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System economics: Overcoming the pitfalls of forecasting models via a multidisciplinary approach

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  • Orrell, David
  • McSharry, Patrick

Abstract

In areas from medicine to climate change to economics, we are faced with huge challenges and a need for accurate forecasts, yet our ability to predict the future has been found wanting. The basic problem is that complex systems such as the atmosphere or the economy can not be reduced to simple mathematical laws and modeled accordingly. The equations in numerical models are therefore only approximations to reality, and are often highly sensitive to external influences and small changes in parameterisation -- they can be made to fit past data, but are less good at prediction. Since decisions are usually based on our best models of the future, how can we proceed? This paper draws a comparison between two apparently different fields: biology and economics. In biology, drug development is a highly inefficient and expensive process, which in the past has relied heavily on trial and error. Institutions such as pharmaceutical companies and universities are now radically changing their approach and adopting techniques from the new field of systems biology to integrate information from disparate sources and improve the development process. A similar revolution is required in economics if models are to reflect the nature of human economic activity and provide useful tools for policy makers. We outline the main foundations for a theory of systems economics.

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Bibliographic Info

Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 25 (2009)
Issue (Month): 4 (October)
Pages: 734-743

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Handle: RePEc:eee:intfor:v:25:y:2009:i:4:p:734-743

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Web page: http://www.elsevier.com/locate/ijforecast

Related research

Keywords: Uncertainty Decision making Financial markets Systems biology Forecasting practice;

References

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Cited by:
  1. Wright, George & Goodwin, Paul, 2009. "Decision making and planning under low levels of predictability: Enhancing the scenario method," International Journal of Forecasting, Elsevier, vol. 25(4), pages 813-825, October.
  2. Makridakis, Spyros & Taleb, Nassim, 2009. "Decision making and planning under low levels of predictability," International Journal of Forecasting, Elsevier, vol. 25(4), pages 716-733, October.
  3. Roberto Savona & Marika Vezzoli, 2012. "Fitting and Forecasting Sovereign Defaults Using Multiple Risk Signals," Working Papers 2012_26, Department of Economics, University of Venice "Ca' Foscari".
  4. Zanoli, Raffaele & Gambelli, Danilo & Vairo, Daniela, 2012. "Scenarios of the organic food market in Europe," Food Policy, Elsevier, vol. 37(1), pages 41-57.
  5. Olga Kiuila, 2011. "Interactions between trade and environmental policies in the Czech economy," Working Papers 2011-16, Faculty of Economic Sciences, University of Warsaw.
  6. Makridakis, Spyros & Hogarth, Robin M. & Gaba, Anil, 2009. "Forecasting and uncertainty in the economic and business world," International Journal of Forecasting, Elsevier, vol. 25(4), pages 794-812, October.

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