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From economic crisis to crisis in economics

11 January 2017
by Guest author

Andy Haldane, Chief Economist and Executive Director, Monetary Analysis & Statistics, ​Bank of England

It would be easy to become very depressed at the state of economics in the current environment. Many experts, including economics experts, are simply being ignored. But the economic challenges facing us could not be greater: slowing growth, slowing productivity, the retreat of trade, the retreat of globalisation, high and rising levels of inequality. These are deep and diverse problems facing our societies and we will need deep and diverse frameworks to help understand them and to set policy in response to them. In the pre-crisis environment when things were relatively stable and stationary, our existing frameworks in macroeconomics did a pretty good job of making sense of things.

But the world these days is characterised by features such as discontinuities, tipping points, multiple equilibria, and radical uncertainty. So if we are to make economics interesting and the response to the challenges adequate, we need new frameworks that can capture the complexities of modern societies.

We are seeing increased interest in using complexity theory to make sense of the dynamics of economic and financial systems. For example, epidemiological models have been used to understand and calibrate regulatory capital standards for the largest, most interconnected banks, the so-called “super-spreaders”. Less attention has been placed on using complexity theory to understand the overall architecture of public policy – how the various pieces of the policy jigsaw fit together as a whole in relation to modern economic and financial systems. These systems can be characterised as a complex, adaptive “system of systems”, a nested set of sub-systems, each one itself a complex web. The architecture of a complex system of systems means that policies with varying degrees of magnification are necessary to understand and to moderate fluctuations. It also means that taking account of interactions between these layers is important when gauging risk.

Although there is no generally-accepted definition of complexity, that proposed by Herbert Simon in The Architecture of Complexity – “one made up of a large number of parts that interact in a non-simple way” – captures well its everyday essence. The whole behaves very differently than the sum of its parts. The properties of complex systems typically give rise to irregular, and often highly non-normal, statistical distributions for these systems over time. This manifests itself as much fatter tails than a normal distribution would suggest. In other words, system-wide interactions and feedbacks generate a much higher probability of catastrophic events than Gaussian distributions would imply.

For evolutionary reasons of survival of the fittest, Simon posited that “decomposable” networks were more resilient and hence more likely to proliferate. By decomposable networks, he meant organisational structures which could be partitioned such that the resilience of the system as a whole was not reliant on any one sub-element. This may be a reasonable long-run description of some real-world complex systems, but less suitable as a description of the evolution of socio-economic systems. The efficiency of many of today’s networks relies on their hyper-connectivity. There are, in the language of economics, significantly increasing returns to scale and scope in a network industry. Think of the benefits of global supply chains and global interbank networks for trade and financial risk-sharing. This provides a powerful secular incentive for non-decomposable socio-economic systems.

Moreover, if these hyper-connected networks do face systemic threat, they are often able to adapt in ways which avoid extinction. For example, the risk of social, economic or financial disorder will typically lead to an adaptation of policies to prevent systemic collapse. These adaptive policy responses may preserve otherwise-fragile socio-economic topologies. They may even further encourage the growth of connectivity and complexity of these networks. Policies to support “super-spreader” banks in a crisis for instance may encourage them to become larger and more complex. The combination of network economies and policy responses to failure means socio-economic systems may be less Darwinian, and hence decomposable, than natural and biological systems.

Andy Haldane addresses OECD New Approaches to Economic Challenges (NAEC) Roundtable

 

What public policy implications follow from this complex system of systems perspective? First, it underscores the importance of accurate data and timely mapping of each layer in the system. This is especially important when these layers are themselves complex. Granular data is needed to capture the interactions within and between these complex sub-systems.

Second, modelling of each of these layers, and their interaction with other layers, is likely to be important, both for understanding system risks and dynamics and for calibrating potential policy responses to them.

Third, in controlling these risks, something akin to the Tinbergen Rule is likely to apply: there is likely to be a need for at least as many policy instruments as there are complex sub-components of a system of systems if risk is to be monitored and managed effectively. Put differently, an under-identified complex system of systems is likely to result in a loss of control, both system-wide and for each of the layers.

