Combining Reference Class Forecasting with Overconfidence Theory for Better Risk Assessment of Transport Infrastructure Investments


  • Steen Leleur Technical University of Denmark
  • Kim Bang Salling Technical University of Denmark
  • Inga Pilkauskiene Rail Net Denmark
  • Morten Skou Nicolaisen Aalborg University



Assessing the risks of infrastructure investments has become a topic of growing importance. This is due to a sad record of implemented projects with cost overruns and demand shortfalls leading, in retrospect, to the finding that there is a need for better risk assessment of transport infrastructure investments. In the last decade progress has been made by dealing with this situation known as planners’ optimism bias. Especially attention can be drawn to the use of reference class forecasting that has led to adjustment factors that, when used on the estimates of costs and demand, lead to cost-benefit analysis results that are modified by taking historical risk experience into account. This article seeks to add to this progress in risk assessment methodology in two ways: first it suggests to apply reference class forecasting (RCF) in a flexible way where the effort is focused on formulating the best possible reference pool of projects and second to apply overconfidence theory (OT) to interpret expert judgments (EJ) about costs and demand as relating to a specific project up for examination. By combining flexible use of RCF with EJ based on OT interpretation it is argued that the current adjustment factor methodology of RCF can be further developed. The latter is among other things made possible by the comprehensive project databases that have been developed in recent years. For this article the project database developed in the UNITE research project 2009-2013 has been employed. The presented simulation-based risk examination named SIMRISK is concluded to provide a new ‘in-depth’ possibility for dealing with uncertainties inherent to transport decision making based on socioeconomic analysis. In addition a further research perspective is outlined.


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How to Cite

Leleur, S., Salling, K. B., Pilkauskiene, I., & Nicolaisen, M. S. (2015). Combining Reference Class Forecasting with Overconfidence Theory for Better Risk Assessment of Transport Infrastructure Investments. European Journal of Transport and Infrastructure Research, 15(3).




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