axel a weber : macroeconomic imbalances in the european monetary union – causes and policy challenges speech by professor axel a weber, president of the deutsche bundesbank, at the kangaroo - group / epic lunch, strasbourg, 22 september 2010. * 1. * * introduction ladies and gentlemen first, i would like to thank you for your invitation. it is a pleasure to be here, and i am looking forward to discussing the problem of macroeconomic imbalances in european monetary union ( emu ) with you. intra - emu divergencies and the resulting imbalances in current account positions are not a new phenomenon. in fact, they have existed since the beginning of the monetary union. however, in the pre - crisis years the associated problems were partly masked by strong global economic expansion and the continuing integration within the euro area. it was the financial crisis that revealed the structural nature of the divergencies, and they are now a prominent and controversial issue in public debate. in my speech, i would like to provide a brief overview of the causes of the intra - emu divergencies and imbalances. having laid the groundwork, i would then like to discuss what policy options we have in dealing with the imbalances. 2. causes of macroeconomic imbalances in emu 2. 1 diverging current accounts are not per se a problem … the public debate on divergencies within emu focuses on the current account positions of member states ; let us take a look at them first. some member states such as germany, austria or the netherlands have persistent current account surpluses. other countries such as portugal, spain, greece or ireland show persistent current account deficits. in principle, a current account surplus or deficit reflects saving or borrowing at the national level. and, as for individuals, there is no reason why economies as a whole should not save or borrow. consequently, there is no reason for current accounts to be balanced in equilibrium. a current account surplus or deficit reflects a discrepancy between domestic savings and investment. such a discrepancy is not necessarily a bad thing. consider the following examples : countries with an ageing population usually save more than they invest as they face declining domestic investment opportunities. hence, they have temporary current account surpluses. at the same time, countries that are catching up on economic development usually invest more than they save as they have ample investment opportunities but are usually short of capital. as a consequence, they

lessons that we have learnt along the way. these lessons touch on the themes of openness and integration we have been discussing. in particular, i will stress the importance of three dimensions of openness : o being open to new ideas ; o being open to new businesses entering financial services ; and o being open to improving our own operations. “ new economy, new finance, new bank ”, available online at https : / / www. bankofengland. co. uk / / media / boe / files / report / 2019 / response - to - the - future - of - finance - report. pdf. all speeches are available online at www. bankofengland. co. uk / news / speeches openness to new ideas being open to new ideas and new ways of doing things is crucial for innovation. new approaches can improve the quality and inclusiveness of the financial services our people receive. however, this openness should not compromise our existing standards. instead, we must weigh potential benefits to efficiency and resilience, against potential risks to financial stability. let me give an example from our work in the u. k on machine learning that clarifies our approach. new general purpose technologies like ai and machine learning hold the promise of increasing economic productivity and providing better products across the economy, including in financial services. however, if not overseen appropriately, this technology could introduce new risks and enhance existing ones. the challenges posed by ai / ml are well documented - i will not dwell on them here. ai raises a range of ethical, operational, consumer protection, and competition issues. what is more, these issues are not theoretical. we have already seen the potential for new financial risks from technology during flash crashes in algorithmic trading, reminding us of the potential for introducing new instability. to ensure we balance the risks and opportunities appropriately, the bank of england is researching machine - learning deployment. together with the uk ’ s financial conduct authority ( fca ), we surveyed firms across the financial sector to understand the current state of deployment. our ‘ machine learning in uk financial services ’ report, published earlier in october, is the first structured study of its kind, anywhere in the world. 2 this work has generated many interesting, policy - relevant findings. two thirds of the financial services firms report they already use machine learning, live, in their business. most firms stated that they did not identify uk regulation as a major barrier to their deploying machine learning, focussing instead on challenges internal