eprintid: 10147361
rev_number: 6
eprint_status: archive
userid: 699
dir: disk0/10/14/73/61
datestamp: 2022-04-26 11:23:42
lastmod: 2022-04-26 11:23:42
status_changed: 2022-04-26 11:23:42
type: article
metadata_visibility: show
sword_depositor: 699
creators_name: Niu, Xiaoxiao
creators_name: Harvey, Nigel
title: Point, interval, and density forecasts: Differences in bias, judgment noise, and overall accuracy
ispublished: inpress
divisions: C05
divisions: F49
divisions: B04
divisions: UCL
divisions: C07
divisions: F67
divisions: B02
divisions: D05
keywords: forecast error, judgment bias, judgment noise, overconfidence, uncertainty
note: © 2022 The Authors. Futures & Foresight Science published by John Wiley & Sons Ltd.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
abstract: There are three main ways in which judgmental predictions are expressed: point forecasts; interval forecasts; probability density forecasts. Do these approaches differ solely in terms of their simplicity of elicitation and the detail they provide? We examined error in values of the central tendency extracted from these three types of forecast in a domain in which all of them are used: lay forecasts of inflation. A first experiment using a between-participant design showed that the mean level of forecasts and the bias in them are unaffected by the type of forecast but that judgment noise (and, hence, overall error) is higher in point forecasts than in interval or density forecasts. A second experiment replicated the difference between point and interval forecasts in a within-participant design (of the sort used in inflation surveys) and showed no effect of the order in which different types of forecast are made but revealed that people are more overconfident in interval than in point forecasts. A third experiment showed that volatility in past data increases bias in point but not interval forecasts, and that taking the average of two point forecasts made by an individual reduces judgment noise to the level found in interval forecasting.
date: 2022-02-21
date_type: published
publisher: Wiley
official_url: https://doi.org/10.1002/ffo2.124
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1950477
doi: 10.1002/ffo2.124
lyricists_name: Niu, Xiaoxiao
lyricists_name: Harvey, Nigel
lyricists_id: XNIUX75
lyricists_id: NJWHA27
actors_name: Flynn, Bernadette
actors_id: BFFLY94
actors_role: owner
full_text_status: public
publication: Futures & Foresight Science
issn: 2573-5152
citation:        Niu, Xiaoxiao;    Harvey, Nigel;      (2022)    Point, interval, and density forecasts: Differences in bias, judgment noise, and overall accuracy.                   Futures & Foresight Science        10.1002/ffo2.124 <https://doi.org/10.1002/ffo2.124>.    (In press).    Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10147361/1/Futures%20%20%20Foresight%20Science%20-%202022%20-%20Niu.pdf