We use cookies in order to improve the quality and usability of the HSE website. More information about the use of cookies is available here, and the regulations on processing personal data can be found here. By continuing to use the site, you hereby confirm that you have been informed of the use of cookies by the HSE website and agree with our rules for processing personal data. You may disable cookies in your browser settings.

  • A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
Contacts

109028, Moscow
Pokrovsky blvd. 11,
Room S-527
Phone: (495) 772-95-99 ext.27502, 27503, 27498

Administration
Department Head Svetlana B. Avdasheva
Deputy Department Head Liudmila S. Zasimova
Manager Maxim Shevelev
Book
Academic Star Wars: Excellence Initiatives in Global Perspective
In press

Yudkevich Maria, Altbach P. G., Salmi J.

Cambridge: MIT Press, 2023.

Article
The Impact of Carbon Tax and Research Subsidies on Economic Growth in Japan

Besstremyannaya G., Dasher R., Golovan S.

HSE Economic Journal. 2025. Vol. 29. No. 1. P. 72-102.

Book chapter
Science or industry: Improving the quality of the Russian higher education system

Panova A., Slepyh V.

In bk.: Vocation, Technology & Education. Vol. 1. Iss. 4. Shenzhen Polytechnic University, 2024.

Working paper
Living Standards in the USSR during the Interwar Period

Voskoboynikov I.

Economics/EC. WP BRP. Высшая школа экономики, 2023. No. 264.

Contacts

109028, Moscow
Pokrovsky blvd. 11,
Room S-527
Phone: (495) 772-95-99 ext.27502, 27503, 27498

Administration
Department Head Svetlana B. Avdasheva
Deputy Department Head Liudmila S. Zasimova
Manager Maxim Shevelev

Empirical Industrial Organization

2020/2021
Academic Year
ENG
Instruction in English
3
ECTS credits
Type:
Elective course
When:
1 year, 3 module

Instructor

Course Syllabus

Abstract

This course is designed to introduce students to the tools for the empirical analysis of industries and markets. Broadly speaking, empirical industrial organization (EIO) combines empirical methods, data, and models to analyze imperfect competition and the organization of markets. Modern methods of the EIO are widely applied in merger review, antitrust litigation, regulatory decision making, marketing, and other related fields. Moreover, the increasing availability of firm- and consumer-level data ("big data") opens new empirical questions, that cannot be answered without understanding the basics of the EIO analysis. In this course, we will cover traditional empirical models related to (1) demand estimation for homogeneous and differentiated products; (2) production function estimation and firm productivity; (3) identification of conduct; (4) static entry/exit models. The course is associated to exercise sessions devoted to practical applications. We will replicate some of the empirical workhorse models using software like Stata and MATLAB.
Learning Objectives

Learning Objectives

  • You are expected to acquire a broad knowledge of the key topics and techniques of empirical industrial organization.
  • You are expected to acquire a broad knowledge of the key topics and techniques of empirical industrial organization.
  • You are expected to be able to conduct your own independent industrial analysis using real-life data.
  • You are expected to be able to conduct your own independent industrial analysis using real-life data.
Expected Learning Outcomes

Expected Learning Outcomes

  • Coming to the same level of knowledge of the needed econometric tools.
  • Learning methods to detect collusion on the data.
  • Ability to estimate demand.
  • Ability to estimate production function.
  • Ability to model market entry.
  • Deepen knowledge of the previously discussed topics.
Course Contents

Course Contents

  • Introduction to Empirical Industrial Organization
    Review of the basic econometrics tools, introduction to the topics and problems of EIO.
  • Competition, collusion and cartel
    Porter (1983, Bell); Bresnahan (1987, JIE); Genesove & Mullin (1998, RAND)
  • Estimation of demand for differentiated goods
    Berry (1994, RAND); Berry, Levinsohn, Pakes (1995, Econometrica); Train (2009, Cambridge University Press)
  • Estimation of production functions
    Olley &Pakes (1996, Econometrica); Levinsohn & Petrin (2003, ReStud); Ackerberg, Caves, Frazer (2015, Econometrica)
  • Estimation of static entry/exit games
    Bresnahan & Reiss (1991, JPE); Seim (2006, RAND)
  • Extensions and applications or additional selected topics in EIO
    This lecture includes topics based on students' interests. It can include merger analysis, auctions, basics of the dynamic EIO, or deepen the previously discussed topics.
Assessment Elements

Assessment Elements

  • non-blocking Homework 1
    The content of homework assignments will be the application of learned estimation techniques in practice and the replication of related papers.
  • non-blocking Term project
    Term project evaluation consists of the short essay in a form of a research proposal.
  • non-blocking Exam
    The final written exam will mainly consist of open questions related to the practical application of EIO for industry analysis.
  • non-blocking Homework 2
Interim Assessment

Interim Assessment

  • Interim assessment (3 module)
    0.3 * Exam + 0.25 * Homework 1 + 0.25 * Homework 2 + 0.2 * Term project
Bibliography

Bibliography

Recommended Core Bibliography

  • Belleflamme, P., & Peitz, M. (2010). Industrial Organization : Markets and Strategies. Cambridge, UK: Cambridge eText. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=324082
  • Bresnahan, T. F., & Reiss, P. C. (1991). Entry and competition in concentrated markets. Journal of Political Economy, 99(5), 977. https://doi.org/10.1086/261786
  • Olley, G. S., & Pakes, A. (1996). The Dynamics of Productivity in the Telecommunications Equipment Industry. Econometrica, (6), 1263. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.ecm.emetrp.v64y1996i6p1263.97
  • Steven T. Berry. (1994). Estimating Discrete-Choice Models of Product Differentiation. RAND Journal of Economics, (2), 242. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.rje.randje.v25y1994isummerp242.262

Recommended Additional Bibliography

  • Berry, S., Levinsohn, J., & Pakes, A. (1995). Automobile Prices in Market Equilibrium. Econometrica, (4), 841. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.ecm.emetrp.v63y1995i4p841.90