Course Syllabus

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Il corso si propone di fornire allo studente strumenti avanzati, di natura teorica e applicata, riguardanti i modelli per dati panel, i modelli per variabili dipendenti qualitative, “censurate” o “troncate”, i modelli per dati count e i modelli di durata.

Al termine del corso, lo studente sarà in grado di applicare quanto appreso a casi reali, avendo sviluppato un’adeguata capacità critica per quanto riguarda la scelta degli strumenti e l’interpretazione dei risultati.

· Introduzione, motivazione e definizioni

· Modelli per serie storiche pooled

· Modelli per dati longitudinali

· Dati panel e modelli two-way

· Dati panel e modelli dinamici

· Modelli per variabili dipendenti qualitative: scelte binarie

· Modelli per variabili dipendenti qualitative: scelte multiple

· Modelli per variabili limitate: censura e troncamento

· Modelli per dati count

· Modelli per dati di durata

· Richiami sugli stimatori di base (OLS, GLS, IV)

· Eteroschedasticità cross-sezionale e autocorrelazione

· Effetti fissi (stimatore OLS con variabili dummy, trasformazione within)

· Effetti casuali, non correlati con i regressori (stimatore GLS, trasformazione between)

· Effetti casuali, correlati con i regressori (stimatore IV)

· Modelli panel two-way: effetti fissi e casuali

· Modelli panel dinamici: differenze prime e stimatori IV e GMM

· Modelli per variabili dipendenti qualitative: scelte binarie (Logit e Probit)

· Modelli per variabili dipendenti qualitative: scelte multiple (Multinomial e Conditional Logit, Nested Logit)

· Modelli per variabili limitate: censura e troncamento (Tobit)

· Modelli per dati count (Poisson e Binomiale negativa)

· Modelli di durata

Nessuno. Tuttavia sono date per acquisite le nozioni di base di econometria, microeconomia e macroeconomia.

Lezioni frontali (in aula e in laboratorio informatico).

L’esame finale, unico, consiste in una parte scritta e in una parte orale.

· W. Greene, Econometric Analysis, Prentice Hall International, 4ᵃ edizione, 2002

· G.S. Maddala, Limited-Dependent and Qualitative Variables in Econometrics, Cambridge University Press, 1983

· M. Manera, M. Galeotti, Microeconometria, Metodi e Applicazioni, Carocci, 2005

· J.M. Wooldridge, Econometric Analysis of Cross Sections and Panel Data, The MIT Press, 2002

Secondo semestre.

Italiano.

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This course aims at providing students with advanced instruments, both theoretical and empirical, to estimate models for panel data (static and dynamic), models for qualitative response variables, models for limited dependent (i.e. censored and truncated) variables, models for count data and duration models.

At the end of the course students will be able to apply the techniques illustrated during lectures and classes to real situations, since they have developed adequate critical skills to choose the appropriate tools of investigation and to interpret the empirical findings.

· Introduction, motivation and definitions

· Models for pooled time series

· Models for longitudinal data

· Panel data and two-way models

· Dynamic panel data models

· Models for qualitative dependent variables: binary choices

· Models for qualitative dependent variables: multiple choices

· Models for limited dependent variables: censoring and truncation

· Count data models

· Duration models

· Summary of introdutory estimation techniques (OLS, GLS, IV)

· Cross-sectional heteroskedasticity and autocorrelation

· Fixed effetcs (OLS estimator with dummy variables, within transformation)

· Random effects, uncorrelated with the regressors (GLS estimator, between transformation)

· Random effects, correlated with some regressors (IV estimator)

· Two-way panel data models: fixed and random effects

· Dynamic panel data models: first differences, IV and GMM estimators

· Models for qualitative dependent variables: binary choices (Logit and Probit)

· Models for qualitative dependent variables: multiple choices (Multinomial and Conditional Logit, Nested Logit)

· Models for limited dependent variables: censoring and truncation (Tobit)

· Count data models (Poisson and Negative Binomial)

· Duration models

None. Nevertheless, introductory notions of econometrics, micro economics and macroeconomics are taken for granted.

Front-lectures (both in standard lecture rooms and in computer labs).

The final exam, which is unique, consists of a written part and an oral part.

· W. Greene, Econometric Analysis, Prentice Hall International, 4ᵗʰ edition, 2002

· G.S. Maddala, Limited-Dependent and Qualitative Variables in Econometrics, Cambridge University Press, 1983

· M. Manera, M. Galeotti, Microeconometria, Metodi e Applicazioni, Carocci, 2005

· J.M. Wooldridge, Econometric Analysis of Cross Sections and Panel Data, The MIT Press, 2002

Second semester.

Italian.

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Key information

Field of research
SECS-P/05
ECTS
6
Term
Second semester
Activity type
Mandatory
Course Length (Hours)
42
Degree Course Type
2-year Master Degreee
Language
Italian

Staff

    Teacher

  • MM
    Matteo Manera

Enrolment methods

Manual enrolments
Self enrolment (Student)