Mortgage interest rate dispersion in the euro area

Despite the remarkable economic and financial convergence over the last ten years in the euro area, mortgage interest rates still differ across countries. This note presents some stylised facts on the heterogeneity of mortgage interest rates across euro area countries on the basis of the Eurosystem’s harmonised MFI interest rate statistics. We also attempt to provide some insights into the reasons behind these cross-country differences using the methodology recently proposed by Affinito and Farabullini (2006). We differ from Affinito and Farabullini (2006) in that we focus on one particular banking market: the market for mortgage loans. This allows us to identify more clearly the role of specific structural features characterising that market in explaining mortgage rate dispersion. More specifically, we investigate the extent to which various mortgage loan demand and supply determinants help explaining the observed dispersion. It turns out that some of the heterogeneity can be explained by these factors, in particular those that relate to the supply side. However, a substantial part of the dispersion remains unexplained suggesting that much of the heterogeneity also reflects country-specific institutional differences that are likely to be caused by differences in the regulatory and fiscal framework of the mortgage markets. In order to test this, we extend our analysis to also include institutional factors and indeed find that crosscountry differences in enforcement procedures, tax subsidies and loan-to-value ratios influence the level of mortgage rates. JEL Classification: C23, E4, F36, G21, N24euro area, financial integration, Interest Rates, Mortgage markets

Euro area banking sector integration: using hierarchical cluster analysis techniques

In this study we apply cluster analysis techniques, including a novel smoothing method, to detect some basic patterns and trends in the euro area banking sector in terms of the degree of homogeneity of countries. We find that in the period 1998-2004 the banking sectors in the euro area countries seem to have become somewhat more homogeneous, although the results are not unequivocal and considerable differences remain, leaving scope for further integration. In terms of clustering, the Western and Central European countries (like Germany, France, Belgium, and to some extent also the Netherlands, Austria and Italy) tend to cluster together, while Spain and Portugal and more recently also Greece usually are in the same distinct cluster. Ireland and Finland form separate clusters, but overall tend to be closer to the Western and Central European cluster. JEL Classification: C49, F36, G21banking sector, cluster analysis, financial integration

Modelling loans to non-financial corporations in the euro area

We model the determinants of loans to non-financial corporations in the euro area. Using the Johansen (1992) methodology, we identify three cointegrating relationships. These relationships are interpreted as the long-run loan demand, investment and loan supply equations. The short-run dynamics of loan demand for the euro area are subsequently modelled by means of a Vector Error Correction Model (VECM). We perform a number of specification tests, which suggest that developments in loans to non-financial corporations in the euro area can be reasonably explained by the model. We then use the estimated model to analyse the impact of permanent and temporary shocks to the policy rate on bank lending to nonfinancial corporations. JEL Classification: C32, C51bank credit, cointegration, error-correction model, euro area, non-financial corporations

The dynamics of bank spreads and financial structure

This paper investigates the dynamics of the pass-through between market interest rates and bank interest rates in the euro area as a function of cyclical and structural differences in the financial system. We find that overall the speed of adjustment for loans is significantly faster than for deposits, and that the pass-through is especially sluggish for demand deposits and savings deposits. Bank soundness, credit risk and interest rate risk are found to exert a significant influence on the speed of pass through. We also find evidence of faster (slower) pass-through for loans (deposits) if the change in monetary policy was up (down). Overall, we find that competition among banks and competition from financial markets result in a faster bank interest rate pass-through. Finally, we find some evidence that financial innovation speeds up the pass-through for those market segments that are most directly affected by these innovations. JEL Classification: E43, G21banks, financial structure, monetary transmission, retail rates

Bank reactions after capital shortfalls

This paper investigates whether European banks have capital targets and how deviations from the target impact their equity composition and activity mix. Using quarterly data for a sample of large European banks between 2004 and 2011, we show that there are notable asymmetries in banks’ reactions to deviations from optimal capital levels. Banks prefer to reshuffle risk-weighted assets or increase asset holdings when being above their optimal Tier 1 ratio, whereas they rather try to increase equity levels or reshuffle risk-weighted assets without changing asset holdings when being below target. At the same time, focusing instead on a unweighted equity ratio target, we find evidence of deleveraging and lower loan growth for undercapitalized banks during the recent financial crisis, whereas in the pre-crisis periods banks primarily reacted to deviations from their optimal target by adjusting equity levels

