When Markets Beat the Polls
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Using Prediction Markets to Estimate the Reproducibility of Scientific
Using prediction markets to estimate the SEE COMMENTARY reproducibility of scientific research Anna Drebera,1,2, Thomas Pfeifferb,c,1, Johan Almenbergd, Siri Isakssona, Brad Wilsone, Yiling Chenf, Brian A. Nosekg,h, and Magnus Johannessona aDepartment of Economics, Stockholm School of Economics, SE-113 83 Stockholm, Sweden; bNew Zealand Institute for Advanced Study, Massey University, Auckland 0745, New Zealand; cWissenschaftskolleg zu Berlin–Institute for Advanced Study, D-14193 Berlin, Germany; dSveriges Riksbank, SE-103 37 Stockholm, Sweden; eConsensus Point, Nashville, TN 37203; fJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138; gDepartment of Psychology, University of Virginia, Charlottesville, VA 22904; and hCenter for Open Science, Charlottesville, VA 22903 Edited by Kenneth W. Wachter, University of California, Berkeley, CA, and approved October 6, 2015 (received for review August 17, 2015) Concerns about a lack of reproducibility of statistically significant (14). This problem is exacerbated by publication bias in favor of results have recently been raised in many fields, and it has been speculative findings and against null results (4, 16–19). argued that this lack comes at substantial economic costs. We here Apart from rigorous replication of published studies, which is report the results from prediction markets set up to quantify the often perceived as unattractive and therefore rarely done, there reproducibility of 44 studies published in prominent psychology are no formal mechanisms to identify irreproducible findings. journals and replicated in the Reproducibility Project: Psychology. Thus, it is typically left to the judgment of individual researchers The prediction markets predict the outcomes of the replications to assess the credibility of published results. -
S:\OHP\Tames, George Oral History\Tamespreface.Wpd
George Tames Washington Photographer for the New York Times PREFACE In 1846, an unknown cameraman took the first photograph of the United States Capitol, a view of the East Front. Thereafter the Capitol, from all angles, became the subject of countless amateur and professional photographers. During the nineteenth century and well into the twentieth most photography took place outside the building, due both to its dimly lit interior and to the antipathy many committee chairmen felt about the distractions of flash powder and bulbs. Eventually, photographers moved into the building, shooting everywhere at will, except within the Senate and House chambers. By the 1980s, television cameras penetrated even this haven. Nearly a century after that first photo, George Tames began photographing the people and events of Capitol Hill, first for Time-Life and later for the New York Times. During the course of a long career that ranged from the 1940s through the 1980s, Tames developed access to, and captured the likenesses of more significant members of Congress, and had his work reproduced more widely in influential publications than any other photographer in American political history. He developed a style contrary to the "herd instinct" that led other photographers to group together outside a closed door waiting for a standard shot. Instead, his pictures demonstrate an artistic eye, an intense sense of place, and a special intimacy with his subjects. George Tames was born in the shadow of the Capitol Dome, in a Washington alley house on January 21, 1919, into a Greek-Albanian immigrant family, and "born into the Democratic party" as well. -
Electoral College Reform: Contemporary Issues for Congress
Electoral College Reform: Contemporary Issues for Congress Updated October 6, 2017 Congressional Research Service https://crsreports.congress.gov R43824 Electoral College Reform: Contemporary Issues for Congress Summary The electoral college method of electing the President and Vice President was established in Article II, Section 1 of the Constitution and revised by the Twelfth Amendment. It provides for election of the President and Vice President by electors, commonly referred to as the electoral college. A majority of 270 of the 538 electoral votes is necessary to win. For further information on the modern-day operation of the college system, see CRS Report RL32611, The Electoral College: How It Works in Contemporary Presidential Elections, by Thomas H. Neale. The electoral college has been the subject of criticism and proposals for reform since before 1800. Constitutional and structural criticisms have centered on several of its features: (1) although today all electors are chosen by the voters in the presidential election, it is claimed to be not fully democratic, since it provides indirect election of the President; (2) it can lead to the election of candidates who win the electoral college but fewer popular votes than their opponents, or to contingent election in Congress if no candidate wins an electoral college majority; (3) it results in electoral vote under- and over-representation for some states between censuses; and (4) “faithless” electors can vote for candidates other than those they were elected to support. Legislative and political criticisms include (1) the general ticket system, currently used in all states except Maine and Nebraska, which is alleged to disenfranchise voters who prefer the losing candidates in the states; (2) various asserted “biases” that are alleged to favor different states and groups; and (3) the electoral college “lock,” which has been claimed to provide an electoral college advantage to both major parties at different times. -
