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Merging models and experts

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  • Franses, Philip Hans

Abstract

It is argued that for specific forecast settings there must exist an optimally-sized model with forecasts that only need occasional adjustments by experts. The argument is built on recent evidence on the interaction between models and experts. A consequence of this is that the future research agenda should involve more interaction between researchers in model-based forecasting and those who are engaged in judgemental forecasting research.

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  • Franses, Philip Hans, 2008. "Merging models and experts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 31-33.
    • Handle: RePEc:eee:intfor:v:24:y:2008:i:1:p:31-33
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    7. Franses, Ph.H.B.F. & Kranendonk, H.C. & Lanser, D., 2007. "On the optimality of expert-adjusted forecasts," Econometric Institute Research Papers EI 2007-38, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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    Cited by:

    1. Youssef Boulaksil & Philip Hans Franses, 2009. "Experts' Stated Behavior," Interfaces, INFORMS, vol. 39(2), pages 168-171, April.
      • Boulaksil, Y. & Franses, Ph.H.B.F., 2008. "Experts' Stated Behavior," ERIM Report Series Research in Management ERS-2008-001-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2009. "Expert opinion versus expertise in forecasting," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 334-346, August.
    3. Abolghasemi, Mahdi & Hurley, Jason & Eshragh, Ali & Fahimnia, Behnam, 2020. "Demand forecasting in the presence of systematic events: Cases in capturing sales promotions," International Journal of Production Economics, Elsevier, vol. 230(C).
    4. Arvan, Meysam & Fahimnia, Behnam & Reisi, Mohsen & Siemsen, Enno, 2019. "Integrating human judgement into quantitative forecasting methods: A review," Omega, Elsevier, vol. 86(C), pages 237-252.
    5. Fenfen Wei & Nanping Feng & Kevin H. Zhang, 2017. "Innovation Capability and Innovation Talents: Evidence from China Based on a Quantile Regression Approach," Sustainability, MDPI, vol. 9(7), pages 1-15, July.
    6. Chang, Chia-Lin & Franses, Philip Hans & McAleer, Michael, 2011. "How accurate are government forecasts of economic fundamentals? The case of Taiwan," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1066-1075, October.
    7. Claudio Felisoni de Angelo & Ronaldo Zwicker & Nuno Manoel Martins Dias Fouto & Marcos Roberto Luppe, 2011. "Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecast," Brazilian Business Review, Fucape Business School, vol. 8(2), pages 01-21, April.
    8. Marcel Boumans, 2016. "Methodological institutionalism as a transformation of structural econometrics," Review of Political Economy, Taylor & Francis Journals, vol. 28(3), pages 417-425, July.
    9. Chang, C-L. & Franses, Ph.H.B.F. & McAleer, M.J., 2009. "How Accurate are Government Forecast of Economic Fundamentals?," Econometric Institute Research Papers EI 2009-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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