Research Interests: applied econometrics, game theory, industrial organization, numerical methods
Ulrich Doraszelski is the Joseph J. Aresty Professor and Professor of Business Economics and Public Policy at the Wharton School at the University of Pennsylvania. He is also a Professor of Economics at the School of Arts and Sciences and a Professor of Marketing at the Wharton School. He received his Ph.D. in Economics from Northwestern University in 2001. Professor Doraszelski has previously been a visiting scholar at the Hoover Institution at Stanford University and a faculty member of the Department of Economics at Harvard University. He currently serves as Associate Editor for Operations Research, Quantitative Economics, and the Rand Journal of Economics. He previously served as Co-Editor for the International Journal of Industrial Organization.
Professor Doraszelski’s research identifies and explains the long-run impact of firms’ strategic decisions on the evolution of an industry. Many decisions such as investments in capacity and research and development are long-lived and affect both current and future profitability. They also have profound consequences for the competitive position of a firm vis-a-vis its rivals and shape the structure of the industry. These changes in industry structure in turn affect the future decisions of firms. Professor Doraszelski’s overarching research interest is to investigate, both theoretically and empirically, this two-way link between firms’ strategic decisions and the evolution of the industry over time.
Professor Doraszelski’s research has been published in leading academic journals including the American Economic Review, Econometrica, the Journal of Political Economy, the Rand Journal of Economics, and the Review of Economic Studies. Professor Doraszelski is the recipient of numerous grants from the National Science Foundation. He was a National Fellow at the Hoover Institution at Stanford University from 2006 to 2007.
Ulrich Doraszelski, Joseph Harrington, Mark Satterthwaite (Work In Progress), Can Collusion Be Sustained Under Demand Uncertainty and Entry and Exit?.
Bryan Bollinger, Ulrich Doraszelski, Kenneth Judd (Work In Progress), Spatial Competition in Growing Markets: A Dynamic Model of Entry.
David Besanko, Ulrich Doraszelski, Yaroslav Kryukov (Working), How Efficient is Dynamic Competition? The Case of Price as Investment.
Ulrich Doraszelski, Gregory Lewis, Ariel Pakes (2017), Just starting out: Learning and equilibrium in a new market, American Economic Review, forthcoming.
Juan Escobar and Ulrich Doraszelski (Working), Protocol Invariance and the Timing of Decisions in Dynamic Games.
Abstract: We explore the sensitivity of the U.S. government's ongoing incentive auction to multi-license ownership by broadcasters. We document significant broadcast TV license purchases by private equity firms prior to the auction and perform a prospective analysis of the effect of ownership concentration on auction outcomes. We find that multi-license holders are able to raise spectrum acquisition costs by 22% by strategically withholding some of their licenses to increase the price for their remaining licenses. A proposed remedy reduces the distortion in payouts to license holders by up to 80%, but lower participation could greatly increase payouts and exacerbate strategic effects.
Ulrich Doraszelski and Jordi Jaumandreu (2016), Measuring the Bias of Technological Change, Journal of Political Economy, (Forthcoming).
David Besanko, Ulrich Doraszelski, Yaroslav Kryukov (2014), The Economics of Predation: What Drives Pricing When There Is Learning-by-Doing?, American Economic Review, 104 (3), pp. 868-897.
David Besanko, Ulrich Doraszelski, Yaroslav Kryukov (Working), Sacrifice tests for predation in a dynamic pricing model: Ordover & Willig (1981) and Cabral & Riordan (1997) meet Ericson & Pakes (1995).
Ulrich Doraszelski and Jordi Jaumandreu (2013), R&D and Productivity: Estimating Endogenous Productivity, Review of Economic Studies, 80, pp. 1338-1383.
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 compared 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 determin what is best 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.
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.
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.
Owners of multiple TV stations can strategically bid to hike payouts by billions of dollars in the FCC’s upcoming spectrum incentive auction. But there is a partial remedy, Wharton experts say.Knowledge @ Wharton - 2016/03/21