Statistical Tests of Real-Money Versus Play- Money Prediction Markets
RESEARCH AbstractStatistical Tests of Real-Money versus Play- Prediction markets are mechanisms that aggregate information such that an esti- Money Prediction Markets mate of the probability of some future event is produced. It has been established that both real-money and play-money prediction E. S. ROSENBLOOM AND WILLIAM NOTZ markets are reasonably accurate. An SPRT- like test is used to determine whether there are statistically significant differences in accuracy between the two markets. The results establish that real-money markets are significantly more accurate for non- sports events. We also examine the effect of volume and whether differences between forecasts are market specific. Keywords: prediction markets, sequential probability ratio test INTRODUCTION eventually use to bid on real prizes. If a participant loses his or her stake of play Prediction markets are mechanisms money, the participant can replenish or that aggregate information such that refill their account back to their original the estimate of the probability of stake. There is considerable evidence some future event is produced. The that such prediction markets, using real probability of some future event money or play money, generate reason- is evoked by contract payoffs; for ably accurate probability forecasts (Berg example, a contract might pay $100 et al. 2000, 2003; Forsythe et al. 1999; if the New England Patriots win the Surowiecki 2004). Super Bowl, or zero if they do not. To date, however, there has only The price at which this contract been one study that examined trades therefore represents the col- directly the question of whether lective consensus of its expected real-money or play-money made value, or the subjective probability any difference in market predictive that the New England Patriot will performance. -
Crowds, Lending, Machine, and Bias
Crowds, Lending, Machine, and Bias Runshan Fu Yan Huang Param Vir Singh Heinz College, Tepper School of Business, Tepper School of Business, Carnegie Mellon University Carnegie Mellon University Carnegie Mellon University [email protected] [email protected] [email protected] Abstract Big data and machine learning (ML) algorithms are key drivers of many fintech innovations. While it may be obvious that replacing humans with machines would increase efficiency, it is not clear whether and where machines can make better decisions than humans. We answer this question in the context of crowd lending, where decisions are traditionally made by a crowd of investors. Using data from Prosper.com, we show that a reasonably sophisticated ML algorithm predicts listing default probability more accurately than crowd investors. The dominance of the machine over the crowd is more pronounced for highly risky listings. We then use the machine to make investment decisions, and find that the machine benefits not only the lenders but also the borrowers. When machine prediction is used to select loans, it leads to a higher rate of return for investors and more funding opportunities for borrowers with few alternative funding options. We also find suggestive evidence that the machine is biased in gender and race even when it does not use gender and race information as input. We propose a general and effective “debiasing” method that can be applied to any prediction focused ML applications, and demonstrate its use in our context. We show that the debiased ML algorithm, which suffers from lower prediction accuracy, still leads to better investment decisions compared with the crowd. -
Incentives in Computer Science Lecture #18: Prediction Markets∗
CS269I: Incentives in Computer Science Lecture #18: Prediction Markets∗ Tim Roughgardeny November 30, 2016 1 Markets for Information 1.1 Uncertain Events Suppose we're interested in an uncertain event, such as whether or not the Warriors will win the 2017 NBA Championship, whether or not the winner of the next Presidential election will be a Republican or a Democrat, or whether or not 2017 will be the hottest year on record. Each of these events is uncertain, but eventually we will know whether or not they occurred. That is, the outcomes of these uncertain events are eventually verifiable. (Similar to the setup for scoring rules in the first half of last lecture, but different from the setup for eliciting subjective opinions in the second half.) What's the best way to predict whether or not such events will happen? For example, suppose you had to predict the winner of a sporting match, despite knowing very little about the sport. You could do a lot worse than turning to the betting markets in Vegas for help. Vegas odds don't let you predict anything with anything close to full certainty, but even the best experts struggle to outperform betting markets with any consistency. For example, favorites cover the Vegas spread about 50% of the time, while underdogs beat the spread about 50% of the time. 1.2 The Iowa Electronic Markets If betting markets work so well for forecasting the outcomes of sporting events, why not use them to also predict other kinds of uncertain events? This is exactly the idea behind the Iowa Electronic Markets (IEM), which have operated since 1988 with the goal of using markets to forecast the outcome of presidential, congressional, and gubernatorial elections. -
