20629 - EMPIRICAL INDUSTRIAL ORGANIZATION AND MARKET DESIGN
Department of Economics
FRANCESCO DECAROLIS
Suggested background knowledge
Mission & Content Summary
MISSION
CONTENT SUMMARY
Part I - Demand Estimation:
- Introduction to Demand Estimation & Demand in Product Space.
- Demand in Characteristics Space: Basics Discrete Choice Models.
- Demand in Characteristics Space: Advanced Models.
- Demand Estimation: Supply Side, IV Choice and Computational Issues.
- Applications to Antitrust: Market Power and Collusion.
- Applications to Competition Policy: Market Power, Collusion and M&A.
- Applications to Industrial Policy: Subsidies and the Introduction of New Goods.
Part II - Market Design, Auctions and Matching:
- Review of Game Theory and Basics of Auction and Matching Theory.
- Estimation of Matching Models
- Estimation Methods for Auction and Procurement Data.
- Applications: Single Unit Auctions.
- Applications: Multiunit Auctions.
- Applications: Internet Auctions.
Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
- Identify the areas of the economy where the tools of empirical industrial organization and market design can be applied.
- Describe the perspective through which the IO approach looks at markets.
- Recognize the appropriate tools for analyzing data and use them to estimate relevant features of the data.
- Read, explain and reproduce the quantitative analyses conducted in important cases in antitrust and competition policy.
- Distinguish the different auction and procurement systems throughout the economy and define their characteristics and implications.
APPLYING KNOWLEDGE AND UNDERSTANDING
- Use the tools learnt in class to analyze the functioning of imperfectly competitive markets.
- Read and interpret the evidence produced by others (both academic papers and studies by private consulting firms or public bodies) concerning these markets and to directly examine the data and compute/estimate the quantities needed to evaluate/assess the functioning of these markets.
- Master the tools of data analysis that have become an essential part of the economists' work in both the private sector (consulting firms and data-driven, such as Amazon, Google or Microsoft) and the public sector (competition authorities and central banks).
Teaching methods
- Guest speaker's talks (in class or in distance)
- Practical Exercises
- Individual works / Assignments
- Collaborative Works / Assignments
DETAILS
- Guest speaker's talks (in class or in distance): a guest speaker discusses how in his company/institutions the economists working there use the tools discussed in class to conduct their activity.
- Exercises (Exercises, database, software etc.): exercises aimed at refining the students' understanding of the empirical methods discussed in class is given out for both parts of the class.
- Assignments: both individual and group assignments are given out during the course of the class to apply the empirical methods presented in class.
Assessment methods
Continuous assessment | Partial exams | General exam | |
---|---|---|---|
|
x | x |
ATTENDING AND NOT ATTENDING STUDENTS
Grading:
Written exam 30%
Empirical project 40%
Due on Firday, December 20 by midnight.
3 Problem sets 30%
PS1: Due on Firday, September 27 by midnight.
PS2: Due on Firday, October 18 by midnight.
PS3: Due on Firday, November 29 by midnight.
Teaching materials
ATTENDING AND NOT ATTENDING STUDENTS
The class is based on the instructor's note and on a few academic papers that are detailed in the course syllabus. The following four books are not required but they all contain useful material from which the instructor's notes draw:
- A. ROTH, Who Gets What ― and Why: The New Economics of Matchmaking and Market Design, Eamon Dolan/Mariner Books, Reprint edition, June 7, 2016.
- K. TRAIN, Discrete Choice Methods with Simulation, Cambridge University Press, June 30, 2009, 2 edition.
- J. ANGRIST, J.S. PISCHKE, Mastering 'Metrics: The Path from Cause to Effect, Princeton University Press; with French flaps edition (December 21, 2014).
- H.J. PAARSCH, H. HONG, An Introduction to the Structural Econometrics of Auction Data, The MIT Press, January 6, 2006, 5-6-4-5-8th edition.