1. Socio-Economic Complexity Workshop Leiden 27 March 2015 Andrew G Haldane On Microscopes and Telescopes

2. The story so far … 2 Biggest crisis since the 1930s Existing models no use in explaining it – before, during or after Existing policies ineffective in preventing it Network/complexity models have risen in prominence Complexity language enters regulatory lexicon – tipping points, contagion cascades etc New regulatory architecture put in place Eg, “too big to fail” and capital surcharges for “superspreader” banks

3. Forecasting GDP Growth 3

4. The Macro-Financial Policy Architecture 4 Old Micro- Prudential Monetary Policy Global Architecture How to make sense of this new architecture?

5. The Macro-Financial Policy Architecture 5 NewOld Micro- Prudential Macro- Prudential Monetary Policy Global Architecture Micro- Prudential Monetary Policy Global Architecture

6. Architecture of Complexity 6 Complex system: whole ≠ sum of parts Complex dynamics: non-linearities, emergent behaviour, fat tails Hierarchical structures may re-emerge for evolutionary reasons – “decomposable” systems (Simon) Is that true of socio-economic systems?  Network economies of scale/scope foster tight-coupling  Policy moral hazard prevents Darwinian evolution  It may even encourage tight coupling – the “Doom Loop”  Socio-economic systems may be “non-decomposable”  Complex “System of Systems”

7. A Complex System of Systems? 7 Complex System of Systems: nested set of sub-systems, themselves individually complex Eg, “layered” networks  Risk much greater than implied by looking at each layer  “Missing a layer” poses real risks when assessing risks  The more complex the layers, and the higher their correlation, the more complex the system  Tinbergen rule (for complex systems): as many policy instruments as there are complex layers

8. Layered network 7 Layer 1 Layer 2 Layer 3

9. Simulating Complexity 9 Chart 1: Joint Distributions of Simulated System of systems (a) An uncorrelated simple versus correlated complex system of systems

10. Simulating Complexity 10 Chart 1: Joint Distributions of Simulated System of systems (a) … adding a complex layer …

11. The Macro-Financial System of Systems 11

12. Complexity of Individual Banks - 2006 12 Size of Balance Sheet (b) Nominal Value of Derivatives (c) Number of Legal Entities (d) Trading Assets (% of Total Assets) (e)

13. Complexity of Individual Banks - 2013 13 Size of Balance Sheet (b) Nominal Value of Derivatives (c) Number of Legal Entities (d) Trading Assets (% of Total Assets) (e)

14. Bank Complexity and Performance 14 Source: True Cost of complexity in the banking sector’, Simplicity Consulting (2012).

15. Financial System Complexity 15 Interbank exposures network (2013)

16. Financial System Complexity – Non-Banks 16

17. Macro-Economic Complexity 17 Flow of Funds, United Kingdom (1978)

18. Macro-Economic Complexity 18 Flow of Funds, United Kingdom (2013) Source: ONS, IMA, FCA, BVCA, Financial statements, Regulatory Returns, Bank calculations. Notes: Balance sheets are sized net of derivatives and intrabank exposures and expressed as a % of GDP.

19. Macro-Economic Complexity 19 Flow of Funds, United Kingdom (2013) Source: ONS, IMA, FCA, BVCA, Financial statements, Regulatory Returns, Bank calculations. Notes: Balance sheets are sized net of derivatives and intrabank exposures and expressed as a % of GDP.

20. Macro-Economic Complexity 20 Flow of Funds, United Kingdom (2013) Source: ONS, IMA, FCA, BVCA, Financial statements, Regulatory Returns, Bank calculations. Notes: Balance sheets are sized net of derivatives and intrabank exposures and expressed as a % of GDP.

21. Global Complexity 21 The Growth in Global Trade and Finance

22. Global Trade Complexity 22 19952013

23. Global Financial Complexity 23 The Global Banking System 1980 2007

24. Economic and Financial Complexity 24 GDP growthCredit Growth

25. Economic and Financial Complexity 25 Equity Returns Rice Prices

26. Public Policy Implications 26 How does this help us assess the new macro-financial architecture?  Data  Models  Policy Design

27. Data Gaps 27 green=Available data, amber=Limited availability, and red=no data availability

28. Modelling Banking Interactions 28 Total assets in the system generated from RAMSI

29. Simulating Monetary and Macro-Prudential Policy 29

30. Macro-Financial Policy Design 30 TEXT [ARIAL 20]

31. Source: Data are based on the Bank of England’s internal Product Sales Database collected by the FCA. Calibrating Macro-Prudential Policy Loan-to-income multiple ≥ 4.5

52. Macro-Prudential Policy

53. Global Financial Architecture 53 Chart 20: Correlation of 10 year bond yields and equity prices Co-ordinating global macro-prudential policy?

54. Conclusion 54 … unfinished business …