We present a new way to model age-specific demographic variables with the example of age-specific mortality in the U.S., building on the Lee-Carter approach and extendingit in several dimensions. We incorporate covariates and model their dynamics jointly with the latent variables underlying...

We implement a long-horizon static and dynamic portfolio allocation involvinga risk-free and a risky asset. This model is calibrated at a quarterly frequencyfor ten European countries. We also use maximum-likelihood estimates andBayesian estimates to account for parameter uncertainty. We nd that...

We present an object-oriented software framework allowing to specify, solve, and estimate nonlinear dynamic general equilibrium (DSGE) models. The implemented solution methods for finding the unknown policy function are the standard linearization around the deterministic steady state, and a...

We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids. The Smolyak operator underlying the sparse grids approach frees global approximation from the curse of dimensionality and we apply it to a Chebyshev approximation of the...

We use a Bayesian dynamic factor model to measure Germanys pre WorldWar I economic activity. The procedure makes better use of existing time seriesdata than historical national accounting. To investigate industrializationwe propose to look at comovement between sectors. We find that...

We analyze the impact of short-run economic fluctuations on age-specific mortality usingBayesian time series econometrics and contribute to the debate on the procyclicality ofmortality. For the first time, we examine the differing consequences of economic changesfor all individual age classes....

This paper analyzes the evolution of the degree of global cyclicalinterdependence over the period 1960-2005. We categorize the 106 countries in oursample into three groups—industrial countries, emerging markets, and other developingeconomies. Using a dynamic factor model, we then decompose...

We systematically examine the comparative predictive performance of a number of alternativelinear and non-linear models for stock and bond returns in the G7 countries. Besides Markovswitching, threshold autoregressive (TAR), and smooth transition autoregressive (STAR) regimeswitching...

In this paper we adopt a principal components analysis (PCA) to reduce the dimensionality of the term structure and employ autoregressive models (AR) to forecast principal components which, in turn, are used to forecast swap rates. Arguing in favor of structural variation, we propose data...