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2014.05.19 - OECD-ECLAC Workshop_Session 1_Greg FISHER

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2014.05.19 - OECD-ECLAC Workshop_Session 1_Greg FISHER

  1. 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. 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. 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 ! 3. Examples of academic - policy interaction ! 4. Questions raised / implications Scope of Talk
  4. 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. 5. Complexity Theory The study of: ! systems containing multiple parts (possibly heterogeneous) that interact with and adapt to each other over time
  6. 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. 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 ! 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. 8. Q: Does Arrow-Debreu capture some underlying essence, which is time and context invariant? ! Complexity theory (and Phil of science) perspective: questionable ! 1. The same context will change over time, unpredictably (non-ergodic) ! 2. Idiosyncrasies: contexts vary, the same essence might not hold in another part of the system Modelling & the Philosophy of Science
  9. 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. 10. I should emphasise: ! • 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. 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. 12. Illustration of complexity in econ & finance - David Tuckett’s work: “Minding the Markets” ! - Interviewed 50 asset managers in 2007 / 8 ! - Interested in how people make decisions under conditions of radical uncertainty ! - Psychoanalytic approach after “orthodox finance didn’t help” ! - Narratives: sense-making & communication
  13. 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.” ! “It looks like a double-dip recession.” ! “We’re in the recovery phase now.”
  14. 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. 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) ! Monetary policy decision making: are narratives accounted for in monetary transmission mechanism (perhaps intuitively / informally?)
  16. 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. 17. - Complexity Science in the Real World x 4 projects ! - Crossrail ! - Ben Ramalingam’s project with DFID ! - Sheri & Doyne’s interactions with policy makers Examples of complexity in policy
  18. 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. 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
  20. 20. Thank you

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