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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

2022/2023
Academic Year
ENG
Instruction in English
3
ECTS credits
Type:
Mago-Lego
When:
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 empirical workhorse models using software like R and MATLAB.