MARC Record from Library of Congress

LEADER: 02773cam a22003017a 4500
001 2009655861
003 DLC
005 20100106094203.0
007 cr |||||||||||
008 100104s2009 mau sb 000 0 eng
010 $a 2009655861
040 $aDLC$cDLC
050 00 $aHB1
100 1 $aLevitt, Steven D.
245 10 $aWhat happens in the field stays in the field$h[electronic resource] :$bexploring whether professionals play minimax in laboratory experiments /$cSteven D. Levitt, John A. List, David H. Reiley, Jr..
260 $aCambridge, MA :$bNational Bureau of Economic Research,$cc2009.
490 1 $aNBER working paper series ;$vworking paper 15609
538 $aSystem requirements: Adobe Acrobat Reader.
538 $aMode of access: World Wide Web.
500 $aTitle from PDF file as viewed on 1/4/2010.
530 $aAlso available in print.
504 $aIncludes bibliographical references.
520 3 $a"The minimax argument represents game theory in its most elegant form: simple but with stark predictions. Although some of these predictions have been met with reasonable success in the field, experimental data have generally not provided results close to the theoretical predictions. In a striking study, Palacios-Huerta and Volij (2007) present evidence that potentially resolves this puzzle: both amateur and professional soccer players play nearly exact minimax strategies in laboratory experiments. In this paper, we establish important bounds on these results by examining the behavior of four distinct subject pools: college students, bridge professionals, world-class poker players, who have vast experience with high-stakes randomization in card games, and American professional soccer players. In contrast to Palacios-Huerta and Volij's results, we find little evidence that real-world experience transfers to the lab in these games--indeed, similar to previous experimental results, all four subject pools provide choices that are generally not close to minimax predictions. We use two additional pieces of evidence to explore why professionals do not perform well in the lab: (1) complementary experimental treatments that pit professionals against preprogrammed computers, and (2) post-experiment questionnaires. The most likely explanation is that these professionals are unable to transfer their skills at randomization from the familiar context of the field to the unfamiliar context of the lab"--National Bureau of Economic Research web site.
700 1 $aList, John A.,$d1968-
700 1 $aReiley, David H.
710 2 $aNational Bureau of Economic Research.
830 0 $aWorking paper series (National Bureau of Economic Research : Online) ;$vworking paper no. 15609.
856 40 $uhttp://www.nber.org/papers/w15609