The Benefits Are at the Tail: Uncovering the Impact of Macroprudential Policy on Growth-At-Risk

Abstract

for their very helpful comments and suggestions. I also thank the comments of the participants of the research seminar at Banco de España and the International Finance and Banking Society Conference 2019. I specially acknowledge the colleagues of the working groups of the European Systemic Risk Board where this study has been extensively discussed, for their very useful improvement ideas and suggestions. This paper is the sole responsibility of its author. The views represented here do not necessarily reflect those of the Banco de España or the Eurosystem.

Economic Consequences of High Public Debt: Evidence from Three Large Scale DSGE Models

“…Hence, households receive interest and wage payments, unemployment benefits and other fiscal transfers, and they pay taxes. In line with Galí et al (2007), we also assume that a fraction of households does not participate in asset markets and consumes the entire income each period. Those households have become known in the literature as "rule-of-thumb" (RoT) households; we call the other type of households "optimizers".…”

“…Furthermore, households enjoy some monopoly power on the labour market because different types of labour are needed in production, and these are not perfectly substitutable. Wages are, hence, set by a union which takes into account optimizers and RoT households as in Galí et al (2007). Wage setting is associated with Rotemberg adjustment costs in the sense that changing nominal wages is costly for firms and for workers.…”

Real-time Weakness of the Global Economy: A First Assessment of the Coronavirus Crisis

“…We justify our modelling choice as the minimal specification that is necessary to account for the obvious fact that recessionary episodes come with very different growth rates of the GDP, and other real activity indicators. On the one hand, the Global Financial Crisis of [2007][2008] was unusually severe for many economies that, compared to it, subsequent recessions look barely distinguishable from normal times. For example, based on the data for many European countries, one would almost certainly fail to detect any other recession but the one observed upon the Global Financial Crisis when using a Markov-switching model with the common factor of the Hamilton type.…”

“…The literature involving the use of this type of frameworks to infer turning points in emerging economies is scarce. One possible reason for this is that modelling business cycles nonlinearities associated to emerging markets tends to be more challenging than for the case of developed countries due to a variety of features, such as strongly counter-cyclical current accounts or dramatic 'sudden stops' in capital inflows, Aguiar and Gopinath (2007), the role of country risk in the determination of emerging countries interest rates, Neumeyer and Perri (2005), or the role of patterns of production and international trade, Kohn et al (2018).…”

“…Jerzmanowski (2006) shows that output growth of emerging economies exhibit substantially different types of recurrent recessionary regimes. Also, Aguiar and Gopinath (2007) illustrate that modelling business cycles nonlinearities associated to emerging markets tends to be even more challenging than for the case of developed economies.…”