AØKK08201U Mechanism Design

Volume 2019/2020
Education

MSc programme in Economics – elective course

 

The PhD Programme in Economics at the Department of Economics  - elective course with resarch module (PhD students must contact the study administration and the lecturer in order to write the research assignment)

 

The course is a part of the admission requirements for the 5+3 PhD Programme in Economics. Please consult the 5+3 PhD admission requirements.

Content

Mechanism design explores institutions in environments with asymmetric information. While game theory explores how players act in a given environment, mechanism design takes a dual approach and asks instead how we should design the environment to induce the desirable behavior. Real-world applications include, among others, market design, organization of social choice and voting mechanisms, design of regulations and institutional design in general.

 

The course can roughly be split in two parts:

  • Part 1 introduces the students to the classic results and methods of mechanism design. We introduce classical mechanisms and discuss their strengths and weaknesses. We then look at mechanisms that are optimal in some special cases, such as trade, social choice, and matching problems.
  • Part 2 explores the world beyond the models described in the first part. In particular, we look at cases when agents' information is correlated, at mechanism design in dynamic settings, at mechanism design without money, and conclude with information design.

 

The course is based on selected chapters from the textbooks by Mas-Colell, Whinston and Green, and by Roth and Sotomayor (part 1), as well as on published papers (part 2).

The content is subject to minor changes.

 

Learning Outcome

After completing the course the student is expected to be able to:

 

Knowledge:

  • Account for the fundamental ideas behind and approaches to mechanism design.

 

Skills:

  • Choose mechanisms that induce the desired outcomes in various environments.
  • Analyze the drawbacks of existing institutions and suggest alternatives or identify reasons why none are available.

 

Competencies:

  • Use the analytical framework of mechanism design in discussions of the real-world institutions, proposed policies, and market strategies.

 

Textbooks:

  • Mas-Colell, Andreu, Michael Dennis Whinston, and Jerry R. Green. Microeconomic theory. New York: Oxford University Press, 1995, ISBN: 978-0195073409 (Chapters 21 and 23.)
  • Roth, A., & Sotomayor, M. (1990). Two-Sided Matching: A Study in Game-Theoretic Modeling and Analysis (Econometric Society Monographs). Cambridge: Cambridge University Press. doi:10.1017/​CCOL052139015X (Selected chapters.)

 

Papers: (the list is preliminary and will likely see changes during the course)

  • Cremer, J., & McLean, R. P. (1988). Full extraction of the surplus in Bayesian and dominant strategy auctions. Econometrica, 1247-1257.
  • Bergemann, D., & Välimäki, J. (2019). Dynamic Mechanism Design: An Introduction. Journal of Economic Literature, 57 (2): 235-74. doi: 10.1257/jel.20180892
  • Bergemann, D., & Morris, S. (2019). Information Design: A Unified Perspective. Journal of Economic Literature, 57 (1): 44-95. doi: 10.1257/jel.20181489
It is strongly recommended to have followed the course Microeconomics III at the study of Economics, University of Copenhagen, prior taking this course.

Mastering the material from the mathematics courses in the Bachelor program (Mathematics A and B) is very helpful.
Schedule:
3 hours of lectures every week from week 36 to 50 (except week 42).

Schema:
The overall schema for the Master can be seen at KUnet:
MSc in Economics => "Courses and teaching" => "Planning and overview" => "Your timetable"

Timetable and venue:
To see the time and location of lectures please press the link under "Se skema" (See schedule) at the right side of this page. E means Autumn.

You can find the similar information partly in English at
https:/​/​skema.ku.dk/​ku1920/​uk/​module.htm
-Select Department: “2200-Økonomisk Institut” (and wait for respond)
-Select Module:: “2200-E19; [Name of course]””
-Select Report Type: “List – Weekdays”
-Select Period: “Efterår/Autumn – Weeks 31-5”
Press: “ View Timetable”
  • Category
  • Hours
  • Exam
  • 24
  • Lectures
  • 42
  • Preparation
  • 140
  • Total
  • 206
Credit
7,5 ECTS
Type of assessment
Written assignment, 24 hours
individual take-home exam. It is not allowed to collaborate on the assignment with anyone.
The exam assignment is in English and must be answered in English.
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Exam registration requirements

One mandatory take-home assignment must be approved to be able to sit the exam.

Collaboration is allowed on the assignment.

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Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
for the written exam. The exam may be chosen for external censorship by random check.
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Exam period

The exam takes place:

From 5 January 2020 at 10.00 AM to 6 January 2020 at 10.00 AM

 

Exam information:

In special cases, the exam date can be changed to another day and time within the exam period.

 

For enrolled students more information about examination, rules etc. is available at the intranet for Master students (UK) and Master students (DK).

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Re-exam

The reexam takes place:

From 17 February 2020 at 10.00 AM to 18 February 2020 at 10.00 AM

 

NOTE: If only a few students have registered for the written re-exam, the reexam might change to an oral exam including the date, time and place for the exam, which will be informed by the Examination Office.

 

Reexam information:

Information about the reexam will be available in the Digital Exam  early February.

 

More information is available at  Master students (UK)and Master students (DK).  

 

Criteria for exam assesment

Students are assessed on the extent to which they master the learning outcome for the course.

 

To receive the top grade, the student must with no or only a few minor weaknesses be able to demonstrate an excellent performance displaying a high level of command of all aspects of the relevant material and can make use of the knowledge, skills and competencies listed in the learning outcomes.