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Distributed investment decisions and forecasting errors: An analysis based on a multi-agent simulation model

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  • Leitner, Stephan
  • Rausch, Alexandra
  • Behrens, Doris A.

Abstract

This paper analyzes the impact of both non-systematic and systematic forecasting errors on the coordination of distributed investment decisions. The forecasts of concern pertain to the expected cash outlay necessary to launch and operate an investment project, to the expected cash flows generated by the project’s operation, and to the self-assessment of whether or not the abilities expected to be needed for operation coincide with one’s own. Systematic forecasting errors manifested by systematically over- or underestimating these predicted project indicators are interpreted as being produced by overconfidence. Utilizing a multi-agent simulation approach, we show that within a hierarchical business organization with distributed authorities for decision making, in some cases being overconfident can mitigate the negative effect of erroneous forecasting compared to being non-systematically wrong.

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  • Leitner, Stephan & Rausch, Alexandra & Behrens, Doris A., 2017. "Distributed investment decisions and forecasting errors: An analysis based on a multi-agent simulation model," European Journal of Operational Research, Elsevier, vol. 258(1), pages 279-294.
    • Handle: RePEc:eee:ejores:v:258:y:2017:i:1:p:279-294
    DOI: 10.1016/j.ejor.2016.08.042
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    Cited by:

    1. Darío Blanco-Fernández & Stephan Leitner & Alexandra Rausch, 2023. "Interactions between the individual and the group level in organizations: The case of learning and group turnover," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(4), pages 1087-1128, December.
    2. Emanuele Borgonovo & Marco Pangallo & Jan Rivkin & Leonardo Rizzo & Nicolaj Siggelkow, 2022. "Sensitivity analysis of agent-based models: a new protocol," Computational and Mathematical Organization Theory, Springer, vol. 28(1), pages 52-94, March.
    3. Loretta Mastroeni & Maurizio Naldi & Pierluigi Vellucci, 2023. "Personal Finance Decisions with Untruthful Advisors: An Agent-Based Model," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1477-1522, April.
    4. Patrick Reinwald & Stephan Leitner & Friederike Wall, 2021. "Limited intelligence and performance-based compensation: An agent-based model of the hidden action problem," Papers 2107.03764, arXiv.org.
    5. Dario Blanco-Fernandez & Stephan Leitner & Alexandra Rausch, 2022. "Interactions between the individual and the group level in organizations: The case of learning and autonomous group adaptation," Papers 2203.09162, arXiv.org.
    6. Manouchehrabadi, Behrang & Letizia, Paolo & Hendrikse, George, 2022. "Democratic versus elite governance for project selection decisions in executive committees," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1126-1138.

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