Macroprudential policy As you all know, a macroprudential authority (AMCESFI) has been in place in Spain since the start of the year. Its main task involves contributing to the coordination and exchange of information on financial stability-related aspects between the Banco de España, the Ministry of the Economy and Enterprise, the National Securities Market Commission and the Directorate General of Insurance and Pension Funds. In parallel, the supervision of the financial system as a whole has been bolstered by the extension of the macroprudential tools available to the sectoral supervisory authorities. Some of these new tools, in particular those of the Banco de España based on borrowers’ ability to pay, aim to prevent an excessive easing in lending standards on the part of banks and to contribute to the sustainability of household and corporate debt. These new instruments complement those already being used by the Banco de España: the countercyclical capital buffer, the systemic risk buffer and the buffer for systemically important institutions, among others. Overall, this new institutional framework and the attendant powers mark progress and the strengthening of financial stability in Spain. In fact, in my opinion1, the introduction of macroprudential policy instruments to complement monetary and fiscal policy is probably one of the most significant advances in the wake of the international financial crisis. For countries which, like Spain, belong to a monetary union, these tools are particularly important. They are some of the few instruments available in the national realm to ensure the stability of the domestic financial system.
The paper, written while they were both working in the New York Fed's Research Group in the mid-1990s, formed the basis of many internal discussions in 1999-2000 and 2006-2007 as the U.S. yield curve inverted.11 Much of the internal discussion was around trying to understand whether the properties of the yield curve were different. The current estimate from this model is a 23.6 percent chance that the U.S. economy will be in an NBER-defined recession in January 2020. Just like Tetlock, Arturo liked to extremize the results of the model, so for example a probability of at or above 30 percent is moved to 100 percent and below 30 percent is moved to zero. One reason to extremize the results is that the prediction object is a recession in one particular month, rather than the probability of a recession over a period of time. Marcelle Chauvet and I analyzed this more general problem.12 Our goal was to avoid the problem with the probit model that a constant forecast of, for example, a 25 percent probability that the economy will be in 3/6  BIS central bankers' speeches  recession in 12 months' time implying after one year of such monthly predictions a 97 percent probability the economy would be in a recession in at least one month of the 12. This is similar to the issue I mentioned earlier, where some of the superforecasters appear to have had difficulty calibrating their probability assessments over varying time horizons.