ALEXEY KUSHNIR

Associate Professor of Economics
Tepper School of Business
Carnegie Mellon University
Tepper Quad, 5228
412 268 6079, akushnir@andrew.cmu.edu


Teaching


I was fortunate to teach undergraduate-, MBA-, and PhD-level courses at US and European universities. I received the Richard M. Cyert Award for Excellence in the Classroom (2018) at Tepper School of Business that is given annually to a faculty member who is recognized by economics students and the Undergraduate Economics Program Administration for outstanding pedagogy in economics courses, Best Teacher Award (2018) at Higher School of Economics for teaching a machine learning course, and Outstanding Undergraduate Instructor Award (2009) at The Pennsylvania State University for teaching an econometrics course. To learn how to teach with business cases, I took the Harvard Business Publishing Case Method Teaching Seminar (2015) and read several books on the business case teaching method. Below, I briefly outline my past teaching experience. Available copies of teaching evaluation are provided.

Educational statement

Managing Through Incentives (Tepper School of Business, 2022-23)

  • Topics covered: objective and subjective performance measurements, relative performance evaluations, career-based incentives, seniority pay, promotions, skill acquisitions, relational contracts, and executive compensation
  • Course materials: HBS Business Cases, lecture notes, Edward P. Lazear and Michael Gibbs, Personnel Economics in Practice, Wiley, 3rd edition, 2014
  • Audience: MBA students
  • Evaluations: 4.21-5.00 (out of 5.00)
  • Notes: a popular MBA elective class with enrollment of 35 students in 2023

Game Theory Applications for Business and Economics (Carnegie Mellon University, 2021-23)

  • Topics covered: this course is at the introductory level and covers the fundamentals of game theory with particular attention to practical applications in business and economics; static and dynamic games of complete information, static and dynamic games of incomplete information, coalitional game theory.
  • Course materials: Joel Watson (2013). Strategy: An Introduction to Game Theory. Third Edition.
  • Audience: second, third, and fourth-year undergraduate students
  • Evaluations: 4.0-4.67 (out of 5.00)
  • Notes: an undergraduate class of around 35 students

Microeconomics II (Game Theory) (Carnegie Mellon University, 2020-23)

  • Topics covered: This course equips young researchers in Economics and other fields with the core game-theoretic tools on how to model various strategic situations; static and dynamic games of complete information, static and dynamic games of incomplete information, coalitional game theory.
  • Course materials: . D. Fudenberg and J. Tirole, (FT) .Game Theory, MIT Press, 1991.
  • Audience: a first-year PhD-level class
  • Evaluations: n/a
  • Notes: typical class size 10-20 students from various departments

Within the Firm: Managing Through Incentives (Carnegie Mellon University, 2015-2024)

  • Topics covered: objective and subjective performance measurements, relative performance evaluations, career-based incentives, seniority pay, promotions, skill acquisitions, relational contracts, and executive compensation
  • Course materials: HBS Business Cases, lecture notes, Edward P. Lazear and Michael Gibbs, Personnel Economics
    in Practice, Wiley, 3rd edition, 2014
  • Audience: second, third, and fourth-year undergraduate students
  • Evaluations: 4.22-4.88 (out of 5.00)
  • Notes: we discuss 15 business cases during the course

Market Design (Carnegie Mellon University, 2020, 2021)

  • Topics covered: market regulation, matching markets, auctions, the design of market platforms
  • Course materials: paper readings and case studies
  • Audience: second, third, and fourth-year undergraduate students
  • Evaluations: 3.86-4.67 (out of 5.00)
  • Notes: mainly based on non-technical discussions

Machine Learning (Higher School of Economics and New Economics School, 2018)

  • Topics covered: linear regression, linear classification, decision trees, decision forest, bootstrap, bagging, and gradient boosting.
  • Course materials: Bishop C. M. Pattern Recognition and Machine Learning. Springer, 2006
  • Audience: third- and forth-year undergraduate
  • Evaluations: 4.39 (out of 5.00)
  • Notes: the introductory course to machine learning taught to the best undergraduate economics students in Russia; I received the Best Teacher Award for teaching this course.

The Principles of Economics (Carnegie Mellon University, 2015-17)

  • Topics covered: consumers and sellers incentives in markets, market equilibrium, the benefits of trade, externality, and the role of government in the economy, etc.
  • Course materials: Economics, 1st edition, by Acemoglu, Laibson, and List (Pearson Education). ISBN-13: 978-0-133-48774-9
  • Audience: first-year undergraduate
  • Evaluations: 3.98 (2017) (out of 5.00)
  • Notes: two sections with >400 students in total

Economic Foundations of Finance (University of Zurich, 2013)

  • Topics covered: basic concepts of game theory, strategic and extensive form games, Nash equilibrium, elimination of dominated strategies, subgame perfect Nash equilibrium, Bayes-Nash Equilibrium, finance applications
  • Course materials: Mas-Colell, A., M.D. Whinston, and J.R. Green, Microeconomic Theory, 1995, Oxford University Press
  • Audience: Master students with majors in banking and finance
  • Evaluations: N/A
  • Notes: co-taught with Jacob Goeree the first half of the course; Thorsten Hens taught the second half of the course

Mechanism Design (University of Zurich, 2013-14)

  • Topics covered: Bayesian and dominant strategy implementation, envelope theorem, optimal auctions, geometric approach to mechanism design, multi-unit and combinatorial auctions, mechanism design with correlated types and interdependent values, voting, matching theory, financial market design
  • Course materials: the course was mainly based on original articles
  • Audience: Doctoral students
  • Evaluations: 5.00 (out of 5.00) (full evaluations)
  • Notes: co-taught with Jacob Goeree

Microeconomics for Research Students (University of Zurich, 2011-12)

  • Topics covered: fundamental topics of non-cooperative game theory, signaling and screening, principal-agent problem, cooperative game theory, elements of matching theory, elements of mechanism design
  • Course materials: Fudenberg, D. and J. Tirole, Game theory, 1991, MIT Press
  • Audience: Doctoral students
  • Evaluations: 5.88 (out of 6.00) for 2011 (full evaluations), 4.05 (out of 5.00) for 2012 (full evaluations)
  • Notes: a part of a core sequence for PhD student in Department of Economics at University of Zurich; taught both lectures and exercise sections.

Introductory Microeconomic Analysis and Policy (The Pennsylvania State University, 2010)

  • Topics covered: methods and tools of economic analysis, demand and supply, market equilibrium, elasticity, consumer choice, producer choice, general equilibrium, monopoly, public good provision, uncertainty and asymmetric information
  • Course materials: Case, K., R. Fair, and S. Oster, Principles of Microeconomics, 2008, Pearson Prentice Hall, 9th edition
  • Evaluations: N/A
  • Notes: online course 

Introductory Econometrics (The Pennsylvania State University, 2009)

  • Topics covered: simple regression, multivariate linear regression, predictions and errors, hypothesis testing, heteroskedasticity, ordinary and generally least squares models, model selection, instruments, time series, forecasting, panel data
  • Course materials: Wooldridge, J., Introductory Econometrics: A Modern Approach, 2008, Cengage Learning; 4 edition
  • Audience: first year undergraduate students
  • Audience: fourth year undergraduate students
  • Evaluations: 6.22 (out of 7.00) (full evaluations)
  • Notes: the most advanced undergraduate econometrics course; intensive summer course taught each week day during two months; I received the Department of Economics Outstanding Undergraduate Instructor Award for teaching this course; one could also consult the Reference Letter from Dr. Clair Smith, who supervised me during this course.