Building on the Institute's recent System Stewardship working paper, this event on the future of policy making explored how thinking about behavioural economics, networks and complexity can help policy makers cope with new and pressing challenges.
Eric Beinhocker is a senior fellow at the McKinsey Global Institute, author of The Origin of Wealth, and an advisor to the Institute for New Economic Thinking (INET).
Eric Beinhocker argued that policy makers require economic models that accurately describe the real world.
Neo-classical theory, heavily influenced by mathematical thinking, has long formed the foundation of thought in the economic world. But it is characterised by equilibria and as such fails to explain such crucial and observable facts as explosive (rather than linear) growth in wealth, as well as increasing complexity and novelty. Similarly, it neglects interactions with the physical environment.
"Complexity economics" can provide a more credible worldview by accounting for the ‘emergent behaviour' of individual agents, which are shaped through interactions both with each other and their environment. This way of thinking could transform the way we tackle problems such as financial system reform and growth policy.
Complexity economics brings together fields such as engineering and biology, which also seek to analyse complex adaptive systems. It views the economy as an evolutionary system, where change is driven by adaptation, selection, and amplification.
The evolutionary process of ‘deductive tinkering' can be identified in central sectors of the economy: physical technologies (like bicycle design); social technologies, such as legal frameworks and production lines; and the institutional design of firms. Thus, the evolutionary process can be found at all economic levels: individuals, organisations, and markets.
Taking a complexity approach had significant potential implications for policy making, such as new methods of modelling and analysis to re-shape policy making discussions. Agent-based modelling, for instance, aggregates real data to calibrate models of how agents interact in complex ways and shape emergent behaviours. This technique has been used to better understand such scenarios as hospital emergency rooms, including details such as staffing levels, equipment availability, and geographical layout.
Adopting an experimental approach is crucial. The role of policy making may not to be the optimal designer (we can't design optimal policies without trial and error), but to develop a framework within which policy evolves and adapts. The Institute for Government's recent System Stewardship report shows how the government can adopt such an approach in practice. A system stewardship approach, however, raises the political conundrum of whether policy makers can admit to not knowing the optimal way to solve a problem without losing legitimacy.
- Listen to a podcast of this event (MP3, 1h:24m 48MB) Please note that this recording has been edited due to issues with the sound quality
- Watch the video on You Tube Please note that there are areas of poor quality sound in this video.