Affecting policy by manipulating prediction markets: Experimental evidence

Cary Deck (), Shengle Lin and David Porter

Journal of Economic Behavior & Organization, 2013, vol. 85, issue C, 48-62

Abstract: Documented results indicate prediction markets effectively aggregate information and form accurate predictions. This has led to a proliferation of markets predicting everything from the results of elections to a company's sales to movie box office receipts. Recent research suggests prediction markets are robust to manipulation attacks and resulting market outcomes improve forecast accuracy. However, we present evidence from the lab indicating that single-minded, well-funded manipulators can in fact destroy a prediction market's ability to aggregate informative prices and mislead those who are making forecasts based upon market predictions. However, we find that manipulators primarily influence market trades meaning outstanding bids and asks remain informative.

Keywords: Information aggregation; Prediction markets; Manipulation (search for similar items in EconPapers)
JEL-codes: C9 D8 G1 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167268112002223
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Affecting Policy by Manipulating Prediction Markets: Experimental Evidence (2010)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jeborg:v:85:y:2013:i:c:p:48-62

DOI: 10.1016/j.jebo.2012.10.017

Access Statistics for this article

Journal of Economic Behavior & Organization is currently edited by Houser, D. and Puzzello, D.

More articles in Journal of Economic Behavior & Organization from Elsevier
Bibliographic data for series maintained by Catherine Liu ().