A macro stress testing framework for assessing systemic risks in the banking sector

The use of macro stress tests to assess bank solvency has developed rapidly over the past few years. This development was reinforced by the financial crisis, which resulted in substantial losses for banks and created general uncertainty about the banking sector's loss-bearing capacity. Macro stress testing has proved a useful instrument to help identify potential vulnerabilities within the banking sector and to gauge its resilience to adverse developments. To support its contribution to safeguarding financial stability and its financial sector-related work in the context of EU/IMF Financial Assistance Programmes, and looking ahead to the establishment of the Single Supervisory Mechanism (SSM), the ECB has developed a top-down macro stress testing framework that is used regularly for forward-looking bank solvency assessments. This paper comprehensively presents the main features of this framework and illustrates how it can be employed for various policy analysis purposes

Multi-layered interbank model for assessing systemic risk

In this paper, we develop an agent-based multi-layered interbank network model based on a sample of large EU banks. The model allows for taking a more holistic approach to interbank contagion than is standard in the literature. A key finding of the paper is that there are material non-linearities in the propagation of shocks to individual banks when taking into account that banks are related to each other in various market segments. The contagion effects when considering the shock propagation simultaneously across multiple layers of interbank networks can be substantially larger than the sum of the contagion-induced losses when considering the network layers individually. In addition, a bank “systemic importance” measure based on the multi-layered network model is developed and is shown to outperform standard network centrality indicators. The finding of non-linear contagion effects when accounting for the interaction between the different layers of banks’ interlinkages have important policy implications. For example, it provides an argument for separating banks’ trading activities from their other intermediation activities

Multi-layered interbank model for assessing systemic risk

In this paper, we develop an agent-based multi-layered interbank network model based on a sample of large EU banks. The model allows for taking a more holistic approach to interbank contagion than is standard in the literature. A key finding of the paper is that there are non-negligible non-linearities in the propagation of shocks to individual banks when taking into account that banks are related to each other in various market segments. In a nutshell, the contagion effects when considering the shock propagation simultaneously across multiple layers of interbank networks can be substantially larger than the sum of the contagion-induced losses when considering the network layers individually. In addition, a bank 'systemic importance' measure based on the multi-layered network model is developed and is shown to outperform standard network centrality indicators

Assessing interbank contagion using simulated networks

This paper presents a new approach to randomly generate interbank networks while overcoming shortcomings in the availability of bank-by-bank bilateral exposures. Our model can be used to simulate and assess interbank contagion effects on banking sector soundness and resilience. We find a strongly non-linear pattern across the distribution of simulated networks, whereby only for a small percentage of networks the impact of interbank contagion will substantially reduce average solvency of the system. In the vast majority of the simulated networks the system-wide contagion effects are largely negligible. The approach furthermore enables to form a view about the most systemic banks in the system in terms of the banks whose failure would have the most detrimental contagion effects on the system as a whole. Finally, as the simulation of the network structures is computationally very costly, we also propose a simplified measure - a so-called Systemic Probability Index (SPI) - that also captures the likelihood of contagion from the failure of a given bank to honour its interbank payment obligations but at the same time is less costly to compute. We find that the SPI is broadly consistent with the results from the simulated network structures

Macroeconomic propagation under different regulatory regimes: Evidence from an estimated DSGE model for the euro area

The financial crisis clearly illuminated the potential amplifying role of financial factors on macroeconomic developments. Indeed, the heavy impairments of banks’ balance sheets brought to the fore the banking sector’s ability to provide a smooth flow of credit to the real economy. However, most existing structural macroeconomic models fail to take into account the crucial role of banks’ balance sheet adjustment in the propagation of shocks to the economy. This paper contributes to fill this gap, analyzing the role of credit market frictions in business cycle fluctuations and in the transmission of monetary policy. We estimate a closed-economy dynamic stochastic general equilibrium (DSGE) model for the euro area with financially-constrained households and firms and embedding an oligopolistic banking sector facing capital constraints. Using this setup we examine the macroeconomic implications of various financial frictions on the supply and demand of credit, and in particular we assess the effects of introducing risk-sensitive and more stringent capital requirements. Finally, we explore the scope for counter-cyclical bank capital rules and the strategic complementarities between macro-prudential tools and monetary policy. JEL Classification: E4, E5, F4banking, Bayesian estimation, DSGE Models, financial regulation