We examine the global dimension of inflation in 24 OECD countries between 1980 and 2007 in a traditional Phillips curve framework. We decompose output gaps and changes in unit labor costs into common (or global) and idiosyncratic components using a factor analysis and introduce these components...

This paper discusses pooling versus model selection for now- and forecasting in the presence of model uncertainty with large, unbalanced datasets. Empirically, unbalanced data is pervasive in economics and typically due to different sampling frequencies and publication delays. Two model classes...

This paper considers factor forecasting with national versus factor forecasting withinternational data. We forecast German GDP based on a large set of about 500 time series, consisting of German data as well as data from Euro-area and G7 countries. For factor estimation, we consider standard...

We look at how large international datasets can improve forecasts of national activity. We use the case of New Zealand, an archetypal small open economy. We apply "data-rich" factor and shrinkage methods to tackle the problem of efficiently handling hundreds of predictor data series from many...

Die vorliegende Arbeit untersucht, wie sich Angebots-, Nachfrage- und geldpolitische Schocks aus den Vereinigten Staaten auf Deutschland übertragen. Dabei wird ein so genanntes factor-augmented vector autoregressive model (FAVAR) auf einen neu zusammengestellten Datensatz mit mehr als 200...

We propose a Nelson-Siegel type interest rate term structure model where the underlying yield factors follow autoregressive processes with stochastic volatility. The factor volatilities parsimoniously capture risk inherent to the term structure and are associated with the time-varying...

Bayesian nonparametric methods are useful for modeling data without having to define the complexity of the entire model a priori, but rather allowing for this complexity to be determined by the data. Two problems considered in this dissertation are the number of components in a mixture model,...

Dynamic models for credit rating transitions are important ingredients for dynamic credit risk analyses. We compare the properties of two such models that have recently been put forward. The models mainly differ in their treatment of systematic risk, which can be modeled either using discrete...

Using a limiting approach to portfolio credit risk, we obtain analyticexpressions for the tail behavior of the distribution of credit losses. We showthat in many cases of practical interest the distribution of these losses haspolynomial ('fat') rather than exponential ('thin') tails. Our...

When the yield curve is modelled using an affine factor model, residuals may still contain relevant information and do not adhere to the familiar white noise assumption.This paper proposes a pragmatic way to improve out of sample performance for yield curve forecasting. The proposed adjustment...