A concern for reputation incentivises banks to seek risky ventures (to keep dancing), the more so the better is the market’s prior on the macro state (the louder the music). We also posit as a larger proportion of banks set risky credit policies, the larger the incentive to pursue similarly risky policies. When others are posting positive earnings, the reputational loss from foreclosing and taking losses is that much greater. This is the “Keynes constraint”. It is better for your reputation to fail conventionally than to succeed unconventionally. These conditions generate the potential for credit booms and busts. The better is the macro state, the greater banks’ incentive to pursue risky projects to preserve reputation, as the market attributes low earnings to low ability. But one bank’s announcement of positive earnings encourages others to announce positive earnings by setting risky policies too. In Rajan’s model this strategic complementarity between banks generates multiple equilibria: in sufficiently good states, banks coordinate on risky policies (“credit booms”), while in bad states they coordinate on tight policies (“credit crunches”). In between, either equilibrium is possible. Define the payoff function  . Substituting gives:  This captures the marginal return to adopting a risky policy. It allows us to define the regions of fundamentals over which risky policies and tight policies dominate respectively.
On the face of it, these summary statistics are consistent with credit dynamics being distinct from GDP dynamics. It is possible to formalise this intuition by using filtering techniques to  11  The countries covered are: Australia, Canada, Germany, Denmark, Spain, France, United Kingdom, Italy, Netherlands, Norway, Sweden and the United States. 12  They argue that medium term cycles in GDP reflect persistent responses of real activity to the high-frequency fluctuations normally associated with the “business cycle” (Comin and Gertler, op. cit.). In this sense, there is a direct analogy with our model, in which strategic complementarities in risk taking can generate persistent credit cycles in response to high-frequency fluctuations in fundamentals. 13  The bank loans series consists of total domestic currency loans of banks and banking institutions to companies and households, while the assets series consists of total domestic currency assets of banks and banking institutions. For a full description of the data and its sources, see Schularick and Taylor (2009), Appendix B.  BIS Review 168/2010  9  extract the cycle in credit. To do so, we apply a band-pass filter to the data. 14 This isolates the cyclical component of a series operating in a frequency range specified by the user. 15 Charts 6–7 show cyclical fluctuations in real loan growth in the UK and US. The specified frequency domain is 8–20 years. Shorter-term, business cycle fluctuations, say between 2–8 years, were typically not found to account for much of the overall cyclical variation in credit.