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Bars, lines and points: The effect of graph format on judgmental forecasting

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  • Reimers, Stian
  • Harvey, Nigel

Abstract

Time series are often presented graphically, and forecasters often judgmentally extrapolate graphically presented data. However, graphs come in many different formats: here, we examine the effect of format when non-experts make forecasts from data presented as bar charts, line graphs, and point graphs. In four web-based experiments with over 4000 participants, we elicited judgmental forecasts for eight points that followed a trended time series containing 50 points. Forecasts were lower for bar charts relative to either line or point graphs. Factors potentially affecting these format effects were investigated: We found that the intensity of shading had no effect on forecasts and that using horizontal stepped lines led to higher forecasts than bars. We also found that participants added more noise to their forecasts for bars than for points, leading to worse performance overall. These findings suggest that format significantly influences judgmental time series forecasts.

Suggested Citation

  • Reimers, Stian & Harvey, Nigel, 2024. "Bars, lines and points: The effect of graph format on judgmental forecasting," International Journal of Forecasting, Elsevier, vol. 40(1), pages 44-61.
    • Handle: RePEc:eee:intfor:v:40:y:2024:i:1:p:44-61
    DOI: 10.1016/j.ijforecast.2022.11.003
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    References listed on IDEAS

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