This in a sense underscores the importance of Tinbergen’s augmented policy rule – that there should be as many policy tools as there are complex sub-systems – when managing a complex system of systems. None of the models so far considers global spill-overs, either through trade or financial channels. Generally-speaking, there is a dearth of macro-economic models which take seriously these international spillovers in an analytically-coherent fashion. Even if modelling this behaviour is over-ambitious in the short-term, there may be merit in improved monitoring of these global flows of financing over time, given their importance for the stability of economies and financial systems. Elsewhere, I have likened this to the creation of “global weather map”. This could be used to track and map the source, scale and nature of cross-border capital flows in close to real-time (Haldane (2012, 2014) and IMF (2013)). Plotting this complex, rapidly-adapting web would be a natural precursor to using it to address “what if” questions. What, for example, would be the impact of a rise in US interest rates on the international flow of funds? The IMF would be the natural guardians of this surveillance-cum-stress-testing machine. (c)  Policy design  Significant changes have been made to the macro-financial policy architecture since the crisis. In general, these frameworks have moved closer towards meeting Tinbergen’s rule of having as many distinct policy tools as there are complex layers in the macro-financial system.
This is a diagnostic on the diversity of a bank’s business model – whether it is engaged in investment as well as commercial banking. Some of these trading assets will also be complex and hence difficult to price and trade – so-called Level 2 and 3 assets. As Chart 3 shows, the average SIFI had a trading book of around a quarter of assets in 2006. For the largest, this was closer to around 50% of assets. 7  See BCBS (2014). 8  Notional exposures are likely to be a poor proxy of the underlying risk on this portfolio, but provide an indication of the scale of gross derivative positions. 6  BIS central bankers’ speeches  Since the crisis, there is little evidence of these complexities having reversed. Chart 4 updates the four metrics using end-2013 data. The balance sheet of the average SIFI has not shrunk. In fact, it had risen to around $ trillion by end-2013. For the largest SIFI, it was around $ trillion. The pattern is even more striking off balance sheet. For the average SIFI, the derivatives book has risen by over 50% to over $ trillion by 2013. For the largest, it had risen to $ trillion. On the other complexity metrics, the number of legal entities for the average SIFIs is essentially unchanged comparing 2006 and 2013.