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Forecasting by Extrapolation: Conclusions from 25 Years of Research

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  • J. Scott Armstrong

    (Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

Abstract

Sophisticated extrapolation techniques have had a negligible payoff for accuracy in forecasting. As a result, major changes are proposed for the allocation of the funds for future research on extrapolation. Meanwhile, simple methods and the combination of forecasts are recommended.

Suggested Citation

  • J. Scott Armstrong, 1984. "Forecasting by Extrapolation: Conclusions from 25 Years of Research," Interfaces, INFORMS, vol. 14(6), pages 52-66, December.
  • Handle: RePEc:inm:orinte:v:14:y:1984:i:6:p:52-66
    DOI: 10.1287/inte.14.6.52
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    1. repec:asg:wpaper:1002 is not listed on IDEAS
    2. Jerzy Witold Wiśniewski, 2021. "Forecasting in Small Business Management," Risks, MDPI, vol. 9(4), pages 1-17, April.
    3. Li, Shuying & Garces, Edwin & Daim, Tugrul, 2019. "Technology forecasting by analogy-based on social network analysis: The case of autonomous vehicles," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    4. Green, Kesten C. & Armstrong, J. Scott, 2015. "Simple versus complex forecasting: The evidence," Journal of Business Research, Elsevier, vol. 68(8), pages 1678-1685.
    5. Arvydas Jadevicius & Brian Sloan & Andrew Brown, 2013. "Property Market Modelling and Forecasting: A Case for Simplicity," ERES eres2013_10, European Real Estate Society (ERES).
    6. Vokurka, Robert J. & Flores, Benito E. & Pearce, Stephen L., 1996. "Automatic feature identification and graphical support in rule-based forecasting: a comparison," International Journal of Forecasting, Elsevier, vol. 12(4), pages 495-512, December.
    7. Kweon, Young-Jun, 2010. "Data-driven reduction targets for a highway safety plan," Transport Policy, Elsevier, vol. 17(4), pages 230-239, August.
    8. JS Armstrong, 2004. "Research on Forecasting: A Quarter-Century Review, 1960-1984," General Economics and Teaching 0412006, University Library of Munich, Germany.
    9. Diamantopoulos, Adamantios & Winklhofer, Heidi, 2003. "Export sales forecasting by UK firms: Technique utilization and impact on forecast accuracy," Journal of Business Research, Elsevier, vol. 56(1), pages 45-54, January.
    10. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
    11. Danese, Pamela & Kalchschmidt, Matteo, 2011. "The impact of forecasting on companies' performance: Analysis in a multivariate setting," International Journal of Production Economics, Elsevier, vol. 133(1), pages 458-469, September.
    12. Huang, Chun-Yao, 2012. "To model, or not to model: Forecasting for customer prioritization," International Journal of Forecasting, Elsevier, vol. 28(2), pages 497-506.
    13. JS Armstrong, 2004. "Forecasting for Environmental Decision Making," General Economics and Teaching 0412023, University Library of Munich, Germany.
    14. Jaganathan, Srihari & Prakash, P.K.S., 2020. "A combination-based forecasting method for the M4-competition," International Journal of Forecasting, Elsevier, vol. 36(1), pages 98-104.
    15. Oesinghaus, Andreas, 2024. "Analysts’ extrapolative expectations in the cross-section," Journal of Economics and Business, Elsevier, vol. 130(C).
    16. Ashish Sood & Gareth M. James & Gerard J. Tellis, 2009. "Functional Regression: A New Model for Predicting Market Penetration of New Products," Marketing Science, INFORMS, vol. 28(1), pages 36-51, 01-02.
    17. Pathak, Pankaj & Srivastava, Rajiv Ranjan & Ojasvi,, 2017. "Assessment of legislation and practices for the sustainable management of waste electrical and electronic equipment in India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 220-232.
    18. Ashish Sood & Gareth M. James & Gerard J. Tellis & Ji Zhu, 2012. "Predicting the Path of Technological Innovation: SAW vs. Moore, Bass, Gompertz, and Kryder," Marketing Science, INFORMS, vol. 31(6), pages 964-979, November.

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