This is an edited version of a post on pancrit.org commenting on the public letter advocating safe harbor for small-scale academic prediction markets. I can see why they limited their goals as they did, and I agree that everything they advocated should be legal, but I think they may have limited their objectives just enough to prevent any big wins.

One thing that Chris Masse seems to constantly argue is that Prediction Markets on dry subjects need to be accompanied by entertaining questions in order to to keep the audience&#8217-s attention. The economists had good reasons for shying away from recommending that sports betting should be included, but there are many other topics that diverse markets could include that give traders a reason to check back in. The range from the obvious entertainment questions (movie earnings and oscar winners) to legislative outcomes (bills passing and control of particular legislative bodies) and introduction and market success of new technologies. While these kinds of questions might be out of place on some single-topic markets modeled after the University of Iowa&#8217-s markets on elections, the internal corporate markets that they also mentioned often use them to help maintain interest. The letter&#8217-s recommendations that the CFTC &#8220-allow contracts that price an economically meaningful risk or uncertainty&#8221- unnecessarily limits the kinds of contracts that would be allowed.

Back on the side of supporting the letter&#8217-s authors again, I&#8217-d have to admit that if the CFTC or Congress acts to implement anything resembling the recommendation it would very likely increase Prediction Market activity greatly, and eventually lead to a broader acceptance. If the initial definition is too narrow, however, questions that don&#8217-t have clear economic implications (in the view of Congress and the regulators) might be stuck offshore for a long time to come.

Statement on Prediction Markets – (Click here to read the abstract and download the petition from the SSRN site) – by Kenneth J. Arrow, Robert Forsythe, Michael Gorham, Robert Hahn, Robin Hanson, Daniel Kahneman, John O. Ledyard, Saul Levmore, Robert Litan, Paul Milgrom, Forrest D. Nelson, George R. Neumann, Charles R. Plott, Thomas C. Schelling, Robert J. Shiller, Vernon L. Smith, Erik Snowberg, Cass R. Sunstein, Paul C. Tetlock, Philip E. Tetlock, Hal R. Varian, Marco Ottaviani, Justin Wolfers, and Eric Zitzewitz – 2007-05-XX

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Executive Summary

Prediction markets are markets for contracts that yield payments based on the outcome of an uncertain future event, such as a presidential election. Using these markets as forecasting tools could substantially improve decision making in the private and public sectors. We argue that U.S. regulators should lower barriers to the creation and design of prediction markets by creating a safe harbor for certain types of small stakes markets. We believe our proposed change has the potential to stimulate innovation in the design and use of prediction markets throughout the economy, and in the process to provide information that will benefit the private sector and government alike.

Introduction

Prediction markets are markets for contracts that yield payments based on the outcome of an uncertain future event, such as a presidential election, the release date for new software, or the action taken by the Federal Reserve on short-term interest rates. A key benefit is that the market price of these contracts can potentially provide more accurate forecasts of future events than other methods. Using these markets as forecasting tools could substantially improve decision making in the private and public sectors. They also can help manage risk more efficiently. It is precisely because prediction markets have great potential that we think the government should facilitate rather than hinder the introduction of these markets.

There are significant regulatory barriers to establishing prediction markets in the United States, in part because they are potentially subject to gambling laws. We argue that U.S. regulators should lower barriers to the creation and design of prediction markets by creating a safe harbor for certain types of small stakes markets. We believe our proposed change has the potential to stimulate innovation in the design and use of prediction markets throughout the economy, and in the process to provide information that will benefit the private sector and government alike.

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Conclusion

We believe prediction markets can significantly improve decision making in both the private and public sectors. One of the clear benefits of allowing small stakes, non-profit markets to operate would be the greater use of prediction markets to inform both public and private decision making. A second benefit would be that access to better information could promote greater transparency and accountability in decision making. A third benefit might be that other countries and regions would promote prediction markets with more sensible regulation. Finally, we think there would be benefits from the development of new knowledge on how to design prediction markets.

We are aware that Congress did not intend the CFTC to regulate gambling and we believe that it is important to design this safe harbor in such a fashion that socially valuable prediction markets can get in, but gambling markets cannot.

Prediction markets have great potential for improving economic welfare and the decisions of private and public institutions alike. To help achieve that potential, the regulatory impediments to the use of prediction markets in the U.S. should be lowered. Here, we have suggested one approach for reducing those regulatory barriers.

AEI-Brookings Joint Center – The views in this paper represent those of the authors and do not necessarily represent the views of the institutions with which they are affiliated.

Kenneth J. Arrow – Stanford University

Robert Forsythe – University of South Florida

Michael Gorham – Illinois Institute of Technology

Robert Hahn – AEI-Brookings Joint Center

Robin Hanson – George Mason University

Daniel Kahneman – Princeton University

John O. Ledyard – California Institute of Technology

Saul Levmore – University of Chicago

Robert Litan – AEI-Brookings Joint Center

Paul Milgrom – Stanford University

Forrest D. Nelson – University of Iowa

George R. Neumann – University of Iowa

Charles R. Plott – California Institute of Technology

Thomas C. Schelling – University of Maryland

Robert J. Shiller – Yale University

Vernon L. Smith – George Mason University

Erik Snowberg – Stanford University

Cass R. Sunstein – University of Chicago

Paul C. Tetlock – University of Texas at Austin

Philip E. Tetlock – University of California at Berkeley

Hal R. Varian – University of California at Berkeley

Marco Ottaviani – London Business School

Justin Wolfers – University of Pennsylvania

Eric Zitzewitz – Stanford University

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