Relative to the baseline, there is an additional large and persistent boom in the middle of the simulation, followed by a period of below counterfactual fundamentals. The path of the economy is more volatile, with deviations from trend larger and more persistent. In other words, the credit cycle has real and adverse consequences. Chart 2 Model simulation with low reputational weight  Source: Bank calculations. Chart 3 Model simulation with high reputational weight  Source: Bank calculations. 8  BIS Review 168/2010  2.4  Empirical implications  Several empirical implications follow from the model. First, strategic complementarities incentivise banks to adopt risky strategies in a coordinated fashion during the boom. So the dynamics of the model predict that we should observe cycles in financial activity at a macroeconomic level. Initial productivity improvements are amplified into lending booms, which are followed by credit busts and, potentially, crises. Second, at a micro-economic level, the coordination of risky strategies during the boom should compress the dispersion of bank earnings, as low ability banks masquerade as high ability banks during good times. But during the bust, when the macro state turns bad, the dispersion of banks’ earnings should increase as low ability types crystallise losses while high ability types do not. We turn next to the macro and micro evidence. 3.  Credit cycle dynamics  To what extent are the macroeconomic credit cycle dynamics predicted by the model present in the real world? To assess that, we draw on a dataset recently developed by Schularick and Taylor (2009).
16  We also used crisis dating from Lopez-Salido and Nelson (2010) for the US. BIS Review 168/2010  15  Table 3 asks what proportion of crisis years occurred within 5 years of the peak in the credit cycle in those countries. On average, more than half of all financial crisis years across the 12 countries appear to have been preceded by a credit boom. Among Anglo-Saxon countries, such as the US, UK and Australia, closer to 75% of crisis years occurred following a credit boom. This is relatively concrete evidence of the credit cycle having real and damaging effects on output. 17, 18 4.  Credit cycle spillovers  This empirical evidence to date, operating at a macro-economic level, is consistent with the model in Section 2: a credit cycle is clearly discernible; its frequency is different and its amplitude larger than the business cycle; and its fluctuations may exacerbate the business cycle. But the model also has implications at a micro-economic level, arising from strategic complementarities, or spillover effects, across firms. In this section we consider empirical evidence on such credit spillover effects. The model implies that the cross-sectional distribution of returns to banking should be compressed during a credit boom, as banks seek to keep up with competitors by collectively boosting returns. This is a time-series phenomenon. A second implication is that the dispersion in returns may be smaller for financial than for non-financial companies to the extent that former are more susceptible to risk illusion. This is a cross-sectional phenomenon.