Cross-border interbank lending flows fell by around 20% between 2008Q2 and 2010Q2. The largest crossborder banks – the “super-spreaders” – appear to have played a central role in instigating and propagating this global contagion (Hills and Hoggarth (2013)). (e)  Correlations among sub-systems  Another dimension when gauging risks to the macro-financial system is the correlation between layers of the system. For correlations between individual banks and the financial system as a whole, one metric is provided by looking at the common component within the joint distribution of bank equity prices. For example, the first principal component of UK bank equity prices accounts for around 70% of the overall movement in bank equities. At the time of the financial crisis, this common component rose to nearer 90%. These correlations are high and highly crisis-sensitive, suggesting a close link between individual and systemic bank risk. The picture is similar when looking at correlations between developments in the financial system and the wider economy. For example, the pairwise correlation between the financial and non-financial components of UK equity prices is high, at around 0.8–0.9. The picture is similar if we move from the national to the international level: the first principal component of international equity prices accounts for around 80–90% of the variation. Each of these  11  This analysis uses the Bank for International Settlements bilateral locational statistics. This does not capture flows between periphery countries, so there is a risk that it overstates the importance of the core.

Another important element in our transition towards FIT is improving the skills, capabilities and capacities of our staff as well as the systems and procedures to establish a solid framework for forward-looking monetary policy conduct. A key step towards this advancement was when we partnered with the IMF, 4 years back, to develop a comprehensive, model-based Forecasting and Policy Analysis System (FPAS) to enhance the monetary policy decision making process. Substantial progress has been made in this regard, yielding a marked improvement in the modelling and forecasting capacity of the Central Bank, thereby enhancing the forward-looking monetary policy decision making process. The details of this modelling framework are in the public domain now. Going forward, the Central Bank will focus on devoting resources towards 15  further improving technical capacity and infrastructure, which would help generate timely and reliable model-based projections for macroeconomic analyses. The Central Bank has already planned to launch a number of new surveys and compile an array of new indicators to support monetary policy analysis. We continuously endeavour to improve the existing data collection and compilation efforts. These include several production trends related early warning indicators, upgraded price indices, extension of PMI surveys to sectors that need focused attention, and several digitalisation initiatives. We are also in the process of further expanding the household sector Inflation Expectations Survey (IES) beyond the Colombo District through the Country-Wide Data Collection System (CWDCS) with the intention of improving its coverage and precision.