Prediction Markets

Stanford GSB Research Paper No. 1854

28 Pages Posted: 30 Jun 2004

See all articles by Justin Wolfers

Justin Wolfers

University of Michigan at Ann Arbor - Department of Economics; University of Michigan at Ann Arbor - Gerald R. Ford School of Public Policy; The University of Sydney - Discipline of Economics; Brookings Institution - Economic Studies Program; Peter G. Peterson Institute for International Economics; National Bureau of Economic Research (NBER); IZA Institute of Labor Economics; Centre for Economic Policy Research (CEPR); CESifo (Center for Economic Studies and Ifo Institute); Kiel Institute for the World Economy

Eric Zitzewitz

Dartmouth College; NBER

Multiple version iconThere are 2 versions of this paper

Date Written: April 2004

Abstract

We analyze the extent to which simple markets can be used to aggregate disperse information into efficient forecasts of uncertain future events. Drawing together data from a range of prediction contexts, we show that market-generated forecasts are typically fairly accurate, and that they outperform most moderately sophisticated benchmarks. Carefully designed contracts can yield insight into the market's expectations about probabilities, means and medians, and also uncertainty about these parameters. Moreover, conditional markets can effectively reveal the market's beliefs about regression coefficients, although we still have the usual problem of disentangling correlation from causation. We discuss a number of market design issues and highlight domains in which prediction markets are most likely to be useful.

Keywords: Idea futures, forecasting, economic policy, information markets, prediction markets, policy evaluation, macroeconomics, microeconomics, public policy

JEL Classification: D7, D8, E3, E6, G1, H8, Q4

Suggested Citation

Wolfers, Justin and Zitzewitz, Eric W., Prediction Markets (April 2004). Stanford GSB Research Paper No. 1854. Available at SSRN: https://ssrn.com/abstract=560070 or http://dx.doi.org/10.2139/ssrn.560070

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