In the meantime, there is a crisis in economics. For some, it is a threat. For others it is an opportunity to make a great leap forward, as Keynes did in the 1930s. But seizing this opportunity requires first a re-examination of the contours of economics and an exploration of some new pathways. Second, it is important to look at economic systems through a cross-disciplinary lens. Drawing on insights from a range of disciplines, natural as well as social sciences, can provide a different perspective on individual behaviour and system-wide dynamics.

The NAEC initiative does so, and the OECD’s willingness to consider a complexity approach puts the Organisation at the forefront of bringing economic analysis policy-making into the 21st century.

Useful links

This article draws on contributions to the OECD NAEC Roundtable on 14 December 2016; The GLS Shackle Biennial Memorial Lecture on 10 November 2016; and “On microscopes and telescopes”, at the Lorentz centre, Leiden, workshop on socio-economic complexity on 27 March 2015.

The OECD organised a Workshop on Complexity and Policy, 29-30 September, OECD HQ, Paris, along with the European Commission and INET. Watch the webcast: 29/09 morning29/09 afternoon30/09 morning

 

4 Responses leave one →
  1. Godfree Roberts permalink
    January 12, 2017

    Since the Chinese have mastered predictive economics, why don’t we ask them to tell us how they do it? We’re not getting anywhere with our current paradigms.

    • Cade permalink
      January 13, 2017

      How has the Chinese mastry of predictive economics manifested itself? Is the flooding of international markets with excess steel production a calculated outcome or a miscalculation? Do the central planners initiate housing bubbles as a form of stimulus?

  2. Patrick Love permalink*
    January 18, 2017

    From Pr.Velupillai, who contributed this article on Simon and complexity
    Dear Dr. Haldane,
    Your contribution was most impressively and constructively critical and I hope many of the important suggestions – both analytical and conceptual – you outline in it are incorporated into the ‘standard’ macroeconomic outlook and modelling exercises. At least in the sense in which it emphasises the role and place of radical uncertainty, it is of one piece with one of the key building blocks of the ‘ending of alchemy’, advocated by Dr. Mervyn King in his new vision of Macroeconomics (The End of Alchemy: Money, Banking and future of the Global Economy).
    In your important piece you indicate that: “For evolutionary reasons of survival of the fittest, Simon posited that decomposable networks were more resilient and hence more likely to proliferate.” [italics added]
    I would like to point out that Simon, not only ‘for evolutionary reasons of survival of the fittest’, but also for ‘evolutionary dynamic’ (in strict quantifiable and precisely identifiable senses) reasons, postulated not ‘decomposable networks’ [or, ‘systems’ of also, ‘system of systems’) nearly-decomposable systems. The dynamic evolution – in a neo-Darwinian sense – was linked to the causality inherent in hierarchical systems, whose architecture of complexity – according to the wholly ‘practical’ definition he gave of this slippery concept – enabled itself to engineer observably rich nearly-decomposable organizational structures, forever changing, often for the better.
    There were two sources for his reliance and development of such ideas – Richard Goodwin’s introduction of the notion of unilateral coupling (in his 1947, Econometrica paper – a reading of which, by Simon, led him to try to ‘recruit’ Goodwin to CMU) and his own celebrated work with the mathematician David Hawkins. His work on formalizing the evolutionary dynamics of hierarchic systems always emphasized the layers of ‘hierarchy, residing within any global, real-world, observable, entity’ – all the way from his early 1950s response to von Neumann to one of his last formal contributions, in the Raffaele Mattioli Lectures and his posthumous work on parsimony.
    By the way, I was myself taught of the importance of the work of J.B.S. Haldane, by my Cambridge teacher (of eons ago), Richard Goodwin, who – due to a timely conversation with this great scion of Robert the Bruce (according to him), at the home of P.C. Mahalanobis, their common host to Nehru’s India of 1952, developed his own important dynamics of the contours (a word you also use – introduced, first, by Goodwin’s Harvard teacher and friend, Schumpeter) of capitalist market economies via the Lotka-Volterra equations.
    Very many thanks for your fine contribution to the OECD Insights blog.
    Very best wishes,
    Vela Velupillai
    [email protected]

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