Бакалавриат 2026/2027

Микроэкономика

ID 1212562

Статус: Курс обязательный (Международный бизнес)

Кто читает: Департамент финансового менеджмента

Где читается: Высшая школа бизнеса

Когда читается: 1-й курс, 1, 2 модуль

Охват аудитории: для своего кампуса

Преподаватели: Федоровых Данил Александрович

Язык: английский

Кредиты: 6

Контактные часы: 96

Course Syllabus

Abstract

Microeconomics is a first-year course for the International Business program, taught in English over modules 1 and 2. It treats microeconomics as the language in which business arguments are made and tested: what a price should be, where profit comes from and why it erodes, what a competitor does when you move first, and why the best supplier is rarely the cheapest. The course is built around a single organizing decision about assessment. Every graded element is produced under supervision, in the room: short written activities at the start of some seminars, artifacts written and handed in during seminars, a midterm, an oral defense of the team project, and a written examination. No mark in this course depends on work produced outside the classroom, so students are free to use generative AI without restriction while preparing. One part of the examination assesses the student’s ability to find and correct errors in AI-generated economic analysis. 28 lectures (one of which is the midterm examination) and 20 seminars, all 80 minutes. Seminars run in four formats — problem seminars, laboratory sessions built on experiments and games, decision cases on primary documents and real data, and the project presentations.

Learning Objectives

• Give students a working command of microeconomic reasoning as applied to business decisions, sufficient to analyze a market, a price and a competitive move without further coursework in economics.
• Establish the distinction between what a model assumes and what it establishes, and the habit of naming both.
• Develop the ability to work from primary evidence — company filings, competition-authority decisions, and price data collected by the students themselves — rather than from stylized numbers.
• Develop the ability to use generative AI productively on economic analysis and to identify where it is wrong.

Expected Learning Outcomes

• Apply marginal reasoning and opportunity cost to a business decision, and identify what is and is not a cost.
• Measure and interpret an elasticity from real price and quantity data, and use it to evaluate a proposed price change.
• Explain the structure of a firm’s costs and decide whether an activity should be performed inside the firm or bought.
• Distinguish the four standard market structures, and explain why free entry drives economic profit to zero even where firms price above marginal cost.
• Set a price using economic value estimation and breakeven analysis, and choose an appropriate form of price discrimination.
• Solve simultaneous and sequential games, and identify commitment and credible threats in a business setting.
• Define a relevant market, compute and interpret concentration measures, and evaluate a merger on a real decision document.
• Explain adverse selection, moral hazard and signaling, and identify them in contracts, labor markets and platforms.
• Evaluate an argument produced by a generative AI model: identify its errors, verify its sources, and correct it.

Course Contents

• Foundations of economic reasoning
• Demand, costs and the firm
• Markets and public policy
• Consolidation, midterm examination and final review
• Market power and pricing
• Strategic interaction
• Information, platforms and the AI economy
• Course project

Assessment Elements

• Attendance
  Attendance is recorded at every seminar and, occasionally, at the lectures. The mark is a step rule applied to the register and requires no individual assessment: 10 out of 10 for attendance at 75% or more, 5 out of 10 for 50–74%, 0 below 50%. The reason of absence does not matter.
• Seminar work
  Some seminars end with a short written artifact produced in the room and handed in — a half-page of analysis, a completed worksheet, or a written decision with its justification. Each is recorded on a three-point scale: 0 absent or the artifact is inadequate, 1 the artifact is somewhat adequate, 2 the artifact is adequate. There is no per-student rubric and no written feedback on individual artifacts; the common errors are addressed in a general communication. The worst score does not count.
• Quizzes
  A problem set is issued through the course of the term. It is neither collected nor graded, and students may prepare it individually, in groups, or with any tool they choose. Some seminars open with a short written activity of two or three questions drawn from the current problem set; which seminars carry one is not announced in advance. The mark is the average of the activities written, and the worst score does not count.
• Midterm exam
  A written examination of 80 minutes, held in place of a lecture in the middle of the course and covering the material up to that point. No new material is presented in that session. It may contain problems that end in a decision rather than a number, and short questions on a case extract: what the market is, where market power lies, and what the student would recommend. It is a rehearsal of the format of the final examination.
• Course project
  Teams of four (five is the maximum) are formed by the instructor early in the course and analyze either a real market or a real competition case, working from at least one primary document — a decision of the European Commission, the CMA or the FAS, a company filing, or price data the team has collected itself. The document must be brought to class and the team must be able to point to the page. The team presents in one of the final seminars; the slides carry no marks. Each student is then asked individual questions based on the team’s case material. The mark is out of 10 and is individual, reflecting the team’s presentation and, principally, the student’s own answers.
• Final exam
  A written examination, invigilated, with no electronic devices. It may contain problems that end in a decision rather than a number; short questions on a case extract — what the market is, where market power lies, what the student would do and what would change that recommendation; and a task requiring the student to find, explain and correct the errors in a page of AI-generated economic analysis. The examination is a blocking element and a mark of at least 4 out of 10 is required to pass the course.

Interim Assessment

• 2026/2027 2nd module
  0.1 * Course project + 0.1 * Seminar work + 0.1 * Attendance + 0.1 * Midterm exam + 0.2 * Quizzes + 0.4 * Final exam

Bibliography

Recommended Core Bibliography

• Третьякова, Е. А. Microeconomics. Collection of Tasks and Cases = Микроэкономика. Сборник задач и кейсов : учебно-методическое пособие / Е. А. Третьякова. — Пермь : ПГНИУ, 2023. — 90 с. — ISBN 978-5-7944-3947-2. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/409724 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.

Recommended Additional Bibliography

• Kolmar, M., & Hoffmann, M. (2018). Workbook for Principles of Microeconomics. Springer.
• Principles of behavioral economics : microeconomics and human behavior, Dhami, S., 2025

Authors