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Over the past few decades, changes in market conditions such as globalisation and deregulation of financial markets as well as product innovation and technical advancements have induced financial institutions to expand their business activities beyond their traditional boundaries and to engage in cross-sectoral operations. As combining different sectoral businesses offers opportunities for operational synergies and diversification benefits, financial groups comprising banks, insurance undertakings and/or investment firms, usually referred to as financial conglomerates, have rapidly emerged, providing a wide range of services and products in distinct financial sectors and oftentimes in different geographic locations. In the European Union (EU), financial conglomerates have become part of the biggest and most active financial market participants in recent years. Financial conglomerates generally pose new problems for financial authorities as they can raise new risks and exacerbate existing ones. In particular, their cross-sectoral business activities can involve prudentially substantial risks such as the risk of regulatory arbitrage and contagion risk arising from intra-group transactions. Moreover, the generally large size of financial conglomerates as well as the high complexity and interconnectedness of their corporate structures and risk exposures can entail substantial systemic risk and can therefore threaten the stability of the financial system as a whole. Until a few years ago, there was no supervisory framework in place which addressed a financial conglomerate in its entirety as a group. Instead, each group entity within a financial conglomerate was subject to the supervisory rules of its pertinent sector only. Such silo supervisory approach had the drawback of not taking account of risks which arise or aggravate at the group level. It also failed to consider how the risks from different business lines within the group interrelate with each other and affect the group as a whole. In order to address this lack of group-wide prudential supervision of financial conglomerates, the European legislator adopted the Financial Conglomerates Directive 2002/87/EC8 (‘FCD’) on 16 December 2002. The FCD was transposed into national law in the member states of the EU (‘Member States’) by 11 August 2004 for application to financial years beginning on 1 January 2005 and after. The FCD primarily aims at supplementing the existing sectoral directives to address the additional risks of concentration, contagion and complexity presented by financial conglomerates. It therefore provides for a supervisory framework which is applicable in addition to the sectoral supervision. Most importantly, the FCD has introduced additional capital requirements at the conglomerate level so as to prevent the multiple use of the same capital by different group entities. This paper seeks to examine to what extent the FCD provides for an adequate capital regulation of financial conglomerates in the EU while taking into account the underlying sectoral capital requirements and the inherent risks associated with financial conglomerates. In Part 1, the definition and the basic corporate models of financial conglomerates will be presented (I), followed by an illustration of the core motives behind the phenomenon of financial conglomeration (II) and an overview of the development of the supervision over financial conglomerates in the EU (III). Part 2 begins with a brief elaboration on the role of regulatory capital (I) and gives a general overview of the EU capital requirements applicable to banks and insurance undertakings respectively. A delineation of the commonalities and differences of the banking and the insurance capital requirements will be provided (II). It continues to further examine the need for a group-wide capital regulation of financial conglomerates and analyses the adequacy of the FCD capital requirements. In this context, the technical advice rendered by the Joint Committee on Financial Conglomerates (JCFC) as well as the currently ongoing legislative reforms at the EU level will be discussed (III). The paper finally closes with a conclusion and an outlook on remaining open issues (IV).
The financial services industry worldwide has undergone major transformation since the late 1970s. Technological advancements in information processing and communication facilitated financial innovation and narrowed traditional distinctions in financial products and services, allowing them to become close substitutes for one another. The deregulation process in many major economies prior to the recent financial crisis blurred the traditional lines of demarcation between the distinct types of financial institutions, exposing those firms to new competitors in their traditional business areas, while the increasing globalization of financial markets fostered the provision of financial services across national borders. Against this backdrop, a trend toward consolidation across financial sectors as well as across national borders increasingly manifested itself since the 1990s. The developments in the financial markets ever more intensified competition in the financial services industry and induced financial institutions to redefine their business strategies in search of higher profitability and growth opportunities. Consolidation across distinct financial sectors, i.e. financial conglomeration, in particular became a popular business strategy in light of the potential operational synergies and diversification benefits it can offer. This trend spurred the growth of diversified financial groups, the so-called financial conglomerates, which commingle banking, securities, and insurance activities under one corporate umbrella.5 Still today, large, complex financial conglomerates are represented among major players in the financial markets worldwide, whose activities not only sway across traditional boundaries of banking, securities, and insurance sectors but also across national borders.
