Does Machine Learning Help us Predict Banking Crises?
Johannes Beutel, Sophia List, Gregor von Schweinitz
Journal of Financial Stability,
December
2019
Abstract
This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance metric, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly efficiently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.
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Did the Swiss Exchange Rate Shock Shock the Market?
Manuel Buchholz, Gregor von Schweinitz, Lena Tonzer
Abstract
The Swiss National Bank abolished the exchange rate floor versus the Euro in January 2015. Based on a synthetic matching framework, we analyse the impact of this unexpected (and therefore exogenous) shock on the stock market. The results reveal a significant level shift (decline) in asset prices in Switzerland following the discontinuation of the minimum exchange rate. While adjustments in stock market returns were most pronounced directly after the news announcement, the variance was elevated for some weeks, indicating signs of increased uncertainty and potentially negative consequences for the real economy.
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Die wirtschaftliche Entwicklung Sachsen-Anhalts seit 1990
Oliver Holtemöller, Axel Lindner
Abstract
In diesem Beitrag wird die wirtschaftliche Entwicklung Sachsen-Anhalts seit 1990 im Kontext des ostdeutschen Transformationsprozesses von einer Zentralverwaltungswirtschaft zu einer Marktwirtschaft beschrieben. Die wirtschaftliche Leistungsfähigkeit Sachsen-Anhalts hat in den frühen 1990er Jahren zunächst schnell gegenüber Westdeutschland aufgeholt, vor allem weil der Kapitalstock modernisiert und erweitert worden ist. Seit einiger Zeit stagniert der Aufholprozess jedoch, und das Bruttoinlandsprodukt je Erwerbstätigen liegt etwa 20% unter dem westdeutschen Niveau. Die wirtschaftspolitische Herausforderung besteht darin, den Aufholprozess durch die Förderung von Forschung und Innovation und durch bessere Qualifizierung der Erwerbstätigen weiter voranzubringen.
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The Effects of Sovereign Risk: A High Frequency Identification Based on News Ticker Data
Ruben Staffa
IWH Discussion Papers,
Nr. 8,
2022
Abstract
This paper uses novel news ticker data to evaluate the effect of sovereign risk on economic and financial outcomes. The use of intraday news enables me to derive policy events and respective timestamps that potentially alter investors’ beliefs about a sovereign’s willingness to service its debt and thereby sovereign risk. Following the high frequency identification literature, in the tradition of Kuttner (2001) and Guerkaynak et al. (2005), associated variation in sovereign risk is then obtained by capturing bond price movements within narrowly defined time windows around the event time. I conduct the outlined identification for Italy since its large bond market and its frequent coverage in the news render it a suitable candidate country. Using the identified shocks in an instrumental variable local projection setting yields a strong instrument and robust results in line with theoretical predictions. I document a dampening effect of sovereign risk on output. Also, borrowing costs for the private sector increase and inflation rises in response to higher sovereign risk.
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Emissionsrechtemanagement mit dem „CO2-Navigator“
Wilfried Ehrenfeld
IWH Discussion Papers,
Nr. 19,
2011
Abstract
Das Modul „Emissionsrechtemanagement“ des Softwarepaketes „CO2-Navigator“ ist ein Instrument zum unternehmensinternen Management von Emissionsrechten im Rahmen des europäischen Emissionshandels. Es liefert zu jedem Zeitpunkt eines Kalenderjahres einen Überblick über den tagesaktuellen Bestand an Emissionszertifikaten sowie Transaktionen von CO2-Emissionszertifikaten wie Zuteilung, Kauf- und Verkaufsaktivitäten. Dabei werden die relevanten Zeitpunkte, Mengen und Preise erfasst.
Ausgehend vom aktuellen Stand der Emissionen einer Anlage wird mit Hilfe eines
unternehmenstypischen Emissionsprofils eine Abschätzung der Zertifikatedeckung
zum Bilanzstichtag des aktuellen Jahres ermöglicht. Hierbei wird eine eventuelle
Zertifikateunter- oder -überdeckung quantifiziert und graphisch verdeutlicht. Das
Modul stellt somit ein nützliches Hilfsmittel im Risikomanagementprozess von emissionsintensiven Unternehmen dar. Auf den von diesem Modul gelieferten Daten baut eine eventuell anschließende Investitionsanalyse auf, beispielsweise eine stochastische Investitionsplanung. Dieses Papier veranschaulicht die Motivation und den rechtlichen Rahmen sowie die technische Konzeption des Instruments.
