Science and modelling in public and commercial policy
This series of events, seminars and research discussions explored questions related to how modelling and scientific evidence is used in policy making. The programme forms part of the Institute of Advanced Study theme for 2015/2016 on Evidence
Organised by Durham Energy Institute in collboration with Global Policy Institute (GPI), Centre for Humanities Engaging Science and Society (CHESS), School of Engineering and Computer Sciences, Mathematical Sciences, and Institute of Advanced Study.
Important questions include:
- How do non-scientists taking decisions based on modelling or scientific insights interpret the modelling results?
- What do they think that modelling or science can and cannot tell them?
- Are the messages which people in one group think they are sending the same as those being received?
- How can modelling and science be used more robustly in the policy process?
The core of the series was a 1 day workshop in early 2016 based around the example of UK energy policy.
Evidence from mathematical modelling and science are increasingly important in the determination of public and commercial policy and strategy. Prominent current examples include:
- climate change adaptation and mitigation (where policy relies on very large scale physical climate models, and has been influenced by economic models e.g. the Stern Report);
- Electricity market reform (where UK government decision making has been heavily influenced by sophisticated microeconomic models);
- High Speed 2 (where the technical modelling was more towards an accounting exercise, but there were important issues of how to treat uncertainty in economic and social background looking decades ahead);
- implications of unsatisfactory use of mathematical modelling in the current financial crisis, e.g. Joseph Stiglitz “These economists provided models - based on unrealistic assumptions of perfect information, perfect competition, and perfect markets - in which regulation was unnecessary”; and
- recent debate over flood defence policy following the extremely wet winter of 13/14 in the South West of England.
More generally, the current practice in the UK government is for policy proposals to be supported by a quantitative Impact Assessment, which often means a large scale modelling study.
A common feature across all these different applications is that the ultimate decision makers do not themselves have a quantitative or science background. One can often divide the participants in the policy process into several layers:
- Modellers and scientists, including both methodological researchers and those who do day-to-day modelling and scientific analysis.
- People who interpret modelling or science for decision makers (e.g. civil servants, academics such as the UK Energy Research Centre).
- High level decision makers, who do not usually have a modelling or quantitative science training.
Workshop on modelling use in UK Energy Policy
This workshop explored the role that quantitative modelling has had in UK energy policy. It explored how modelling has been used to support UK energy policy, how these models are interpreted by policy decision makers and their support teams, and the implications of these processes and structures for energy policy. Ultimately the workshop asked whether there are opportunities for modelling and science to be used more robustly in the policy process.
- Paddy Teahon (Energy Strategy Implementation Consultant at University College Dublin, previously Department of the Taoiseach, Irish Civil Service and Honorary President of the Irish Wind Energy Association) will discuss high level decision making in energy policy
- Duncan Rimmer (Demand & Generation Forecasting Manager, National Grid) will discuss the use of technical modelling in the Electricity Market Reform and UK Energy Scenarios.
- Professor Jim Skea (Chair in Sustainable Energy, Centre for Environmental Policy at Imperial College Research and RCUK Energy Strategy Fellow, formerly Research Director UKERC) will discuss the interpretation of modelling results for policy and decision-making.
Date: 20th January 2016
Location: Senate Suite, Castle, Durham University
Programme: You can view the programme here
A follow-on workshop was hosted at Ofgem in May 2017 lead-sponsored by Supergen Hubnet. It was also supported byDurham Energy Institute, the Centre for Energy Systems Integration, and the Maxwell Institute for Mathematical Sciences (the joint Mathematics Schools of Edinburgh and Heriot-Watt Universities).
You can read the briefing of the issues emerging from the workshops by following the link below: