CdSECONOMICS
Codice246PP
CFU9
PeriodoSecondo semestre
LinguaInglese
L'obiettivo del corso è quello di fornire agli studenti i principi fondamentali dell'econometria teorica e gli strumenti computazionali utilizzati nell'analisi empirica moderna on una particolare enfasi alla stima delle relazioni causali tra le variabili economiche.
The course's objective is to cover the theory behind classical econometrics and its applications in modern empirical microeconomic analyses. The emphasis is mainly on the estimation of causal relations between economic variables.
Per l'accertamento delle conoscenze saranno svolte delle prove in itinere.
Ongoing assessment to monitor academic progress will be carried out.
Alla fine del corso gli studenti dovrebbero avere una comprensione critica delle idee alla base della teoria econometrica e dovrebbero essere in grado di applicare queste idee al mondo reale. Gli studenti inoltre acquisiranno familiarità con il software statistico R che sarà utilizzato durante tutto il corso.
By the end of the course, students will have a good understanding of econometric theory's core ideas and they will be able to apply these ideas to real-world cases using R, the statistical software used throughout the course.
Alcune lezioni saranno dedicate alle appliazioni empiriche per le quali sarà usato il software statistico R. Durante le sessioni di laboratorio, molti esempi saranno presentati al dine di far comprendere agli studenti la giusta specificazione econometrica da utlizzare e la corretta interpretazione dei risultati empirici.
About a third of the lectures will be devoted to empirical applications. They will require R, the statistical software that is one of the most used languages used by practitioners and researchers. The practical sessions' goal is to make students appreciate the applied relevance of the topics covered during the theoretical lectures. The empirical applications are from the literature and are interesting from a policy perspective.
Frequenza
La frequenza alle lezioni è consigliata, così come una preparazione per una piena partecipazione alla lezione. Gli studenti che hanno problemi possono fare domande durante la lezione o durante l'orario di ricevimento.
Imbrogli o altre forme di disonestà
Non ci saranno tolleranze nei confronti di qualsiasi tipo di imbroglio. Gli studenti che saranno trovati a copiare non supereranno l'esame e il loro comportamento sarà riportato agli uffici competenti.
Attendance
It is expected that all students attend the lectures, be up to date with their readings, and be prepared to participate fully in class. If you have problems mastering the material covered in class, please ask questions in class or during office hours.
Cheating and other forms of dishonesty
I have no tolerance for cheating. I regard academic dishonesty as a very serious offense. Students caught cheating during exams will fail the class and will be reported to the appropriate officer of the college.
Durante le lezioni la partecipazione attiva degli studenti sarà valutata, così come la correttezza del loro comportamento nello svolgimento degli esami.
During lectures the active participation of students will be evaluated, as well as their honesty during the exams.
Gli studenti devono essere familiari con i concetti base della probabilità, della statistica e dell'algebra lineare. Il corso include comunque un ripasso di statistica e probabilità. Gli studenti che non hanno familiarità con questi strumenti dovrebbero riverderli in dettaglio per loro conto.
Importante: A chi non avesso mai seguito corsi di introduzione all'econometria è fortemente consigliato di colmare le proprie lacune utilizzando un testo non avanzato, come ad esempio:
Wooldridge, Jeffrey M. Introductory econometrics: A modern approach. Nelson
Education, 2016.
Una conoscenza base del software R è richiesta. Gli studenti che non sono familiari con le funzionalità base di R devono cercare di recuperare il loro gap. A tal fine possono far riferimento al testo Using R for Introductory Econometrics by Florian Heiss.
Students need to be familiar with basic concepts in probability and statistics, as well as
linear algebra. The course includes a brief statistics and probability refresher. However,
students lacking familiarity with this material should make time out of class to review it
in detail.
Important: If you have not taken an introductory econometric course, we suggest students to fill the gap in their preparation by using undergraduate material. A good reference for this purpose is:
- Wooldridge, Jeffrey M. Introductory econometrics: A modern approach. Nelson Education, 2016.
Basic knowledge of R is assumed. If students feel they are not confident in using the basic functionalities of R, they should get up to speed. A very useful resource to this regard is Using R for Introductory Econometrics by Florian Heiss (Using R for Introductory Econometrics: Second edition www.urfie.net)
Lezioni frontali ed esercitazioni in laboratorio.
Lectures and lab sessions.
1. Basic Asymptotic Theory
2. Single equation Linear Model and Ordinary Least Squares Estimation
3. Instrumental Variables of Single Equation Models
5. Basic Linear Unobserved Panel Data Models
6. Binary Response Models
7. Other Nonlinear Models and estimators
8. Special topic: Program Evaluation
1. Basic Asymptotic Theory
2. Single equation Linear Model and Ordinary Least Squares Estimation
3. Instrumental Variables of Single Equation Models
5. Basic Linear Unobserved Panel Data Models
6. Binary Response Models
7. Other Nonlinear Models and estimators
8. Special topic: Program Evaluation
Principale libro di testo:
- Wooldridge, J. M.: Introductory Econometrics: A Modern Approach 5th edition), South-Western Publishing.
Agli studenti saranno anche forniti degli Handout.
Per R:
- Heiss, F.: Using R for Introductory Econometrics (http://www.urfie.net/)
The main reference for this courses is:
- Wooldridge, J. M.: Econometric analysis of cross section and panel data. MITpress, 2010.
We will also provide students with handouts.
For R:
- Heiss, F.: Using R for Introductory Econometrics (http://www.urfie.net/)
All homework assignments contain a mixture of empirical and theoretical exercises covering the material discussed during lectures. Homework assignments are made available to students periodically (they will be posted on Moodle). There would be five HW, three before the midterm and two after the midterm.
EMERGENZA COVID19:
Vista le modalite di insegnamento remoto/ibrido, per gli appelli della sessione estivi il voto finale consiste:
1) Homework
2) Midterm
3) Esame finale
Queste tre componenti costituiranno il voto finale.
Consultare il canale di Teams o il sito del corso https://advmetrics.gragusa.org per informazioni dettagliate sulle modalita' di esame.
Per gli studenti che non hanno consegnato gli homework, il voto finale consistera' esclusivamente della componente scritta e orale.
The final grade for this class will be calculated as follow:
1) Homework assignments
2) Midterm exam (written, remote)
2) Final exam (written, remote)
The final grade will depend on a midterm, a final, and the homework assignments. Students have some flexibility in choosing the aggregation of these three different scores into a final grade.
Students have two options:
(Standard option)
Take a comprehensive final written examination on the date of the regular ``appelli''.
On the first appello right after the end of the course, the course grade will be given by the maximum between the grade on the final and the average of the final itself and the homework assignments. The homework assignments will count if and only if the student received at least 18/30 on each.
On subsequent dates, the course grade will be just that of the comprehensive written final.
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(Midterm option)
Students take two written examinations: {a midterm exam) on April, 9th and a final exam on the date of the first ``appello'' right after the end of lectures.
The final grade is in this case given by the weighted average of the grades on the two written exams and the homework assignments. The weights are given by:
Homework assignments 30%
Midterm 30%
Final 40%
Important:
- Only students with a grade of at least 18/30 on all homework assignments due back before the midterm are allowed to take the midterm exam. Students who do not satisfy this requirement won't be allowed to take the midterm.
- To be considered, the grade on each assignment, the midterm, and the final must be at least 18/30.
- The midterm option is only available on the first appello right after the end of the course. After that, only the comprehensive final option (without the assignments) will be available.
Students will not be allowed to take the exam on two consecutive dates.
https://advmetrics.gragusa.org
Ricevimento:
Per appuntamento
Office hours:
By appointment