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Course 2021-2022 a.y.

20754 - DECISION THEORY AND HUMAN BEHAVIOR

Department of Decision Sciences

Course taught in English

Go to class group/s: 31

IM (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...

The course aims to endow students with the ability to use the analytical tools of decision theory, to build and solve microeconomics models, to conduct comparative statics analysis, and to 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...

The course aims to endow students with the ability to apply the theoretical tools of decision theory to a variety of human behavior settings, to articulate economic reasoning, and to evaluate the trade-offs involved in a given choice. In addition, the course introduces students to the world of academic research in economic theory and enables them to develop research ideas.


Teaching methods
  • Face-to-face lectures
  • Group assignments
DETAILS

IMPORTANT 1: we may need to change or adapt any features of the course. For this reason, all information provided below 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’ Announcements area.

IMPORTANT 2: from our point of view, attending and not attending students are identical. We care about each of you and our mission is to make you learn and do great in this course regardless of whether you will be physically in class or attending the course remotely.


Assessment methods
  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
  •   x x
  • Group assignment (report, exercise, presentation, project work etc.)
  • x    
    ATTENDING AND NOT ATTENDING STUDENTS

    There will be no differences in the teaching and assessment methods between attending and not attending students.

    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

    Understanding Decision Theory is about learning the models and the theoretical framework through a combination of mathematical tools and economic intuition. In the theory lectures we learn together a series of concepts and formal models.

    • Group Assignments

    There are 4 assignments that students are asked to solve in groups of 3 or 4. Working with fellow students endows students with team-working skills that are valuable assets in many working environments. In addition, this is one of the best ways to get to know your peers and develop friendships. Group problem sets must be typed using LaTex.

    ATTENDING AND NOT ATTENDING STUDENTS

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

    • 10% of the grade  ---   4 group assignments aimed to acquire sophisticated decision-theoretic analytical skills and the ability to work in groups.
    • 45% of the grade  ---   a midterm exam consisting of theoretical questions and problems aimed to assess students’ 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.
    • 45% of the grade  ---   a final exam consisting of theoretical questions and problems aimed to assess students’ 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.

    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.

    Last change 28/06/2021 14:46