Why Obama Probably Can't Win--But Romney Could Still Lose July 24, 2012
Why Obama Probably Can't Win--But Romney Could Still Lose July 24, 2012 G. Terry Madonna & Michael L.Young It’s known as Ockham’s razor. Attributed to 14th-century philosopher William of Ockham, it advocates seeking the simplest explanation necessary to make sense of things. The popular acronym KISS captures its spirit—“keep it simple stupid.” Alas, Ockham’s adage finds few takers today among contemporary electoral analysts. Amid the pundit literati predicting presidential elections, the slogan might be, “seek complexity, lots of it.” This criticism applies particularly to the various and sundry “models” used by the “punditocracy” to predict who will win the next election. These models usually include dozens of variables using arcane statistics to make electoral predictions. Complex and convoluted, they use bazookas to hunt flies when a good, serviceable fly swatter works just as well. But the even more serious problem with some of the presidential predictions models is that they ignore much of the enormous changes in the history of presidential elections since the end of World War II. Not well understood is that American electoral history divides sharply into two very different eras. The first era now largely irrelevant to modern elections ranged from 1800-1945. During this period, one or the other of America’s two major political parties tended to dominate presidential elections, sometimes for decades at a time. From 1800-1856, the Democrats dominated, winning 13 of 15 elections while opposition Whigs won only two. Then from 1860-1928, the Republicans had their turn, winning 18 elections while holding Democrats to just two presidents, each winning two terms. -
Voters Overwhelmingly Positive On
The Harris Poll b For release: Sunday AM, July 17, 1988 1988 W57 ISSN 0895-7983 VOTERS OVERWHELMINGLY POSITIVE ON DUKAKIS NOMINATION: GOVERNOR RATED MORE PCSJTIVELY THAN BUSH ON LEADERSHIP SCALE By Louis Harris As Governor Michael Dukakis prepares for his nomination as the Democratic candidate for President, he is more positively perceived by the voters than nearly any Democrat in many years. For example, a substantial 77-17 percent majority of the voters say they feel positive about his upcoming nomination this week in Atlanta. Even a 66-26 percent majority of Republicans say they are reacting positively to his being named, as does a higher 81 percent of Democrats who left their party four years ago to vote for the President. A just finished Harris Poll, taken by telephone between July 7th and 12th, asked a cross section of 1,252 voters nationwide to rate the two current candidates and Presidents Ronald Reagan, Jimmy Carter, and John F. Kennedy as "leaders," on a scale of 1 to 10, with one the most negative and 10 the most positive. These results reveal how well Dukakis stands on the eve of the Democratic convention: L -- A dramatically high 81-15 percent come up positive on President Kennedy as a leader. -- A substantial 65-34 percent are positive about Ronald Reagan as a leader. -- Close behind Reagan comes Dukakis, rated positively as a leader by a 55-38 percent margin. -- Vice President George Bus\ emerges on this same measurement at 50-47 percent negative. -- Finally, the American people give President Jimmy Carter a 61-37 percent negative rating on his leadership capabilities. -
Crowdsourced Outcome Determination in Prediction Markets
Crowdsourced Outcome Determination in Prediction Markets Rupert Freeman Sebastien´ Lahaie David M. Pennock Duke University Microsoft Research Microsoft Research [email protected] [email protected] [email protected] Abstract to their own stake in the market; this is known as outcome manipulation (Shi, Conitzer, and Guo 2009; Berg and Ri- A prediction market is a useful means of aggregating infor- etz 2006; Chakraborty and Das 2016). Additionally, by al- mation about a future event. To function, the market needs a trusted entity who will verify the true outcome in the end. lowing anyone to create a market, there is no longer any Motivated by the recent introduction of decentralized pre- guarantee that all questions will be sensible, or even have diction markets, we introduce a mechanism that allows for a well-defined outcome. In this paper, we propose a specific the outcome to be determined by the votes of a group of ar- prediction market mechanism with crowdsourced outcome biters who may themselves hold stakes in the market. Despite determination that addresses several challenges faced by de- the potential conflict of interest, we derive conditions under centralized markets of this sort. which we can incentivize arbiters to vote truthfully by us- ing funds raised from market fees to implement a peer pre- First is the issue of outcome ambiguity. At the time the diction mechanism. Finally, we investigate what parameter market closes, it might be unreasonable to assign a binary values could be used in a real-world implementation of our value to the event outcome due to lack of clarity in the out- mechanism. -
