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When does more mean worse? Accuracy of judgmental forecasting is nonlinearly related to length of data series

Theocharis, Z; Harvey, N; (2019) When does more mean worse? Accuracy of judgmental forecasting is nonlinearly related to length of data series. Omega , 87 pp. 10-19. 10.1016/j.omega.2018.11.009. Green open access

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Abstract

When people make forecasts from series of data, how does their accuracy depend on the length of the series? Previous research has produced highly conflicting findings: some work shows accuracy increases with more data; other research shows that it decreases. In two experiments, we found an inverted U-shaped relation between forecast error and series length for various series containing different patterns and noise levels: error decreased as the length of the series increased from five through 20 to 40 items but also decreased as the series length decreased from five through two to one item. We argue that, with short series, people use a simple heuristic approach to forecasting (e.g., the naïve forecast). With longer series, they extract patterns from the series and extrapolate from them to produce their forecasts. Use of heuristics is poorer but extraction of patterns is better when there are more items in the series. For series of intermediate length, neither type of strategy operates well, thereby producing the inverted U-shaped relation that we observed. Implications for unaided judgmental forecasting and for forecasting based on a combination of judgmental and statistical methods are discussed.

Type: Article
Title: When does more mean worse? Accuracy of judgmental forecasting is nonlinearly related to length of data series
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.omega.2018.11.009
Publisher version: https://doi.org/10.1016/j.omega.2018.11.009
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Judgmental forecasting; Time series; Heuristics; Pattern extraction
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology
URI: https://discovery.ucl.ac.uk/id/eprint/10079027
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