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UID:pretalx-2024-9FSMWY@conferences.acspri.org.au
DTSTART;TZID=AEST:20241129T093000
DTEND;TZID=AEST:20241129T094500
DESCRIPTION:In economics and finance\, many decisions are based on uncertai
 n outcomes. Published economic data\, such as the unemployment rate or GDP
  growth\, are based on estimates that have confidence bands. The uncertain
 ty around the estimates is even larger for forecasts or projections. Most 
 economic data\, actual data\, and forecasts are published as point estimat
 es that lead people to ignore the uncertainty around the estimates. Ignori
 ng these uncertainties leads to worse decisions.\n\nOur paper explores how
  to convey probabilistic information in economics and finance to layperson
 s. We conducted a survey experiment within ANUpoll\, a quarterly survey re
 presentative of the Australian population. ANUpoll is based on Life in Aus
 tralia\, a probability-based panel run by the Social Research Centre. \n\n
 We randomly showed respondents one of four plots: a kernel density plot\, 
 a histogram\, a quantile dot plot with 20 dots\, and a quantile dot plot w
 ith 50 dots. We then asked each of the treatment groups the same four ques
 tions to gauge their understanding of the information conveyed by the plot
 s. Respondents were told what was shown but received no further instructio
 n regarding the interpretation. Each plot summarised the same probability 
 distribution of forecasts of the Australian unemployment rate. We took the
 se forecasts from actual figures published by the Reserve Bank of Australi
 a. When shown the randomly assigned plot for the first time\, respondents 
 were asked to provide their best forecast of the unemployment rate one yea
 r out. We repeatedly reminded respondents to base their estimates on the s
 hown plot.\n\nOur experiment was included in the online questionnaire for 
 January 2024. A good-sized sample of about 4\,000 respondents completed th
 at questionnaire. In addition to the data from the experiment\, we were ab
 le to access rich data from the current and earlier waves of ANUpoll. This
  enabled us to examine how well the four plot types performed and whether 
 this varied by sociodemographic and economic variables. We also found that
  incorporating figures into the online questionnaire was straightforward a
 nd worked quite well. Online surveys should consider doing this more often
 .
DTSTAMP:20260615T195441Z
LOCATION:Sutherland Room
SUMMARY:Communicating Probabilistic Information with Plots: Evidence from a
  Survey Experiment - Markus Hahn
URL:https://conferences.acspri.org.au/2024/talk/9FSMWY/
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