Econometrics

Anno accademico
2021/2022 Programmi anni precedenti
Titolo corso in inglese
Econometrics
Codice insegnamento
PHD143 (AF:364613 AR:193154)
Modalità
In presenza
Crediti formativi universitari
3 su 6 di Econometrics and Machine Learning
Livello laurea
Corso di Dottorato (D.M.45)
Settore scientifico disciplinare
SECS-P/05
Periodo
I Semestre
Anno corso
1
Sede
VENEZIA
Spazio Moodle
Link allo spazio del corso
The course will provide students with the essential econometric tools needed for climate change analysis. The course contributes to achieve the main objectives of the PhD Programme in Science and Management of Climate Change. It will teach students to design useful strategies to measure and quantify economic phenomena such as climate change and to specify proper econometric models from economic theory.
Knowledge and competences:
- understand how to specify an econometric model starting from an economic model
- understand the implications of the assumptions underlying each econometric model and recognize potential violations of those assumptions

Application of acquired knowledge and skills:
- being able to design useful strategies to measure and quantify economic phenomena such as climate change
- exploit the statistical and econometric tools studied throughout the course to conduct empirical research at the PhD level

Judgement and interpretation skills:
- evaluate strengths and weaknesses of the methodologies analysed and of their empirical application
- being able to critically interpret the outcomes of empirical analyses and of scientific papers
Undergraduate-level notions of calculus, statistics, and basic notions of microeconomics, macroeconomics.
REGRESSION ANALYSIS WITH CROSS-SECTIONAL DATA
- The Simple and Multiple Regression Models: OLS Estimation, Inference and Asymptotics
- Heteroskedasticity and Autocorrelation: the GLS estimator
- Endogeneity: the Instrumental Variable estimator
- Quadratic forms, interaction terms, adjusted R-squared
- Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables
- Heteroskedasticity
- Model misspecification

REGRESSION ANALYSIS WITH LIMITED DEPENDENT VARIABLE
- Linear probability model, Logit and Probit Models

REGRESSION ANALYSIS WITH PANEL DATA
- Pooling Cross Sections Across Time: Simple Panel Data Methods and Fixed Effects Estimation
- Random Effect Estimation

Wooldridge, J.M., Introductory Econometrics: A Modern Approach, Fifth Edition
South-Western College Publishing, 2013
Final take home exam or empirical project
lectures and practical sessions
scritto

Questo insegnamento tratta argomenti connessi alla macroarea "Cambiamento climatico e energia" e concorre alla realizzazione dei relativi obiettivi ONU dell'Agenda 2030 per lo Sviluppo Sostenibile

Programma definitivo.