Notwithstanding the economic benefits that conglomeration may produce as a business strategy, the emergence of financial conglomerates also exacerbated existing and created new prudential risks in the financial system. 6 The mixing of a variety of financial products and services under one corporate roof and the generally large and complex group structure of financial conglomerates expose such organizations to specific group risks such as contagion and arbitrage risk as well as systemic risk. When realized, these risks may not only cause the failure of an entire financial group but threaten the stability of the financial system as a whole, as evidenced by the events during recent financial crisis of 2007-2009...
I propose a dynamic stochastic general equilibrium model in which the leverage of borrowers as well as banks and housing finance play a crucial role in the model dynamics. The model is used to evaluate the relative effectiveness of a policy to inject capital into banks versus a policy to relieve households of mortgage debt. In normal times, when the economy is near the steady state and policy rates are set according to a Taylor-type rule, capital injections to banks are more effective in stimulating the economy in the long-run. However, in the middle of a housing debt crisis, when households are highly leveraged, the short-run output effects of the debt relief are more substantial. When the zero lower bound (ZLB) is additionally considered, the debt relief policy can be much more powerful in boosting the economy both in the short-run and in the longrun. Moreover, the output effects of the debt relief become increasingly larger, the longer the ZLB is binding.
This paper investigates the accuracy of point and density forecasts of four DSGE models for inflation, output growth and the federal funds rate. Model parameters are estimated and forecasts are derived successively from historical U.S. data vintages synchronized with the Fed’s Greenbook projections. Point forecasts of some models are of similar accuracy as the forecasts of nonstructural large dataset methods. Despite their common underlying New Keynesian modeling philosophy, forecasts of different DSGE models turn out to be quite distinct. Weighted forecasts are more precise than forecasts from individual models. The accuracy of a simple average of DSGE model forecasts is comparable to Greenbook projections for medium term horizons. Comparing density forecasts of DSGE models with the actual distribution of observations shows that the models overestimate uncertainty around point forecasts.
The paper illustrates based on an example the importance of consistency between the empirical measurement and the concept of variables in estimated macroeconomic models. Since standard New Keynesian models do not account for demographic trends and sectoral shifts, the authors proposes adjusting hours worked per capita used to estimate such models accordingly to enhance the consistency between the data and the model. Without this adjustment, low frequency shifts in hours lead to unreasonable trends in the output gap, caused by the close link between hours and the output gap in such models.
The retirement wave of baby boomers, for example, lowers U.S. aggregate hours per capita, which leads to erroneous permanently negative output gap estimates following the Great Recession. After correcting hours for changes in the age composition, the estimated output gap closes gradually instead following the years after the Great Recession.
Schuldenanstieg und Haftungsausschluss im deutschen Föderalstaat : zur Rolle des Moral Hazard
(2007)
Einleitung: Die deutschen Staatsschulden sind in den letzten Jahrzehnten kontinuierlich gestiegen. Künftige Generationen werden zusätzlich aufgrund der demographischen Entwicklung durch die umlagenfinanzierten sozialen Sicherungssysteme belastet. Gerade auch der Anstieg der Verschuldung der Bundesländer war in den letzten Jahrzehnten spürbar. So betrug die Verschuldung aller deutschen Bundesländer zusammengenommen 1991 noch 168 Mrd. Euro, während Anfang 2007 die Verschuldung 483 Mrd. Euro betrug, was eine knappe Verdopplung der Schuldenquote der Länder (Verschuldung in Prozent des BIP) auf ca. 21 Prozent impliziert. In der aktuellen Diskussion um die Reform des deutschen Föderalismus besteht Einigkeit in der Diagnose des Problems. Die Entwicklung der Staatsschulden ist kritisch und darf sich so nicht fortsetzen. Uneinigkeit herrscht hingegen über die Ursache des Anstiegs. Ebenfalls wird um die beste Möglichkeit, diesen zu bremsen, gerungen. Verschiedene Autoren argumentieren, dass der Verschuldungsanstieg der deutschen Bundesländer vor allem auf den Moral Hazard Anreiz zurückzuführen ist. Der vorliegende Diskussionsbeitrag diskutiert dies als einen der möglichen Gründe des Schuldenanstiegs. Hierzu wird zunächst das Konzept kurz eingeführt. Anschließend wird die bestehende empirische Evidenz für Deutschland diskutiert. Schließlich wird eine Bewertung und Einordnung in die aktuelle Debatte vorgenommen. Schlußbemerkungen: Im vorliegenden