Insegnamento a.a. 2023-2024

20629 - EMPIRICAL INDUSTRIAL ORGANIZATION AND MARKET DESIGN

Department of Economics

Course taught in English
Go to class group/s: 31
CLMG (6 credits - I sem. - OP  |  12 credits SECS-P/06) - M (6 credits - I sem. - OP  |  SECS-P/06) - IM (6 credits - I sem. - OP  |  SECS-P/06) - MM (6 credits - I sem. - OP  |  SECS-P/06) - AFC (6 credits - I sem. - OP  |  SECS-P/06) - CLELI (6 credits - I sem. - OP  |  SECS-P/06) - ACME (6 credits - I sem. - OP  |  SECS-P/06) - DES-ESS (6 credits - I sem. - OP  |  SECS-P/06) - EMIT (6 credits - I sem. - OP  |  SECS-P/06) - GIO (6 credits - I sem. - OP  |  SECS-P/06) - DSBA (6 credits - I sem. - OP  |  SECS-P/06) - PPA (6 credits - I sem. - OP  |  SECS-P/06) - FIN (6 credits - I sem. - OP  |  SECS-P/06)
Course Director:
FRANCESCO DECAROLIS

Classes: 31 (I sem.)
Instructors:
Class 31: FRANCESCO DECAROLIS


Suggested background knowledge

Students who enrol in this course should have at least some basic knowledge of game theory and statistics/econometrics. Knowledge of Phyton is also useful.

Mission & Content Summary

MISSION

This is a topics course in the methodologies used to analyze data in Industrial Organization and Market Design. It blends together three tightly connected ingredients: (i) Industrial Organization - the field of microeconomics studying the functioning of imperfectly competitive markets. (ii) Market Design - the use of microeconomics tools to design marketplaces to fix market failures. (iii) Empirical microeconomics (or "micro econometrics") - the analysis of individual-level data on the economic behavior of individuals or firms using reduced-form (i.e., regression) methods or structural (i.e., model-based) methods applied to cross-section or panel data, often "big data." The course covers two major areas of IO: auctions and demand estimation. Regarding auction models, the course covers three main types of markets: single unit auctions (like art auctions or contract procurement), multiunit auctions (like treasury bills or electricity auctions) and online auctions (like online ad auctions in Google AdWords or eBay auctions). Regarding demand estimation, the course focuses on how to use price and quantity data to estimate consumer's utility and firms' costs and how to employ these estimates to analyze market power, collusion, mergers and acquisitions and the introduction of new products.

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

At the end of the course student will be able to...
  • 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

At the end of the course student will be able to...
  • 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

  • Face-to-face lectures
  • Guest speaker's talks (in class or in distance)
  • Exercises (exercises, database, software etc.)
  • Individual assignments
  • Group 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
  • Written individual exam (traditional/online)
   x x
  • Individual assignment (report, exercise, presentation, project work etc.)
 x    
  • Group assignment (report, exercise, presentation, project work etc.)
 x    

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.
Last change 29/05/2023 16:45