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Sensitivity to autocorrelation in judgmental time series forecasting

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  • Reimers, Stian
  • Harvey, Nigel

Abstract

How well can people use autocorrelation information when making judgmental forecasts? In Experiment 1, participants forecast from 12 series in which the autocorrelation varied within subjects. The participants showed a sensitivity to the degree of autocorrelation. However, their forecasts indicated that they implicitly assumed positive autocorrelation in uncorrelated time series. Experiments 2 and 2a used a one-shot single-trial between-subjects design and obtained similar results. Experiment 3 investigated the way in which the between-trials context influenced forecasting. The results showed that forecasts are affected by the characteristics of previous series, as well as those of the series from which forecasts are to be made. Our findings can be accommodated within an adaptive approach. Forecasters base their initial expectations of series characteristics on their past experience and modify these expectations in a pseudo-Bayesian manner on the basis of their analysis of those characteristics in the series to be forecast.

Suggested Citation

  • Reimers, Stian & Harvey, Nigel, 2011. "Sensitivity to autocorrelation in judgmental time series forecasting," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1196-1214, October.
  • Handle: RePEc:eee:intfor:v:27:y:2011:i:4:p:1196-1214
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    References listed on IDEAS

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    1. Goodwin, Paul & Wright, George, 1993. "Improving judgmental time series forecasting: A review of the guidance provided by research," International Journal of Forecasting, Elsevier, pages 147-161.
    2. Camerer, Colin F & Hogarth, Robin M, 1999. "The Effects of Financial Incentives in Experiments: A Review and Capital-Labor-Production Framework," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 7-42, December.
    3. repec:bla:joares:v:20:y:1982:i:1:p:68-102 is not listed on IDEAS
    4. Lawrence, Michael & Makridakis, Spyros, 1989. "Factors affecting judgmental forecasts and confidence intervals," Organizational Behavior and Human Decision Processes, Elsevier, vol. 43(2), pages 172-187, April.
    5. Harvey, Nigel & Bolger, Fergus, 1996. "Graphs versus tables: Effects of data presentation format on judgemental forecasting," International Journal of Forecasting, Elsevier, pages 119-137.
    6. Lawrence, Michael & Goodwin, Paul & O'Connor, Marcus & Onkal, Dilek, 2006. "Judgmental forecasting: A review of progress over the last 25 years," International Journal of Forecasting, Elsevier, pages 493-518.
    7. Harvey, Nigel, 1995. "Why Are Judgments Less Consistent in Less Predictable Task Situations?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 63(3), pages 247-263, September.
    8. Collopy, Fred & Armstrong, J. Scott, 1992. "Expert opinions about extrapolation and the mystery of the overlooked discontinuities," International Journal of Forecasting, Elsevier, pages 575-582.
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    Cited by:

    1. Theocharis, Zoe & Harvey, Nigel, 2016. "Order effects in judgmental forecasting," International Journal of Forecasting, Elsevier, pages 44-60.
    2. Meub, Lukas & Proeger, Till & Bizer, Kilian, 2013. "Anchoring: A valid explanation for biased forecasts when rational predictions are easily accessible and well incentivized?," Center for European, Governance and Economic Development Research Discussion Papers 166, University of Goettingen, Department of Economics.
    3. Petropoulos, Fotios & Goodwin, Paul & Fildes, Robert, 2017. "Using a rolling training approach to improve judgmental extrapolations elicited from forecasters with technical knowledge," International Journal of Forecasting, Elsevier, pages 314-324.
    4. repec:eee:intfor:v:33:y:2017:i:3:p:605-617 is not listed on IDEAS
    5. Thomson, Mary E. & Pollock, Andrew C. & Gönül, M. Sinan & Önkal, Dilek, 2013. "Effects of trend strength and direction on performance and consistency in judgmental exchange rate forecasting," International Journal of Forecasting, Elsevier, pages 337-353.
    6. Jalles, João Tovar, 2017. "On the rationality and efficiency of inflation forecasts: Evidence from advanced and emerging market economies," Research in International Business and Finance, Elsevier, pages 175-189.

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