua di insegnamento Inglese

  • Orario delle lezioni dal 06/11/2017 al 07/12/2017

Anno Accademico 2017/2018

Conoscenze e abilità da conseguire

Al termine del corso, lo studente possiede una rigorosa preparazione in economia avanzata ed econometria, che gli permette essenzialmente di perseguire una carriera nella ricerca economica a livello universitario o in centri di ricerca pubblici o privati.

Programma/Contenuti

  1. Introduction and Overview of Statistical Learning
  2. Linear Regression as a Prediction Tool
  3. Binary and Multinomial Classification: Logistic Regression, Linear Discriminant Analysis and K-Nearest Neighbors
  4. Resampling Methods: Cross-Validation and the Boostrap
  5. Linear Model Selection and Regularization: Ridge Regression, the LASSO and Principal Components
  6. Moving Beyond Linearity: Regression Splines, Smoothing Splines and Genelar Additive Models
  7. Tree-based Methods: CART, Bagging, Boosting and Random Forests
  8. Support Vector Machines and Neural Networks
  9. Unsupervised Learning: Hierarchical and K-Means Clustering

Testi/Bibliografia

James, Witten, Hastie and Tibshirani, An Introduction to Statistical Learning, Springer 2014.

Hastie, Tibshirani and Friedman, The elements of Statistical Learning, Springer 2015.

Metodi didattici

For each topic we will first introduce the relevant theory, and then move as soon as possible to its empirical application in the R language. Special emphasis will be placed on the economic interpretation of the results.

Modalità di verifica dell'apprendimento

The final exam is written. It lasts one hour and it is composed of two distinct sections.
The first one is mainly theoretical, and it contains 5 multiple choice questions. The second one is mainly empirical, and it contains 11 questions whose answers shoud be computed using Stata and knowledge of the empirical analysis discussed during classes. Whatever the section, each correct answer yields two points; no penalty is applied to wrong answers. The final mark is the total number of point obtained in the two sections.
During the exam it is forbidden to consult notes, slides, books, pocket calculators and any other electronic devices. The purpose of the exam is to ascertain that students acquired the knowledge required to correctly specify, estimate and test the econometric models discussed during the lectures and possess the ability to properly interpret the results provided by these procedures.

Strumenti a supporto della didattica

We will discuss several empirical analysis and replicate the results of a few papers using the statistical software R.

Orario di ricevimento

Consulta il sito web di Sergio Pastorello