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This paper explains why the collection of panel (reinterview) data on a comprehensive measure of household expenditures is of great value both for measuring budget shares (the core mission of a Consumer Expenditure survey) and for the most important research and public policy uses to which CE data can be applied, including construction of spending-based measures of poverty and inequality and estimating the effects of fiscal policy.
The Great Recession confirmed a bedrock principle of modern consumption theory: It is impossible to explain aggregate spending behavior without knowledge of the underlying microeconomic distribution of circumstances and choices across households. National accounting frameworks therefore need to be augmented by “bottom up” measures that both (a) capture the microeconomic heterogeneity (in expenditures, income, assets, debt, and beliefs) in the population and (b) sum up to statistics that have a recognizable relationship to the aggregate totals that are already reasonably well measured.
Multiple lenders and corporate distress: evidence on debt restructuring : [Version Juli 2002]
(2002)
In the recent theoretical literature on lending risk, the common pool problem in multi-bank relationships has been analyzed extensively. In this paper we address this topic empirically, relying on a unique panel data set that includes detailed credit-fie information on distressed lending relationships in Germany. In particular, it includes information on bank pools, a legal institution aimed at coordinating lender interests in borrower distress. We find that the existence of small bank pools increases the probability of workout success and that coordination costs are positively related to pool size. We identify major determinants of pool formation, in particular the distribution of lending shares among banks, the number of banks, and the severity of the distress shock to the borrower.
We develop a methodology to identify and rank “systemically important financial institutions” (SIFIs). Our approach is consistent with that followed by the Financial Stability Board (FSB) but, unlike the latter, it is free of judgment and it is based entirely on publicly available data, thus filling the gap between the official views of the regulator and those that market participants can form with their own information set. We apply the methodology to annual data on three samples of banks (global, EU and euro area) for the years 2007-2012. We examine the evolution of the SIFIs over time and document the shifs in the relative weights of the major geographic areas. We also discuss the implication of the 2013 update of the identification methodology proposed by the FSB.
We examine the effects of credit default swaps (CDS), a major type of over-the-counter derivative, on the corporate liquidity management of the reference firms. CDS help firms to access the credit market since the lenders can hedge their credit risk more easily using these contracts. However, CDS-protected creditors can be tougher in debt renegotiations and less willing to support distressed borrowers, causing some firms to become more cautious. Consequently, we find that firms hold significantly more cash after the inception of CDS trading on their debt. The increase in cash holdings by CDS firms is more pronounced for financially constrained firms and firms facing higher refinancing risk. Moreover, bank relationships and outstanding credit facilities intensify the CDS effect on cash holding. Finally, firms with greater financial expertise hold more cash when their debt is referenced by CDS. These findings suggest that CDS, which are primarily a risk management tool for lenders, induce firms to adopt more conservative liquidity policies.
We use a unique data set from the Trade Reporting and Compliance Engine (TRACE) to study liquidity effects in the US structured product market. Our main contribution is the analysis of the relation between the accuracy in measuring liquidity and the potential degree of disclosure. Having access to all relevant trading information, we provide evidence that transaction cost measures that use dealer specific information such as trader identity and trade direction can be efficiently proxied by measures that use less detailed information. This finding is important for all market participants in the context of OTC markets, as it fosters our understanding of the information contained in transaction data. Thus, our results provide guidance for improving transparency while maintaining trader confidentiality. In addition, we analyze liquidity in the structured product market in general and show that securities that are mainly institutionally traded, guaranteed by a federal authority, or have low credit risk, tend to be more liquid.
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.
This paper investigates the accuracy of forecasts from four DSGE models for inflation, output growth and the federal funds rate using a real-time dataset synchronized with the Fed’s Greenbook projections. Conditioning the model forecasts on the Greenbook nowcasts leads to forecasts that are as accurate as the Greenbook projections for output growth and the federal funds rate. Only for inflation the model forecasts are dominated by the Greenbook projections. A comparison with forecasts from Bayesian VARs shows that the economic structure of the DSGE models which is useful for the interpretation of forecasts does not lower the accuracy of forecasts. Combining forecasts of several DSGE models increases precision in comparison to individual model forecasts. Comparing density forecasts with the actual distribution of observations shows that DSGE models overestimate uncertainty around point forecasts.
In this study prepared for the ECON Committee of the European Parliament, Gellings, Jungbluth and Langenbucher present a graphic overview on core legislation in the area of economic and financial services in Europe. The mapping overview can serve as background for further deliberations. The study covers legislation in force, proposals and other relevant provisions in fourteen policy areas, i.e. banking, securities markets and investment firms, market infrastructure, insurance and occupational pensions, payment services, consumer protection in financial services, the European System of Financial Supervision, European Monetary Union, Euro bills and Coins and statistics, competition, taxation, commerce and company law, accounting and auditing.
This paper contributes to the ongoing debate on the relationship between austerity measures and economic growth. We propose a general equilibrium model where (i) agents have recursive preferences; (ii) economic growth is endogenously driven by investments in R&D; (iii) the government is committed to a zero-deficit policy and finances public expenditures by means of a combination of labor taxes and R&D taxes. We find that austerity measures that rely on reducing resources available to the R&D sector depress economic growth both in the short- and long-run. High debt EU members are currently implementing austerity measures based on higher taxes and/or lower investments in the R&D sector. This casts some doubts on the real ability of these countries to grow over the next years.