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Human Capital Mobility and Convergence. A Spatial Dynamic Panel Model of the German Regions
Alexander Kubis, Lutz Schneider
Abstract
Since the fall of the iron curtain in 1989, the migration deficit of the Eastern part of Germany has accumulated to 1.8 million people, which is over 10 percent of its ini-tial population. Depending on their human capital endowment, these migrants might either – in the case of low-skilled migration – accelerate or – in high-skilled case– impede convergence. Due to the availability of detailed data on regional human capital, migration and productivity growth, we are able to test how geographic mobil-ity affects convergence via the human capital selectivity of migration. With regard to the endogeneity of the migration flows and human capital, we apply a dynamic panel data model within the framework of β-convergence and account for spatial depend-ence. The regressions indicate a positive, robust, but modest effect of a migration surplus on regional productivity growth. After controlling for human capital, the effect of migration decreases; this decrease indicates that skill selectivity is one way that migration impacts growth.
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Human Capital Mobility and Convergence – A Spatial Dynamic Panel Model of the German Regions
Alexander Kubis, Lutz Schneider
Abstract
Since the fall of the iron curtain in 1989, the migration deficit of the Eastern part of Germany has accumulated to 1.8 million people, which is over ten percent of its initial population. Depending on their human capital endowment, these migrants might either – in the case of low-skilled migration – accelerate or – in high-skilled case – impede convergence. Due to the availability of detailed data on regional human capital, migration and productivity growth, we are able to test how geographic mobility affects convergence via the human capital selectivity of migration. With regard to the endogeneity of the migration flows and human capital, we apply a dynamic panel data model within the framework of β-convergence and account for spatial dependence. The regressions indicate a positive, robust, but modest effect of a migration surplus on regional productivity growth. After controlling for human capital, the effect of migration decreases; this decrease indicates that skill selectivity is one way that migration impacts growth.
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Determinants of Evolutionary Change Processes in Innovation Networks – Empirical Evidence from the German Laser Industry
Muhamed Kudic, Andreas Pyka, Jutta Günther
Abstract
We seek to understand the relationship between network change determinants, network change processes at the micro level and structural consequences at the overall network level. Our conceptual framework considers three groups of determinants – organizational, relational and contextual. Selected factors within these groups are assumed to cause network change processes at the micro level – tie formations and tie terminations – and to shape the structural network configuration at the overall network level. We apply a unique longitudinal event history dataset based on the full population of 233 German laser source manufacturers and 570 publicly-funded cooperation projects to answer the following research question: What kind of exogenous or endogenous determinants affect a firm’s propensity and timing to cooperate and enter the network? Estimation results from a non-parametric event history model indicate that young micro firms enter the network later than small-sized and large firms. An in-depth analysis of the size effects for medium-sized firms provides some unexpected yet quite interesting findings. The choice of cooperation type makes no significant difference for the firms’ timing to enter the network. Finally, the analysis of contextual determinants shows that cluster membership can, but do not necessarily, affect a firm’s timing to cooperate.
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Towards a Theory of Climate Innovation - A Model Framework for Analyzing Drivers and Determinants
Wilfried Ehrenfeld
Journal of Evolutionary Economics,
2013
Abstract
In this article, we describe the results of a multiple case study on the indirect corporate innovation impact of climate change in the Central German chemical industry. We investigate the demands imposed on enterprises in this context as well as the sources, outcomes and determining factors in the innovative process at the corporate level. We argue that climate change drives corporate innovations through various channels. A main finding is that rising energy prices were a key driver for incremental energy efficiency innovations in the enterprises’ production processes. For product innovation, customer requests were a main driver, though often these requests are not directly related to climate issues. The introduction or extension of environmental and energy management systems as well as the certification of these are the most common forms of organizational innovations. For marketing purposes, the topic of climate change was hardly utilized so far. As the most important determinants for corporate climate innovations, corporate structure and flexibility of the product portfolio, political asymmetry regarding environmental regulation and governmental funding were identified.
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Climate Innovation - The Case of the Central German Chemical Industry
Wilfried Ehrenfeld
IWH Discussion Papers,
Nr. 2,
2012
Abstract
In this article, we describe the results of a multiple case study on the indirect corporate innovation impact of climate change in the Central German chemical industry. We investigate the demands imposed on enterprises in this context as well as the sources, outcomes and determining factors in the innovative process at the corporate level. We argue that climate change drives corporate innovations through various channels. A main finding is that rising energy prices were a key driver for incremental energy efficiency innovations in the enterprises’ production processes. For product innovation, customer requests were a main driver, though often these requests are not directly related to climate issues. The introduction or extension of environmental and energy management systems as well as the certification of these are the most common forms of organizational innovations. For marketing purposes, the topic of climate change was hardly utilized so far. As the most important determinants for corporate climate innovations, corporate structure and flexibility of the product portfolio, political asymmetry regarding environmental regulation and governmental funding were identified.
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