ADVANCED ECONOMETRICS | Università degli studi di Bergamo

ADVANCED ECONOMETRICS

Attività formativa monodisciplinare
Codice dell'attività formativa: 
110015-ENG

Scheda dell'insegnamento

Per studenti immatricolati al 1° anno a.a.: 
2020/2021
Insegnamento (nome in italiano): 
ADVANCED ECONOMETRICS
Insegnamento (nome in inglese): 
Advanced Econometrics
Tipo di attività formativa: 
Attività formativa Caratterizzante
Tipo di insegnamento: 
Obbligatoria
Settore disciplinare: 
ECONOMETRIA (SECS-P/05)
Anno di corso: 
1
Anno accademico di offerta: 
2020/2021
Crediti: 
6
Responsabile della didattica: 
Mutuazioni
  • Corso di studi in INTERNATIONAL MANAGEMENT, ENTREPRENEURSHIP AND FINANCE - Percorso formativo in MANAGEMENT AND FINANCE FOR INTERNATIONAL MARKETS

Altre informazioni sull'insegnamento

Modalità di erogazione: 
Didattica Convenzionale
Lingua: 
Inglese
Ciclo: 
Secondo Semestre
Obbligo di frequenza: 
No
Ore di attività frontale: 
48
Ore di studio individuale: 
102
Ambito: 
Economico
Prerequisites

Very good knowledge of Statistics (Probability and Inferential), Linear Algebra, Introductory Econometrics.

Educational goals

To provide students with wide knowledge of econometric techniques useful to modelling micro (MICROECONOMETRICS) and financial (FINANCIAL ECONOMETRICS) variables. Students will be very well equipped to undertake research careers at national (for instance Bank of Italy) and international (for instance European Central Bank, Bank of England, International Monetary Fund, ..) institutions, financial industry and academia.

Course content

MICROECONOMETRICS - Review of the asymptotic distribution of OLS; Regularity conditions and review of testing procedures; Instrumental Variables; 2SLS and introduction to the weak instrument problem; GMM estimation; Binary choice models; Multinomial/ordered response models; Censoring models; Introduction to non parametric techniques; Linear Static Fixed-Effects Models; Linear Static Random-Effects Models; Linear Dynamic Models; Non-linear Panel Data Models; Difference-in-differences models; Regression Discontinuity Design.

Teaching methods

Lectures and practical classes using the econometric packages Stata.

Assessment and Evaluation

The assessment consists of
a) A take-home COURSEWORK to be assigned by the lecturer

b) FINAL WRITTEN EXAM (short-answer, proofs, and numerical questions) based on the material in the syllabus and in the coursework.

Students must pass both coursework and final written exam.

Further information

If lectures and classes will be delivered blended or remotely in full, the syllabus and the assessment process will be modified accordingly.