The Wisdom of the Crowd and Prediction Markets

86 Pages Posted: 16 Jun 2020

See all articles by Min Dai

Min Dai

The Hong Kong Polytechnic University

Yanwei Jia

Columbia University - Department of Industrial Engineering and Operations Research

Steven Kou

Boston University

Date Written: May 14, 2020

Abstract

Thanks to digital innovation, the wisdom of the crowd, which aims at gathering information (e.g. Wikipedia) and making a prediction (e.g. using prediction markets) from a group's aggregated inputs, has been widely appreciated. An innovative survey design, based on a Bayesian learning framework, called the Bayesian truth serum (BTS), was proposed previously to reduce the bias in the simple majority rule by asking additional survey questions. A natural question is whether we can extend the BTS framework to prediction markets (not just polls). To do so, this paper proposes two estimators, one based on a prediction market alone and the other based on both the market and a poll question. We show that both estimators are consistent within the BTS framework, under different sets of regularity conditions. Simulations are conducted to examine the convergence of different estimators. A real data set of sports betting is used to demonstrate the effectiveness of one estimator.

Keywords: prediction markets, public opinion polls, information aggregation

JEL Classification: C58, C11

Suggested Citation

Dai, Min and Jia, Yanwei and Kou, Steven, The Wisdom of the Crowd and Prediction Markets (May 14, 2020). Journal of Econometrics, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3606851

Min Dai

The Hong Kong Polytechnic University ( email )

Yanwei Jia (Contact Author)

Columbia University - Department of Industrial Engineering and Operations Research ( email )

500 W. 120th Street #315
New York, NY 10027
United States

Steven Kou

Boston University ( email )

595 Commonwealth Avenue
Boston, MA 02215
United States
6173583318 (Phone)

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