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UID:20260427T025710EDT-3170ounf3O@132.216.98.100
DTSTAMP:20260427T065710Z
DESCRIPTION:Abstract: Forecasts about research findings affect critical sci
 entific decisions\, such as what treatments an R&D lab invests in\, or whi
 ch papers a researcher decides to write. But what do we know about the acc
 uracy of these forecasts? We analyze a unique data set of all 100 projects
  posted on the Social Science Prediction Platform from 2020 to 2024\, whic
 h received 53\,298 forecasts in total\, including 66 projects for which we
  also have results. We show that forecasters\, on average\, over-estimate 
 treatment effects\; however\, the average forecast is quite predictive of 
 the actual treatment effect. We also examine differences in accuracy acros
 s forecasters. Academics have a slightly higher accuracy than non-academic
 s\, but expertise in a field does not increase accuracy. A panel of motiva
 ted repeat forecasters has higher accuracy\, but this does not extend more
  broadly to all repeat forecasters. Confidence in the accuracy of one's fo
 recasts is perversely associated with lower accuracy. We also document sub
 stantial cross-study correlation in accuracy among forecasters and identif
 y a group of 'superforecasters'. Finally\, we relate our findings to resul
 ts in the literature as well as to expert forecasts.\n\n \n\nEva Vivalt is
  an Assistant Professor in the Department of Economics at the University o
 f Toronto. Her research explores questions related to development and labo
 ur\, and has studied cash transfers in the U.S.\, the stumbling blocks to 
 evidence-based policy decisions\, including methodological issues\, how ev
 idence is interpreted\, and the use of forecasting.\n\n \n
DTSTART:20260402T163000Z
DTEND:20260402T180000Z
SUMMARY:Forecasting Social Science: Evidence from 100 Projects
URL:/isid/channels/event/forecasting-social-science-ev
 idence-100-projects-372071
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