Course 2022-2023 a.y.

20754 - DECISION THEORY AND HUMAN BEHAVIOR

Department of Decision Sciences

Course taught in English
Go to class group/s: 31
CLMG (6 credits - I sem. - OP  |  SECS-S/06)
Course Director:
MASSIMO MARINACCI

Classes: 31 (I sem.)
Instructors:
Class 31: MASSIMO MARINACCI


Mission & Content Summary

MISSION

The course intends to introduce students to classical topics and recent advances at the frontier of decision theory. The elegant and powerful tools of decision theory endow students with an analytical mindset and a strong quantitative preparation, which forms the building block for understanding the foundations of microeconomic analysis. The course helps students address fascinating questions about human behavior in economic and noneconomic settings using a rigorous mathematical approach.

CONTENT SUMMARY

Classical Theory

  ∙  Methodology of decision theory
  ∙  Preferences
  ∙  Utility theory
  ∙  Decision making under risk
  ∙  Risk attitudes
  ∙  Applications
  ∙  Decision making under uncertainty
  ∙  Information acquisition problems

 

Modern and contemporary theory

  ∙  Decision making under ambiguity
  ∙  Decision making under model uncertainty
  ∙  Applications


Intended Learning Outcomes (ILO)

KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • use the analytical tools of decision theory
  • build and solve microeconomics models, to conduct comparative statics analysis
  • solve constrained optimization problems applied to a variety of economic and noneconomic settings.

APPLYING KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • apply the theoretical tools of decision theory to a variety of human behavior settings,
  • articulate economic reasoning,
  • evaluate the trade-offs involved in a given choice,
  • to develop research ideas.

Teaching methods

  • Face-to-face lectures
  • Group assignments

DETAILS

We have designed a course that enables students to acquire a profound understanding of the theoretical underpinnings of human decision making. To accomplish this goal, the course is built around these building blocks:

 

  • Face-to-face Lectures
    • In the lectures students learn concepts and formal models through a combination of mathematical tools and economic intuition.

 

  • Group Assignments
    • Four group assignments are assigned to groups of 3 or 4 students. They permit students to improve and to verify their understaning of the course material as well as to develop team-working skills. Group problem sets must be typed using LaTex (or a software that produces a Latex output, such as Lyx or Scientific WorkPlace).

 

  • Collective office hours
    • To encourage continuous interaction between instructors and students, through Zoom the instructors will hold weekly meetings to answer students' questions.

 

 

IMPORTANT: we may need to change or adapt any features of the course. For this reason, all information provided here is subject to change due to unforeseen circumstances. However, be reassured that if we need to make changes, these changes will be always beneficial to students and swiftly communicated in class and via email, and posted on Blackboard’s Announcements area.


Assessment methods

  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
  x x

ATTENDING AND NOT ATTENDING STUDENTS

There is no difference between attending and non-attending students. The material, the workload, the requirements, and the evaluation based on exams, are identical for each student, attending and non-attending.

 

With the purpose of measuring the acquisition of the learning outcomes mentioned above, students’ assessment is based on the following items:

  • 50% of the grade  ---   a midterm exam (either in-class or take-home) consisting of theoretical questions and problems. Skill tested are: the ability to apply the analytical tools illustrated during the course, to solve and explain decision theory models, to conduct comparative statics analysis, and to solve constrained optimization problems applied to a variety of economic and noneconomic settings.
  • 50% of the grade  ---   a final exam (in-class) consisting of theoretical questions and problems. Skill tested are: the ability to apply the analytical tools illustrated during the course, to solve and explain decision theory models, to conduct comparative statics analysis, and to solve constrained optimization problems applied to a variety of economic and noneconomic settings.

 

The midterm format, in-class or take-home, will be communicated during the first two weeks of the course.

 

Instead of taking the Midterm and the Final Exams, students can take a General written exam on the entire program (the general exam counts 90% of the overall grade).

 

Students are required to familiarize themselves with the Bocconi Academic Conduct Code. All violations, especially the ones dealing with examinations (e.g., cheating, etc.), will have to be reported to the office of the Dean for Undergraduate Studies.

Examinations are closed books.

 

Grades are based on the X/30 cum laude scale with the minimum passing grade for the entire course being 18/30. A minimum grade of at least 10/30 in both the midterm and final exams must be obtained. If this is not the case, students take a General exam on the entire program.


Teaching materials


ATTENDING AND NOT ATTENDING STUDENTS

The course is based on the instructors’ lecture notes. Additional readings will be communicated during the semester.

 

The teaching material is posted on BlackBoard.

Last change 08/06/2022 09:16