Acharya, V.V., and Yorulmazer, T (2008), “Information Contagion and Bank Herding”, Journal of Money, Credit and Banking, Vol 40, 1, 215–231. Adrian, T, Ashcraft, A, Boesky, H and Pozsar, Z (2010), “Shadow Banking”, Federal Reserve Bank of New York Staff Reports 458. Alessandri, P and Haldane, A G (2009), “Banking on the State”, Bank of England. Angeletos, G, Hellwig, C and Pavan, A (2006), “Signalling in a Global Game: Coordination and Policy Traps”, Journal of Political Economy 114(3). Bank of England (2009), “The Role of Macroprudential Policy – A Discussion Paper”, available at http://www.bankofengland.co.uk/publications/other/financialstability/roleofmacroprudentialpoli cy091121.pdf Bean, C, Paustian, M, Penalver, A and Taylor, T (2010), “Monetary Policy After the Fall”, available at http://www.bankofengland.co.uk/publications/speeches/2010/speech444.pdf Belratti and Morana (2006), “Breaks and persistency: macroeconomic causes of stock market volatility”, Journal of Econometrics, 131 pp 151–177. Bernanke, B, Gertler, M and Gilchrist, S (1996), “The Financial Accelerator and the Flight to Quality”, The Review of Economics and Statistics 78(1), pp 1–15, MIT Press. BIS (2010), “Countercyclical Capital Buffer Proposal – Consultative Document”, Basel Committee on Banking Supervision, Bank for International Settlements. Bordo, M, Eichengreen, B, Klingebiel, D and Martinez-Peria, M S (2001), “Is the crisis problem growing more severe?”, Economic Policy 16(1), pp 51–82. Bordo, M and Haubrich, J (2010), “Credit crises, money and contractions: An historical view”, Journal of Monetary Economics, 1–18. Bordo, M D and Helbling, T (2003), “Have National Business Cycles Become More Synchronized?”, NBER Working Paper 10130. Bordo, M D and Helbling, T (2010), “International Business Cycle Synchronization in Historical Perspective”, NBER Working Paper 16103.

Broadly, these models can be classified according to the underlying micro-economic friction. For example, a well-established body of literature has looked at the effects of asymmetric information between borrowers and lenders in placing limits on credit (Bernanke, Gertler and Gilchrist (1996), Holstrom and Tirole (1997)). These constraints can be loosened by the borrower pledging collateral to the lender, in effect as a substitute for information (Kiyotaki and Moore (1997)). This solves one problem, but at the potential expense of another: movements in the prices of collateral then have the potential to aggravate cycles in leverage and credit (Geanakoplos (2010)). These cycles can in turn act as a “financial accelerator” for the business cycle. These are typically models of a representative bank and creditconstrained investor. A second potential source of credit market friction arises from coordination failures among lenders (Gorton and He (2008)). In these models, banks are heterogeneous and their behaviour strategic. The individually rational actions of heterogeneous lenders can generate collectively sub-optimal credit provision in both the upswing (a credit boom) and the downswing (a credit crunch), perhaps through herding (Acharya (2009), Acharya and Yorulmazer (2008)). This is the result of a collective action, or co-ordination, problem among banks. In credit markets, these co-ordination failures are far from new. Keynes memorably noted: “A sound banker, alas, is not one who foresees danger and avoids it, but one who, when he is ruined, is ruined in a conventional and orthodox way with his fellows, so that no one can really blame him” (Keynes (1931)).