Diskussionsbeitrag wird das "Moral hazard" Problem als einer der möglichen Gründe für den beobachteten starken Anstieg der Verschuldung deutscher Bundesländer diskutiert. Es wurde gezeigt, dass die Finanzmärkte kaum auf die erheblichen Unterschiede in den fiskalischen Fundamentaldaten der Länder reagieren. Mit einer Fallstudie wurde außerdem verdeutlicht, dass das aktuelle Bundesverfassungsgerichtsurteil zu einer eventuellen Haushaltsnotlage von Berlin Berlin die Risikoeinschätzung der Märkte für deutsche Bundesländer nicht verändert hat. Alles in allem scheint es sinnvoll, über eine größere Beteiligung der Gläubiger an Risiken einzelner Länder nachzudenken. Dies dürfte aber den Schuldenanstieg nur bei bereits hoch verschuldeten Ländern begrenzen und möglicherweise einem Notlagenfall vorbeugen, nicht aber den grundsätzlichen "Defizit-Bias" der Finanzpolitik kompensieren. Insgesamt scheinen deswegen vorgelagerte Regeln notwendig, um den Anstieg der Verschuldung schon früh zu unterbinden und somit Belastungen zukünftiger Generationen zu reduzieren.
The recent decline in euro area inflation has triggered new calls for additional monetary stimulus by the ECB in order to counter the threat of a self‐reinforcing deflation and recession spiral. This note reviews the available evidence on inflation expectations, output gaps and other factors driving current inflation through the lens of the Phillips curve. It also draws a comparison to the Japanese experience with deflation in the late 1990s and the evidence from Japan concerning the outputinflation nexus at low trend inflation. The note concludes from this evidence that the risk of a selfreinforcing deflation remains very small. Thus, the ECB best await the impact of the long‐term refinancing operations decided in June that have the potential to induce substantial monetary accommodation once implemented for the first time in September.
In the aftermath of the global financial crisis, the state of macroeconomicmodeling and the use of macroeconomic models in policy analysis has come under heavy criticism. Macroeconomists in academia and policy institutions have been blamed for relying too much on a particular class of macroeconomic models. This paper proposes a comparative approach to macroeconomic policy analysis that is open to competing modeling paradigms. Macroeconomic model comparison projects have helped produce some very influential insights such as the Taylor rule. However, they have been infrequent and costly, because they require the input of many teams of researchers and multiple meetings to obtain a limited set of comparative findings. This paper provides a new approach that enables individual researchers to conduct model comparisons easily, frequently, at low cost and on a large scale. Using this approach a model archive is built that includes many well-known empirically estimated models that may be used for quantitative analysis of monetary and fiscal stabilization policies. A computational platform is created that allows straightforward comparisons of models’ implications. Its application is illustrated by comparing different monetary and fiscal policies across selected models. Researchers can easily include new models in the data base and compare the effects of novel extensions to established benchmarks thereby fostering a comparative instead of insular approach to model development
The global financial crisis and the ensuing criticism of macroeconomics have inspired researchers to explore new modeling approaches. There are many new models that deliver improved estimates of the transmission of macroeconomic policies and aim to better integrate the financial sector in business cycle analysis. Policy making institutions need to compare available models of policy transmission and evaluate the impact and interaction of policy instruments in order to design effective policy strategies. This paper reviews the literature on model comparison and presents a new approach for comparative analysis. Its computational implementation enables individual researchers to conduct systematic model comparisons and policy evaluations easily and at low cost. This approach also contributes to improving reproducibility of computational research in macroeconomic modeling. Several applications serve to illustrate the usefulness of model comparison and the new tools in the area of monetary and fiscal policy. They include an analysis of the impact of parameter shifts on the effects of fiscal policy, a comparison of monetary policy transmission across model generations and a cross-country comparison of the impact of changes in central bank rates in the United States and the euro area. Furthermore, the paper includes a large-scale comparison of the dynamics and policy implications of different macro-financial models. The models considered account for financial accelerator effects in investment financing, credit and house price booms and a role for bank capital. A final exercise illustrates how these models can be used to assess the benefits of leaning against credit growth in monetary policy.