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ECONOMETRICS
- Oggetto:
ECONOMETRICS
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Anno accademico 2023/2024
- Codice dell'attività didattica
- CPS0849
- Docente
- Stefano Bianchini (Titolare dell'insegnamento)
- Corso di studi
- Master's Degree Course in Economic analysis and policy
- Anno
- 1° anno
- Periodo didattico
- Da definire
- Tipologia
- Caratterizzante
- Crediti/Valenza
- 9
- SSD dell'attività didattica
- SECS-S/03 - statistica economica
- Modalità di erogazione
- Tradizionale
- Lingua di insegnamento
- Inglese
- Modalità di frequenza
- Facoltativa
- Tipologia d'esame
- Orale
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Sommario insegnamento
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Obiettivi formativi
The objective of this course is to enable students to (i) acquire or strengthen the theoretical foundations of econometrics and (ii) apply these foundations to the practical use of econometrics.- Oggetto:
Risultati dell'apprendimento attesi
At the end of this course, students will be able to:
- Master the mathematical and statistical tools useful for econometrics and impact evaluation
- Understand the scope and limits of certain specifications;
- Interpret the results of estimates;
- Perform hypothesis testing and predictions;
- Prepare, format and harmonize databases and perform empirical estimation;
- Improve their ability to work with R programming language;
- Accumulate hands-on experience by doing empirical work.- Oggetto:
Modalità di insegnamento
The course combines class teaching [28h], discussion of specific cases [6h], hands-on sessions in R [20h]- Oggetto:
Modalità di verifica dell'apprendimento
- Two mandatory take-home assignments [20%]
- Project and discussion (groups of 2 students max) [30%]
- Written examination (theoretical questions and practical exercises) [50%]- Oggetto:
Programma
The course is structured in two macro parts and combines theoretical and practical sessions in R.Part 1: Econometrics
- Recap of some basic concepts of linear algebra and statistics;
- Linear regression (part 1): specification and interpretation;
- Linear regression (part 2): inference and hypothesis testing;
- Heteroscedasticity and autocorrelation;
- Endogeneity: instrumental variable estimators;
- Models for limited dependent variables.Part 2: Impact evaluation
- What is impact evaluation: set evaluation questions and sampling strategies;
- Randomized selection methods;
- Regression discontinuity design;
- Difference-in-difference;
- Propensity score matching.Testi consigliati e bibliografia
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- Wooldridge, J. M. (2015). Introductory econometrics: A modern approach. Cengage learning.
- Verbeek, Marno (2017), A Guide to Modern Econometrics, Fifth Edition, Wiley.
- Gertler, P. J., Martinez, S., Premand, P., Rawlings, L. B., & Vermeersch, C. M. (2016). Impact evaluation in practice. World Bank Publications (2nd Edition).
- Khandker, S. R., Koolwal, G. B., & Samad, H. A. (2010). Handbook on impact evaluation: quantitative methods and practices. World Bank Publications.
Further scientific articles and references will be provided all along the course.
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