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...

To date, empirical investigations of trade liberalization under the conditions of increasingreturns to scale (IRS) and imperfect competition (IC) have either assumed or imposed themarket and productive structures necessary for such a model. However, of the recent IRS/ICmodels used to simulate...

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...

Estimation risk is known to have a huge impact on mean/variance (MV) optimized portfolios,which is one of the primary reasons to make standard Markowitz optimization unfeasible inpractice. Several approaches to incorporate estimation risk into portfolio selection are suggestedin the earlier...

This paper introduces an expected value estimator with expert knowledge to the robust estimation of sovereign rating transitions which are characterised by few observations. Ourestimates of default premia within Mexican, Colombian and Brazilian Eurobond yield spreads provide a better fit than...

Bayesian Model Averaging (BMA) has recently been discussed in the financial literature as an effective way to account for model uncertainty. In this paper we compare BMA to a new model uncertainty framework introduced by Yang (2004), called Aggregate Forecasting Through Exponential Reweighting,...

In the social sciences, it is often useful to introduce latent variables and usestructural equation modeling to quantify relations among observable and latentvariables. Data gathered through surveys is frequently ordinal in nature, asLikert-scale type questions are used in most questionnaires....