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Im Zentrum dieser Dissertation steht das Beschreiben und Erklären von Konjunkturdynamiken. Motiviert durch den außerordentlich starken wirtschaftlichen Einbruch in 2008/2009 betont die Arbeit dabei die Wichtigkeit der Nutzung von nichtlinearen Modellansätzen. Die Dissertation kann als Beitrag...
Persistent link: https://www.econbiz.de/10012154125
The COVID-19 pandemic has led to enormous data movements that strongly affect parameters and forecasts from standard VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine transitory and persistent changes in volatility. The resulting...
Persistent link: https://www.econbiz.de/10013184356
This paper considers an institutional investor who is implementing a long-term portfolio allocation strategy using forecasts of financial returns. We compare the performance of two competing macro-finance models, an unrestricted Vector AutoRegression (VAR) and a fully structural Dynamic...
Persistent link: https://www.econbiz.de/10011515898
This paper investigates the predictive properties of import and export prices of commodities on the exchange rates. A period from 1993 to 2016 is considered. We find that forecasts of the exchange rate adding commodity export and import prices are superior to those neglecting these variables....
Persistent link: https://www.econbiz.de/10011822076
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nominal shocks as well as shocks to aggregate supply and aggregate demand. In contrast to previous analyses of such …, the decomposition suggests that exchange rate variability is mostly driven by shocks to aggregate demand, partcularly in …
Persistent link: https://www.econbiz.de/10010494184
We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...
Persistent link: https://www.econbiz.de/10011389735
This paper investigates the ability of several generalized Bayesian vector autoregressions to cope with the extreme COVID-19 observations and discusses their impact on prior calibration for inference and forecasting purposes. It shows that the preferred model interprets the pandemic episode as a...
Persistent link: https://www.econbiz.de/10013472790
We propose a new variational approximation of the joint posterior distribution of the log-volatility in the context of large Bayesian VARs. In contrast to existing approaches that are based on local approximations, the new proposal provides a global approximation that takes into account the...
Persistent link: https://www.econbiz.de/10014351940
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