Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/200699
Authors: 
Mueller, Steffen Q.
Ring, Patrick
Schmidt, Maria
Year of Publication: 
2019
Series/Report no.: 
Hamburg Contemporary Economic Discussions 66
Abstract: 
We investigate various statistical methods for forecasting risky choices and identify important decision predictors. Subjects (n=44) are presented a series of 50/50 gambles that each involves a potential gain and a potential loss, and subjects can choose to either accept or reject a displayed lottery. From this data, we use information on 8800 individual lottery gambles and specify four predictor-sets that include different combinations of input categories: lottery design, socioeconomic characteristics, past gambling behavior, eye-movements, and various psychophysiological measures that are recorded during the first three seconds of lottery-information processing. The results of our forecasting experiment show that choice-process data can effectively be used to forecast risky gambling decisions; however, we find large differences among models' forecasting capabilities with respect to subjects, predictor-sets, and lottery payoff structures.
Subjects: 
Forecasting
lottery
risk
choice-process tracing
experiments
machine learning
decision theory
JEL: 
C44
C45
C53
D87
D91
ISBN: 
978-3-942820-47-9
Document Type: 
Working Paper
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