Shadow banks and the risk-taking channel of monetary policy transmission in the euro area

Abstract

We provide evidence for a risk-taking channel of monetary policy transmission in the euro area that works through an increase in shadow banks’ total asset growth and their risk assets ratio. Our dataset covers the period 2000Q1–2018Q3 and includes, in addition to the standard variables for real GDP growth, inflation, and the monetary policy stance, the aforementioned two indicators for the shadow banking sector. Based on vector autoregressive models for the euro area as a whole, we find a portfolio reallocation effect towards riskier assets and evidence for a general expansion of assets. Both effects last for roughly six quarters in the case of conventional monetary policy shocks, whereas for unconventional monetary policy shocks the responses are significant for two quarters only. Country-specific as well as sector-specific estimations confirm these findings for most of the euro area countries and all non-bank types, but also reveal some heterogeneity in the reaction of financial institutions.

Analysis of the risk transmission mechanism of monetary policy in the monetary and financial service sectors from the perspective of asset-liability management

“…Previous studies on risk transmission mechanisms also showed that some monetary policies transmitted risks by expanding assets and deposits or stimulating aggregate demands through wealth channels. Another interesting perspective that has been explored by previous studies is the response of monetary and financial services companies to contrasts between monetary policy and regulatory expectations, and that the specific risk transmission is dependent on the heterogeneity across assets and liabilities, market concentration, enterprise size, liquidity, and leverage ratio [4][5][6][7][8][9][10][11][12][13][14].…”

Effects of Bank Capital Requirements on Lending by Banks and Non-Bank Financial Institutions

“…In Appendix 2, we define the group called Other NBFI which comprises Financial enterprises, Factoring companies, Leasing companies, and Non-MFIs. The choice of this sampling is driven by the motivation to define a separate group, which is close to the definition of "shadow banks" used by other papers(Wischnewsky and Neuenkirch (2021),Adrian and Jones (2018)). However, since according to their definition, "shadow banks" are rather heterogeneous entities, we prefer to consider them separately in the baseline analysis.…”