Training and Research
PhD Programme Courses/classes - 2022/2023
Advice to Young Economists
Credits: 4
Language: English
Teacher: Marco Piovesan
Behavioral and Experimental Economics
Credits: 5
Language: Italian
Teacher: Simone Quercia, Maria Vittoria Levati, Marco Piovesan
Development Economics
Credits: 5
Language: English
Teacher: Federico Perali
Finance
Credits: 5
Language: English
Teacher: Cecilia Mancini
Game Theory
Credits: 5
Language: Inglese
Teacher: Francesco De Sinopoli
Inequality
Credits: 5
Language: English
Teacher: Francesco Andreoli, Claudio Zoli
Introduction to Probability – Module II (attività formativa per la Scuola di Dottorato)
Credits: 2
Language: Italian
Teacher: Claudia Di Caterina
Introduction to Probability – Module I
Credits: 2
Language: English
Introduction to Statistical Inference
Credits: 2
Language: English
Teacher: Marco Minozzo
Macroeconomics I
Credits: 7,5
Language: English
Teacher: Tamara Fioroni, Alessia Campolmi
Mathematics
Credits: 7,5
Language: English
Teacher: Letizia Pellegrini, Alberto Peretti
Microeconomics 1
Credits: 10,5
Language: English
Teacher: Simona Fiore, Claudio Zoli, Martina Menon
Political economy
Credits: 5
Language: English
Teacher: Emanuele Bracco, Roberto Ricciuti
Probability
Credits: 7,5
Language: English
Teacher: Marco Minozzo
Game Theory (2022/2023)
Teacher
Referent
Credits
5
Language
Inglese
Class attendance
Free Choice
Location
VERONA
Learning objectives
The goal of the course is to give students a solid background in Game Theory. Game theory provides a structured way to study strategic interactions and can be used to better understand business strategy, contracts, auctions, voting systems, crime, bargaining, and virtually any social interaction one can think of. At the end of the course students should be able to critically read and understand models proposed by economists to describe the above social interactions. Furthermore, students should be able to describe such social interactions as games.
Prerequisites and basic notions
Noone
Program
Normal Form Games.
-Nash Equilibrium.
-Iterated Dominance.
-Incomplete Information.
-Trembling-Hand Perfection.
Extensive Form Games.
-Backward Induction.
-Subgame Perfection.
-Sequential Equilibrium and Extensive Form Perfection.
-Beliefs-based Refinements.
Bibliography
Didactic methods
Frontal
Learning assessment procedures
Written test
Assessment
The examination spans all over the program and aims to test the understanding of the main concepts introduced. In the grading process, more enphasis will be given to the reasonings than to the exact calculations.
Criteria for the composition of the final grade
.
PhD school courses/classes - 2022/2023
PhD students
mattia.argentopagani@univr.it
matteo.benedini@univr.it
laura.bonisoli@univr.it
cesare.cottonaro@univr.it
lidingrong.huang@univr.it
juniorparfait.ngalamo@univr.it
alice.trettenero@univr.it
simone.vecchi@univr.it
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Guidelines for PhD students
Below you will find the files that contain the Guidelines for PhD students and rules for the acquisition of ECTS credits (in Italian: "CFU") for the Academic Year 2024/2025.
Documents
| Title | Info File |
|---|---|
Guidelines PhD students
|
pdf, en, 137 KB, 11/12/24 |
|
Linee guida dottorandi
|
pdf, it, 137 KB, 11/12/24 |
|
Percorso formativo
|
pdf, it, 125 KB, 11/12/24 |
|
Training program
|
pdf, en, 124 KB, 11/12/24 |
