1. Complexity, Public Policy
& Finance
Presentation OECD – ECLAC Workshop on New Tools and
Methods for Policy-Making on 19 May 2014
!
Greg Fisher
Managing Director, Synthesis
greg.fisher@synthesisips.net
2. - Bank of England – 9 Years
- Hedge fund - 4 years
- Chief Economist at ResPublica 2010-11
- Managing Director of Synthesis
- PhD student in Complex Systems Simulation @
Southampton: “Collective Action”
!
Synthesis
- “Think-Tank” set up by myself & Paul Ormerod
in June 2011
- Centred around Complexity in Policy
- Apolitical
My Background
3. 1. Policy makers mostly using non-complex models to
answer complex policy questions
!
2. Example of exclusion from models: David Tuckett’s
work on narratives
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3. Examples of academic - policy interaction
!
4. Questions raised / implications
Scope of Talk
4. “until we gain a better conception of the individual actor within
[policy] settings, which is likely to be a much more complex theory
of the individual, we cannot move ahead as rapidly as we need to.
The entire theoretical structure is likely to be one of complexity
starting with complex models of individual behavior through
complex models of structural interaction.”
!
Elinor Ostrom, 2005
Workshop in Political Theory and Policy Analysis
Indiana University
A Step Back: Collective Action
5. Complexity Theory
The study of:
!
systems containing multiple parts (possibly
heterogeneous)
that interact with
and adapt to
each other
over time
6. 1.Policy makers mostly using non-complex models
to answer complex policy questions
!
2. Example of exclusion from models: David Tuckett’s
work on narratives
!
3. Examples of academic - policy interaction
!
4. Questions raised / implications
Scope of Talk
7. Modelling & the Philosophy of Science
1. Build model to make a point
2. Test it against empirical evidence in some context(s)
3. More empirically consistent models persist & used in
decision-making
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Value of model: depends on its purpose & its context
!
e.g. Arrows-Debreu general equilibrium framework:
useful for understanding how resources are re-allocated
over short periods of time, in a system with given agent
endowments & preferences
8. Q: Does Arrow-Debreu capture some underlying essence,
which is time and context invariant?
!
Complexity theory (and Phil of science) perspective:
questionable
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1. The same context will change over time,
unpredictably (non-ergodic)
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2. Idiosyncrasies: contexts vary, the same essence might
not hold in another part of the system
Modelling & the Philosophy of Science
9. Policy Makers’ Perspective
We have: a collection of non-complex models
e.g. monetary economics, Keynesian theory,
labour market theory, growth theories, etc
…and a policy question
e.g. what should the level of the UK’s official
interest rate be?
Tension: the question terrain is complex, the models
are not
10. I should emphasise:
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• Non-complex models do have value
!
• Plurality is good
What is meant by ‘complex’ here?
Respect for:
(1) networked nature of economy; and
(2) system-wide emergence
11. 1. Policy makers mostly using non-complex models to
answer complex policy questions
!
2.Example of exclusion from models: David
Tuckett’s work on narratives
!
3. Examples of academic - policy interaction
!
4. Questions raised / implications
Scope of Talk
12. Illustration of complexity in econ & finance
- David Tuckett’s work: “Minding the Markets”
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- Interviewed 50 asset managers in 2007 / 8
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- Interested in how people make decisions under
conditions of radical uncertainty
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- Psychoanalytic approach after “orthodox finance
didn’t help”
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- Narratives: sense-making & communication
13. Illustrations of narratives
“The US money markets have frozen, that’s a tipping
point.”
!
“Greece is the first domino, Portugal and Italy will
follow.”
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“It looks like a double-dip recession.”
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“We’re in the recovery phase now.”
14. - People are informationally open systems
- Internal models are coarse-grained (Gell-Mann)
- Social constructivism & Enaction lit’s: we
influence and are influenced by each other
- => narratives (Tuckett) / metaphors (Lakoff &
Johnson) / analogies (Hofstadter & Sander)
- Informal information exchange important in agent
internal models & decision making
Support for the narratives view
15. Implications of narratives view
€ Trillions of capital being allocated in radically
uncertain complex financial markets, subject to
emergence of coarse-grained narratives (versus
utility maximisation in predictable system)
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Monetary policy decision making: are narratives
accounted for in monetary transmission
mechanism (perhaps intuitively / informally?)
16. 1. Policy makers mostly using non-complex models to
answer complex policy questions
!
2. Example of exclusion from models: David Tuckett’s
work on narratives
!
3.Examples of academic - policy interaction
!
4. Questions raised / implications
Scope of Talk
17. - Complexity Science in the Real World x 4 projects
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- Crossrail
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- Ben Ramalingam’s project with DFID
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- Sheri & Doyne’s interactions with policy makers
Examples of complexity in policy
18. 1. Policy makers mostly using non-complex models to
answer complex policy questions
!
2. Example of exclusion from models: David Tuckett’s
work on narratives
!
3. Examples of academic - policy interaction
!
4.Questions raised / implications
Scope of Talk
19. - Do academics think of policy makers as clients?
- Research funds: allocated to ensure research is
sufficiently focused on policy making?
- Do we understand collective action in complex social
systems? (cf Ostrom)
- Finance: should we be allocating society’s capital
though financial markets?
Questions / implications
