The Importance of Estimation Uncertainty in a Multi-Rating Class Loan Portfolio
Henry Dannenberg
IWH Discussion Papers,
Nr. 11,
2011
Abstract
This article seeks to make an assessment of estimation uncertainty in a multi-rating class loan portfolio. Relationships are established between estimation uncertainty and parameters such as probability of default, intra- and inter-rating class correlation, degree of inhomogeneity, number of rating classes used, number of debtors and number of historical periods used for parameter estimations. In addition, by using an exemplary portfolio based on Moody’s ratings, it becomes clear that estimation uncertainty does indeed have an effect on interest rates.
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Fiscal Spending Multiplier Calculations based on Input-Output Tables – with an Application to EU Members
Toralf Pusch, A. Rannberg
Abstract
Fiscal spending multiplier calculations have been revived in the aftermath of the
global financial crisis. Much of the current literature is based on VAR estimation
methods and DSGE models. The aim of this paper is not a further deepening of
this literature but rather to implement a calculation method of multipliers which is
suitable for open economies like EU member states. To this end, Input-Output tables are used as by this means the import intake of domestic demand components can be isolated in order to get an appropriate base for the calculation of the relevant import quotas. The difference of this method is substantial – on average the calculated multipliers are 15% higher than the conventional GDP fiscal spending multiplier for EU members. Multipliers for specific spending categories are comparably high, ranging between 1.4 and 1.8 for many members of the EU. GDP drops due to budget consolidation might therefore be substantial if monetary policy is not able to react in an expansionary manner.
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Identifying Industrial Clusters from a Multidimensional Perspective: Methodical Aspects with an Application to Germany
Matthias Brachert, Mirko Titze, Alexander Kubis
Papers in Regional Science,
Nr. 2,
2011
Abstract
If regional development agencies assume the cluster concept to be an adequate framework to promote regional growth and competitiveness, it is necessary to identify industrial clusters in a comprehensive manner. Previous studies used a diversity of methods to identify the predominant concentrations of economic activity in one industrial sector in a region. This paper is based on a multidimensional approach developed by Titze et al. With the help of the combination of concentration measures and input–output methods they were able to identify horizontal and vertical dimensions of industrial clusters. This paper aims to refine this approach by using a superior measure of spatial concentration and by integrating information about spatial interdependence of industrial cluster structures to contribute to a more adequate framework for industrial cluster identification.
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Has the Euro Increased International Price Elasticities?
Oliver Holtemöller, Götz Zeddies
IWH Discussion Papers,
Nr. 18,
2010
publiziert in: Empirica
Abstract
This paper analyzes the role of common data problems when identifying structural breaks in small samples. Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown, Durbin, and Evans (1975) and Zeileis (2004), Nyblom (1989) and Hansen (1992), and Andrews, Lee, and Ploberger (1996). Power and size properties are derived using Monte Carlo simulations. Results emphasize that mostly the CUSUM type tests are affected by the presence of heteroscedasticity, whereas the individual parameter Nyblom test and AvgLM test are proved to be highly robust. However, each test is significantly affected by leptokurtosis. Contrarily to other tests, where skewness is far more problematic than kurtosis, it has no additional effect for any of the endogenous break tests we analyze. Concerning overall robustness the Nyblom test performs best, while being almost on par to more recently developed tests in terms of power.
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Testing for Structural Breaks at Unknown Time: A Steeplechase
Makram El-Shagi, Sebastian Giesen
Abstract
This paper analyzes the role of common data problems when identifying structural breaks in small samples. Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown, Durbin, and Evans (1975) and Zeileis (2004), Nyblom (1989) and Hansen (1992), and Andrews, Lee, and Ploberger (1996). Power and size properties are derived using Monte Carlo simulations. Results emphasize that mostly the CUSUM type tests are affected by the presence of heteroscedasticity, whereas the individual parameter Nyblom test and AvgLM test are proved to be highly robust. However, each test is significantly affected by leptokurtosis. Contrarily to other tests, where skewness is far more problematic than kurtosis, it has no additional effect for any of the endogenous break tests we analyze. Concerning overall robustness the Nyblom test performs best, while being almost on par to more recently developed tests in terms of power.
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Is there a Superior Distance Function for Matching in Small Samples?
Eva Dettmann, Claudia Becker, Christian Schmeißer
Abstract
The study contributes to the development of ’standards’ for the application of matching algorithms in empirical evaluation studies. The focus is on the first step of the matching procedure, the choice of an appropriate distance function. Supplementary o most former studies, the simulation is strongly based on empirical evaluation ituations. This reality orientation induces the focus on small samples. Furthermore, ariables with different scale levels must be considered explicitly in the matching rocess. The choice of the analysed distance functions is determined by the results of former theoretical studies and recommendations in the empirical literature. Thus, in the simulation, two balancing scores (the propensity score and the index score) and the Mahalanobis distance are considered. Additionally, aggregated statistical distance functions not yet used for empirical evaluation are included. The matching outcomes are compared using non-parametrical scale-specific tests for identical distributions of the characteristics in the treatment and the control groups. The simulation results show that, in small samples, aggregated statistical distance functions are the better
choice for summarising similarities in differently scaled variables compared to the
commonly used measures.
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Banking Integration, Bank Stability, and Regulation: Introduction to a Special Issue of the International Journal of Central Banking
Reint E. Gropp, H. Shin
International Journal of Central Banking,
Nr. 1,
2009
Abstract
The link between banking integration and financial stability has taken center stage in the wake of the current financial crisis. To what extent is the banking system in Europe integrated? What role has the introduction of the common currency played in this context? Are integrated banking markets more vulnerable to contagion and financial instability? Does the fragmented regulatory framework in Europe pose special problems in resolving bank failures? What policy reforms may become necessary? These questions are of considerable policy interest as evidenced by the extensive discussions surrounding the design and implementation of a new regulatory regime and by the increasing attention coming from academia.
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Berücksichtigung von Schätzunsicherheit bei der Kreditrisikobewertung: Vergleich des Value at Risk der Verlustverteilung des Kreditrisikos bei Verwendung von Bootstrapping und einem asymptotischen Ansatz
Henry Dannenberg
IWH Discussion Papers,
Nr. 3,
2009
Abstract
Bei der Kreditrisikobewertung müssen die Parameter Ausfallwahrscheinlichkeit und
-korrelation geschätzt werden. Diese Schätzung erfolgt unter Unsicherheit. In der Literatur werden asymptotische Konfidenzregionen diskutiert, um diese Unsicherheit bei der simultanen Schätzung beider Parameter zu bewerten. Diese Regionen setzen allerdings eine sehr lange Datenhistorie für eine genaue Bewertung voraus. Als Alternative bietet sich bei kurzen Datenhistorien Bootstrapping an. Diese Methode ist allerdings deutlich rechenintensiver. Im vorliegenden Beitrag wird untersucht, ab welcher Anzahl historisch verfügbarer Perioden Bootstrapping und eine Wald-Konfidenzregion zu einer vergleichbaren Bewertung des Kreditrisikos gelangen. Die hier genutzten Methoden führen zu ähnlichen Ergebnissen, wenn über 100 historische Perioden zur Verfügung stehen.
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