Ulrich Doraszelski

• Ulrich Doraszelski, Joseph Harrington, Mark Satterthwaite (Work In Progress), Can Collusion Be Sustained Under Demand Uncertainty and Entry and Exit?.
• Ulrich Doraszelski and Lixiong Li (Working), Production Function Estimation without Invertibility: Imperfectly Competitive Environments and Demand Shocks. Abstract

  We advance the proxy variable approach to production function estimation. We show that the invertibility assumption at its heart is testable. We characterize what goes wrong if invertibility fails and what can still be done. We show that rethinking how the estimation procedure is implemented either eliminates or mitigates the bias that arises if invertibility fails. Furthermore, we show how a modification of the procedure ensures Neyman orthogonality, enhancing efficiency and robustness by rendering the asymptotic distribution of the GMM estimator in the second step of the estimation procedure invariant to estimation noise from the first step.

• Ulrich Doraszelski (2025), “Ownership Concentration and Strategic Supply Reduction,” with Katja Seim, Michael Sinkinson, and Peichun Wang, American Economic Review, Vol. 115, No. 3, 2025, pp. 903-944, .
• Bryan Bollinger, Ulrich Doraszelski, Kenneth Judd, Ryan McDevitt (2024), The Timing and Location of Entry in Growing Markets: Subgame Perfection at Work, , Rand Journal of Economics, 55 (2), pp. 169-198.
• Ulrich Doraszelski, Joao F. Gomes, Felix Nockher, Oligopoly dynamics with Financing Frictions.
• Ulrich Doraszelski and Jordi Jaumandreu, Reexamining the De Loecker & Warzynski (2012) method for estimating markups.
• David Besanko, Ulrich Doraszelski, Yaroslav Kryukov (2020), Sacrifice tests for predation in a dynamic pricing model: Ordover & Willig (1981) and Cabral & Riordan (1997) meet Ericson & Pakes (1995), International Journal of Industrial Organization , 70 (), pp. 1-20.
• David Besanko, Ulrich Doraszelski, Yaroslav Kryukov (2019), How Efficient is Dynamic Competition? The Case of Price as Investment, American Economic Review , 109 (9), pp. 3339-3364. Related
  Files

  Online Appendix
• Ulrich Doraszelski and Jordi Jaumandreu (Working), Using Cost Minimization to Estimate Markups.
• Juan Escobar and Ulrich Doraszelski (2019), Protocol Invariance and the Timing of Decisions in Dynamic Games, Theoretical Economics, 14 (), pp. 597-646.
• All Research from Ulrich Doraszelski »

Past Courses

• BEPP2500 - Managerial Economics

  This course will introduce you to "managerial economics" which is the application of microeconomic theory to managerial decision-making. Microeconomic theory is a remarkably useful body of ideas for understanding and analyzing the behavior of individuals and firms in a variety of economic settings. The goal of the course is for you to understand this body of theory well enough so that you can effectively analyze managerial (and other) problems in an economic framework. While this is a "tools" course, we will cover many real-world applications, particularly business applications, so that you can witness the usefulness of these tools and acquire the skills to use them yourself. We will depart from the usual microeconomic theory course by giving more emphasis to prescription: What should a manager do in order to achieve some objective? That course deliverable is to compare with description: Why do firms and consumers act the way they do? The latter will still be quite prominent in this course because only by understanding how other firms and customers behave can a manager determine what is beswt for him or her to do. Strategic interaction is explored both in product markets and auctions. Finally, the challenges created by asymmetric information - both in the market and within the firm - are investigated.

• BEPP9110 - Empirical Public Policy

  This course examines econometric research on a variety of topics related to public policy, with the goal of preparing students to undertake academic-caliber research. The course is not an econometrics or statistics course per se; rather, it focuses on research designs with observational data and how econometric techniques are applied in practice. The course aims to train students to do applied economic research that involves measuring effects of theoretical or practical interest. It proceeds in two major parts. The first part examines endogeneity and inference about causal relationships, instrumental variables methods and critiques, and panel data methods. The second part of the course addresses 'structural' econometric modeling. Topics covered in this part include sorting and selection, entry models, and counterfactual analyses of policy changes. The course proceeds by analyzing, in detail, approximately 24 well-known empirical research papers in applied economics or related fields. These include public economics and tax policy, labor economics, law and economics, health care policy, industrial organization and competition, transportation demand and policy, and others.

• BEPP9310 - Numerical Methods in Eco

  The objective of this course is to introduce graduate students to computational approaches for solving economic models. We will formulate economic problems in computationally tractable form and use techniques from numerical analysis to solve them. Examples of computational techniques in the current economics literature as well as discuss areas where these techniques may be useful in future research will be disclosed. We will pay particular attention to methods for solving dynamic optimization problems and computing equilibria of games. The substantive applications will cover a wide range of problems including industrial organization, game theory, macroecomics, finance, and econometrics.

• BEPP9500 - Managerial Economics

  Public goods, externalities, uncertainty, and income redistribution as sources of market failures; private market and collective choice models as possible correcting mechanisms. Microeconomic theories of taxation and public sector expenditures. The administration and organization of the public sector.

• Dean's Research Fund, Wharton School, University of Pennsylvania, 2010, 2015, 2019 and 2020, 2020
• NFS Grant No. SES-0924380, "Collaborative Research: Measuring the Bias of Technological Change," with Jordi Jaumandreu, 2009
• Clark Fund, Harvard University, 2004 and, 2008
• NSF Grant No. SES-0617896, "Economic Impacts of Technological Innovations in Product Availability," with Julie Mortimer, 2006
• NSF Grant No. SES-0615615, "Collaborative Research on Dynamic Antitrust Policy: Predatory and Limit Pricing in a Model of Learning-by-Doing and Organizational Forgetting," with David Besanko, 2006
• EARIE Young Economists' Essay Award, 2002
• Dissertation Research Fellowship, Center for the Study of Industrial Organization, Northwestern University, 2000
• University Fellowship, Northwestern University, 1999
• Best Graduate Award, Humboldt-Universitat zu Berlin, 1996
• NSF Grant No. SES-20117068, "Dynamic Strategic Corporate Finance", with Joao Gomes, 1970
• Rodney L. White Center for Financial Research Grant, Wharton School, University of Pennsylvania, 1970

Knowledge @ Wharton

• Markets Brace for Tariffs and Look to AI for Relief, Knowledge @ Wharton - 06/27/2025
• The New Science of Pitching and Hitting With Travis Sawchik, Knowledge @ Wharton - 06/25/2025
• How AI Is Reshaping Customer Experience and Expectations, Knowledge @ Wharton - 06/25/2025
• How Private Equity Firms Are Coping With Tariffs, Knowledge @ Wharton - 06/24/2025
• The AI Efficiency Trap: When Productivity Tools Create Perpetual Pressure, Knowledge @ Wharton - 06/24/2025
• What’s the Best Strategy to Grow Your Business?, Knowledge @ Wharton - 06/24/2025
• Private Finance, Public Power | Peter Conti-Brown, Knowledge @ Wharton - 06/24/2025
• How Tariffs Are Disrupting Retail and Consumer Confidence, Knowledge @ Wharton - 06/20/2025
• Recapping the U.S. Open With Daniel Rapaport, Knowledge @ Wharton - 06/18/2025
• From Amateurism to Paychecks: College Athletics in Transition, Knowledge @ Wharton - 06/18/2025