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Regular version of the site
Bachelor 2019/2020

Mechanism Design

Type: Elective course (Economics)
Area of studies: Economics
When: 4 year, 1 module
Mode of studies: offline
Instructors: Aleksei Kondratev
Language: English
ECTS credits: 3

Course Syllabus

Abstract

Mechanism design is a science of how to construct economic mechanisms (rules, environments, institutions) with desirable properties. While the usual microeconomic approach aims at understanding how agents behave in certain environments given certain rules, Mechanism design aims at finding "good" rules that lead to desirable outcomes. At the same time the rules themselves have to be simple and non-manipulable, i.e. provide incentives to participate sincerely. Mechanism design uses game theory tools and can be considered as its most applied part. The range of applications is very broad: from auctions and internet marketplaces to admission of young students to colleges, voting mechanisms, online dating services, and many others.

Learning Objectives

• provide an overview of general methods used to design mechanisms in different areas of life

Expected Learning Outcomes

• Know types of games and solution concepts
• Understand the main concepts and properties of mechanism design
• Know standard auction forms and able to find optimal bidding functions
• Know Revenue Equivalence Theorem, its assumptions and applications
• Able to define and apply fair division, assignment, matching and voting mechanisms
• know properties of these mechanisms
• Able to identify deficiencies in real-life markets

Course Contents

• Introduction to voting. Basic voting rules and their properties.
• Independence of irrelevant alternatives and its relaxations. Arrow's impossibility theorem.
• VCG--mechanisms. Auctions.
• Matching and assignment mechanisms: dictatorships, core, serial, deferred, and immediate acceptance.
• Introduction to Computational social choice.
• Bargaining. Claims problem.

• test 1
• test 2
• test 3
• test 4
• exam

Interim Assessment

• Interim assessment (1 module)
0.6 * exam + 0.1 * test 1 + 0.1 * test 2 + 0.1 * test 3 + 0.1 * test 4

Recommended Core Bibliography

• Handbook of Computational Social Choice. (2016). Cambridge University Press. https://doi.org/10.1017/cbo9781107446984