Authors: Andre Lot (University of Sydney, presenting), Thomas de Haan (Univeritetet i Bergen), Paolo Crosetto (INRAE) and Kremena Bachmann (Uni. Zurich and ZHAW)
Abstract: We investigate subjective longevity beliefs in a large sample of the Swiss adult population, using the Click-and-Drag interface, a tool to empower subjects to intuitively submit full belief distributions. We collect data on longevity beliefs on archetypes, on a series of different health scenarios, and for themselves. We implement both a CDF elicitation task -- in line with most of the literature -- and a PDF version for the same task. Our results show that participants estimates elicited with a PDF interface were more accurate than those using the CDF interface. We show additionaly that providing participants with a visual support in the form of an average longevity distribution, substantially helps to improve accuracy and debias estimates. Morover providing visual aid right away clearly outperformed helping after a first unguided estimation. Our findings show the promise of eliciting full distributions, reveal a surprising ourperforming of the PDF over the CDF visualisation, and show that providing visual guidance is a powerful tool for improving longevity predictions.
