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In the aftermath of the global financial crisis, the state of macroeconomic modeling 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.
We investigate the decisions of listed firms to go private once again. We start by revealing that while a significant number of firms which go public is VC-backed, an overproportional share of these VC-backed firms go private later on (they stay on the exchange for an average of 8.5 years). We interpret this very robust pattern such that IPOs of VC-backed firms are to a large extent a temporary rather than a permanent feature of the corporate governance of these firms. We investigate various potential hypotheses why VCs actually seem to be able to bring marginal firms to the exchange by relating the going-private decisions to various characteristics of the IPO market as well as to VC characteristics. We find strong support for the certification ability of VCs: more experienced and reputable VCs are more able to bring marginal firms to public exchanges via an IPOs. These marginal firms backed-by more reputable and experienced VCs are more likely to go private later on. Hence, our analysis suggests that IPOs backed by experienced VCs are most likely to be a temporary rather than the final stage in the life of the portfolio firm. We find no support that reputable VCs underprice their IPO-exits more implying that they have no need to leave more money on the table to take the marginal firms public.
Die vorliegende Arbeit beschäftigt sich mit der zeitstetigen Portfoliooptimierung sowie mit Themen aus dem Bereich des Kreditrisikos. Das Ziel der Portfoliooptimierung ist es, zu einem gegebenen Anfangskapital die bestmöglichen Konsum- und Investmentstrategien zu finden. In dieser Arbeit wird dabei vor allem der Einfluss von Einkommen auf diese Entscheidungen untersucht. Da einerseits jedoch der zukünftige Einkommensstrom vom Zufall bestimmt ist und es andererseits keine Finanzprodukte gibt, die diesen replizieren können, stellt die Einbindung von Einkommen in die Portfoliooptimierung ein großes Problem dar. Es führt dazu, dass die Annahmen eines vollständigen Marktes nicht weiter gelten, so dass die Standardmethoden zur Lösung nicht angewendet werden können. Diese Arbeit analysiert mehrere Ausprägungen dieses Problems und geht auf verschiedene Verfahren zur Lösung ein. Weiterhin untersucht diese Studie den Einfluss des Kreditrisikos einer Firma auf die jeweilige Firmenrendite. Dabei wird vor allem auf eine Anomalie, die bereits umfassend in der Literatur diskutiert wurde, Bezug genommen. Diese Anomalie besagt, dass Firmen mit hohen Ausfallwahrscheinlichkeiten geringere Renditen erwirtschaften als Firmen mit kleineren Ausfallwahrscheinlichkeiten. Eine weitere Frage, die in den Bereich des Kreditrisikos fällt, ist die Frage, inwieweit Modelle dazu in der Lage sind, strukturierte Produkte zu bewerten und abzusichern. Diese Arbeit versucht Antworten darauf zu geben.