TY  - INPR
TI  - Point, interval, and density forecasts: Differences in bias, judgment noise, and overall accuracy
Y1  - 2022/02/21/
AV  - public
N1  - © 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.
ID  - discovery10147361
N2  - 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.
SN  - 2573-5152
UR  - https://doi.org/10.1002/ffo2.124
PB  - Wiley
JF  - Futures & Foresight Science
KW  - forecast error
KW  -  judgment bias
KW  -  judgment noise
KW  -  overconfidence
KW  -  uncertainty
A1  - Niu, Xiaoxiao
A1  - Harvey, Nigel
ER  -