All of That Aside, All the History Aside, It Really Is a Place, and I'm Going To
All of that aside, all the history aside, it really is a place, and I’m going to say something that’s going to sound a little bit supercilious, and that is, it’s like Comic-Con, and for those of you out there, students who know what Comic-Con is, it’s just the same thing. It’s a bunch of people, instead of comic books and action figures and movies, it’s politics. It is a massive love, of the process. It’s meeting people who you haven’t seen sometimes in 4, 8, and 12 years. The 1992 Clinton, New York convention, there was a huge party for those of us who worked on Bobby Kennedy’s campaign in ‘68, I hadn’t seen some of those people in 20 years. And both parties, it is an opportunity for people who are in the business of politics in 50 individual states to find one moment in time when they can all come together and basically say, “aren’t we lucky we chose the best business in the world to be in?” People don’t think of conventions as being internal, they think of conventions as being external, because they are external in the sense of sending a message. But they’re also internal, Republicans find other Republicans and they say, “Oh my god, I am right. Look at all the people who agree with me.” Democrats do the same thing. So, there’s a lot of subset things that are going on at these conventions, that aren’t going to be picked up by television and aren’t going to be taught by the teachers. -
Fantasyscotus: Crowdsourcing a Prediction Market for the Supreme Court Josh Blackman Harlan Institute
Northwestern Journal of Technology and Intellectual Property Volume 10 | Issue 3 Article 3 Winter 2012 FantasySCOTUS: Crowdsourcing a Prediction Market for the Supreme Court Josh Blackman Harlan Institute Adam Aft Corey Carpenter Recommended Citation Josh Blackman, Adam Aft, and Corey Carpenter, FantasySCOTUS: Crowdsourcing a Prediction Market for the Supreme Court, 10 Nw. J. Tech. & Intell. Prop. 125 (2012). https://scholarlycommons.law.northwestern.edu/njtip/vol10/iss3/3 This Article is brought to you for free and open access by Northwestern Pritzker School of Law Scholarly Commons. It has been accepted for inclusion in Northwestern Journal of Technology and Intellectual Property by an authorized editor of Northwestern Pritzker School of Law Scholarly Commons. NORTHWESTERN JOURNAL OF TECHNOLOGY AND INTELLECTUAL PROPERTY FantasySCOTUS Crowdsourcing a Prediction Market for the Supreme Court Josh Blackman, Adam Aft and Corey Carpenter January 2012 VOL. 10, NO. 3 © 2012 by Northwestern University School of Law Northwestern Journal of Technology and Intellectual Property Copyright 2012 by Northwestern University School of Law Volume 10, Number 3 (January 2012) Northwestern Journal of Technology and Intellectual Property Fantasy SCOTUS Crowdsourcing a Prediction Market for the Supreme Court By Josh Blackman,* Adam Aft** and Corey Carpenter*** The object of our study, then, is prediction, the prediction of the incidence of the public force through the instrumentality of the courts.1 -Oliver Wendell Holmes, Jr. It is tough to make predictions, especially about the future.2 -Yogi Berra I. INTRODUCTION ¶1 Every year the Supreme Court of the United States captivates the minds and curiosity of millions of Americans—yet the inner-workings of the Court are not fully transparent. -
Speaker Biographies
Speaker Biographies Philip W. Johnston to 2017, Phil served as Chairman of the University Chairman, of Massachusetts Building Authority Board of Massachusetts Directors. He was recently elected Vice Chair of Health Policy Forum the University of Massachusetts Foundation. In 1984, Governor Phil has served on the Board of Directors of Blue Michael S. Dukakis Cross Blue Shield of Massachusetts since 1998. In appointed Phil the 2002, he was appointed to Chair the Board of the Secretary of Health Blue Cross Blue Shield of Massachusetts and Human Services in Massachusetts. As Foundation, which has an endowment of $115 Secretary, he was responsible for the million dollars and provides grants to administration of seventeen state agencies in the Massachusetts nonprofit organizations, which health and human services field, which work in the healthcare field on behalf of low- comprised over fifty percent of the state income citizens. In addition, Phil is the Board budget. Just prior to his appointment as Chair of the Massachusetts Health Policy Forum, Secretary, Phil had begun his fifth consecutive an organization funded by Massachusetts health term as an elected State Representative from the providers and payors, which serves both as a Fourth Plymouth District of Massachusetts. health policy research organization and as a convenor of key players in the health field to In 1991, Phil served as the Executive Director of address key health policy issues confronting the Robert F. Kennedy Human Rights, in Washington, state and the nation. The Forum has a close D.C., an organization established by the Kennedy affiliation with Brandeis University. family to continue to carry on Robert F.