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Ned Augenblick - Haas School of Business, University of California, Berkeley. Berkeley, CA, US

Ned Augenblick Ned Augenblick

Associate Professor | Haas School of Business, University of California, Berkeley


Areas of Expertise (5)

Behavioral Economics

Economic Analysis

Online Markets




Ned Augenblick is a professor in the Economic Analysis and Policy Group at Berkeley Haas. His focus is behavioral economics, which is the incorporation of psychological insights into economics. Broadly, economics is built on a very useful framework of rational decision-making to make predictions about human behavior. However, in reality, people systematically deviate from this rationality benchmark. By understanding and integrating these deviations into economic models, it is possible to create more accurate predictions and policy recommendations about the world. Augenblick has explored these deviations from rational thinking using theoretical models, experimental data, and empirical environments in settings ranging from online markets to the voting booth to the stock market. This research has published in top journals in economics as well as being discussed in outlets such as the Financial Times, the New York Times, and the Atlantic. For the last eight years, Augenblick has taught the core strategy class to full-time Berkeley MBA students. The class combines the framework of game theory with behavioral economics to understand how executives can make thoughtful decisions that drive sustainable competitive advantage in the marketplace. Prior to teaching strategy, Augenblick taught game theory and statistics. Augenblick studied economics and psychology at Georgetown and mathematics at the University College Dublin, and received his PhD in Economics from Stanford.

Education (3)

Stanford University: PhD, Economics

University College, Dublin: HDip, Mathematical Science

Georgetown University: BA, Economics and Psychology

Honors & Awards (6)

Leonard W. and Shirley R. Ely Dissertation Fellowship

2009 - 2010

George Shultz Fellowship Funding (Swoopo Project)


Centennial TA Award: University-wide Annual Teaching Award


George Shultz Fellowship Funding (Election Project)


John M. Olin Law and Economics Program Fellowship


Outstanding Teaching Assistant Award: Six-time winner

2005 – 2009

Selected External Service & Affiliations (4)

  • American Economic Review, the Quarterly Journal of Economics, the Review of Economic Studies, Journal of Political Economy, American Political Science Review, American Journal of Political Science, Review of Economics and Statistics, American Economic Journal: Microeconomics, the Journal of the European Economic Association, RAND, the Journal of Public Economics, Economic Journal, Economic Inquiry, Management Science, Experimental Economics, Games and Economic Behavior, the Journal of Economics & Management Strategy, Journal of Labor Economics, the Journal of Economic Psychology, Public Choice, Electoral Studies, Review of Industrial Organization, Journal of Institutional and Theoretical Economics, California Management Review, AMMA 2011 (Auctions, Market Mechanisms and their Applications), EC’11 (the ACM conference on Electronic Commerce).
  • Summer Institute in Behavioral Economics, Trento, Italy, 2006
  • Complex Systems Summer School, Santa Fe Institute, 2005
  • Associate Editor: the Review of Economics and Statistics, 2016

Positions Held (1)

At Haas since 2010

2018 – present, Associate Professor, Haas School of Business 2010 – 2018, Assistant Professor, Haas School of Business

Media Appearances (3)

The Plan That Could Give Us Our Lives Back

The Atlantic  online


Mass, high-frequency testing could bring the pandemic to heel while we wait for a vaccine, experts say. Assoc. Professors Jonathan Kolstad and Ned Augenblick have developed a strategy to massively increase COVID-19 testing by efficiently pooling samples with the aid of machine learning. It's being tested at a network of nursing homes near Boston.

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Here’s one way to make daily COVID-19 testing feasible on a mass scale

MIT Technology Review  online


In this op-ed, Jonathan Kolstad, Ned Augenblick, associate professors at Berkeley Haas, and Ziad Obermeyer of the School of Public Health, discuss how pooling tests with the help of machine learning can allow us to safely reopen without a vaccine. Their research found that if we combine machine learning with test pooling, large populations can be tested weekly or even daily, for as low as $3 to $5 per person per day.

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Federal Officials Turn to a New Testing Strategy as Infections Surge

The New York Times  online


The White House has cleared the way for pooled testing for COVID-19, which vastly increases testing capacity by grouping samples together. Assoc. Prof. Jonathan Kolstad and Assoc. Prof. Ned Augenblick, along with Ziad Obermeyer of the School of Public Health and economics PhD student AO Wong, have developed a strategy that combines AI with pooled testing and lowers costs to as little as $3/person per day.

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Selected Papers & Publications (7)

An Experiment on Time Preference and Misprediction in Unpleasant Tasks

Review of Economic Studies

Ned Augenblick and Matthew Rabin


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To Reveal or Not to Reveal: Privacy Preferences and Economic Frictions

Games and Economic Behavior

Ned Augenblick and Aaron Bodoh-Creed


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The Economics of Faith: Using an Apocalyptic Prophecy to Elicit Religious Beliefs in the Field

Journal of Public Economics

Ned Augenblick, Jesse Cunha, Ernesto Dal Bo, and Justin Rao


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Ballot Position, Choice Fatigue, and Voter Behavior

Review of Economics Studies

Ned Augenblick and Scott Nicholson


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The Sunk-Cost Fallacy in Penny Auctions

Review of Economic Studies

Ned Augenblick


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Working Over Time: Dynamic Inconsistency in Real Effort Tasks

The Quarterly Journal of Economics

Ned Augenblick, Muriel Niederle, and Charles Sprenger


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Using Competition to Elicit Cooperation in a Public Goods Game: A Field Experiment

Economic Inquiry

Ned Augenblick and Jesse Cunha


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Teaching (2)


MBA 299

Competitive Game Theory