University of Michigan at Ann Arbor - Department of Economics; The Ford School of Public Policy, University of Michigan; The Brookings Institution; National Bureau of Economic Research (NBER); Institute for the Study of Labor (IZA); Centre for Economic Policy Research (CEPR); CESifo (Center for Economic Studies and Ifo Institute); Kiel Institute for the World Economy
Dartmouth College; NBER
Stanford GSB Research Paper No. 1854
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.
Number of Pages in PDF File: 28
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
Date posted: June 30, 2004
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