granular data would open up new possibilities for analysis by providing new insights into the effects of policies. let me give you an example. in order to analyse issues pertaining to global banks with granular data, the international banking research network was founded. this network brings together 1 / 3 bis central bankers'speeches researchers from around the world. they use micro - level data to better understand the consequences of global banking : country teams work on the same topic in parallel, using their distinct, bank - level data sets to help develop comparable cross - country evidence. although the underlying regulatory data cannot be made public, the results of the common analysis can be shared to inform the policy dialogue. one example is the latest research effort on the impact of changes in prudential policy instruments on lending of global banks ( buch / goldberg 2016 and buch / bussiere / goldberg 2016 ). this project uses a new database that focuses on changes in the intensity of the usage of several widely used prudential tools, taking into account both macroprudential and microprudential objectives. it finds that international spillovers vary across prudential instruments and are heterogeneous across banks. bank - specific factors like balance sheet conditions and business models drive, both the amplitude and direction of spillovers to lending growth rates. spillovers into lending growth from prudential tightening are positive in some cases, and negative in others. spillovers are most likely to occur via the affiliates of foreign banks hosted in a country, although some evidence exists of inward transmission through home - country global banks. this would be in line with an attempt of domestic banks to preserve market shares and to protect the domestic market from international policy spillovers. this example shows : the availability and flexible use of granular data early on is an integral part of any structured process of policy evaluation. other examples are easy to find : one can think of information on channels of transmission of monetary policy across different institutions, sectoral and firm - level drivers of productivity, the build - up of risks to financial stability and the causal impact of regulatory and monetary policies. to put it in a nutshell, we need to implement a new paradigm in statistics, moving away from traditional, aggregate statistics towards the flexible use of ( standardised ) micro data. micro data are collected only once and can be used for multiple purposes, which has the added advantage of a lower statistical reporting burden ( deutsche bundesbank 2016 ). in order to develop this benefit immediately

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