Change point models using hierarchical priors share in the information of each regime when estimating the parameter values of a regime. Because of this sharing, hierarchical priors have been very successful when estimating the parameter values of short-lived regimes and predicting the...

This paper extends the existing fully parametric Bayesian literature on stochastic volatility to allow for more general return distributions. Instead of specifying a particular distribution for the return innovation, we use nonparametric Bayesian methods to flexibly model the skewness and...

Empirical volatility studies have discovered nonstationary, long-memory dynamics in the volatility of the stock market and foreign exchange rates. This highly persistent, infinite variance - but still mean reverting - behavior is commonly found with nonparametric estimates of the fractional...

This paper investigates both cross-sectional asymmetry (related to bank-speci.c characteristics like size and liquidity) and asymmetries over time (potentially related to the overall state of the economy) in Austrian bank lending reaction to monetary policy. The first type of asymmetry is...

The purpose of this paper is to analyze the efficiency of the 26 Swiss cantons over the period 2000 to 2004 applying Data Envelopment Analysis (DEA). A Total Public Sector Performance (TPSP) indicator for eight local government activities (administration, public safety, education, culture and...

The purpose of this paper is to analyze the optimal scale of local jurisdictions (cantons) in Switzerland applying Data Envelopment Analysis (DEA) to the years 2000 to 2004. Aggregate output performance indicators for four local government activities (administration, education, health, and...

This paper develops a heterogeneous agents segmented markets model with endogenous production and a monetary authority that follows a Taylor-type interest rate rule. The model is estimated using Markov chain Monte Carlo techniques and is evaluated as a framework suitable for empirical monetary...

Prepared for the Handbook of Economic Forecasting, vol 2 This chapter reviews Bayesian methods for inference and forecasting with VAR models. Bayesian inference and, by extension, forecasting depends on numerical methods for simulating from the posterior distribution of the parameters and spe-...

This paper considers Bayesian inference procedures for regression models with ordinally observed explanatory variables. Taking advantage of a latent variable interpretation of the ordinally observed variable we develop an efficient Bayesian inference procedure that estimates the regression model...

We propose a general class of multivariate fat-tailed distributions which includes the normal, t and Laplace distributions as special cases as well as their mixture. Full conditional posterior distributions for the Bayesian VAR-model are derived and used to construct a MCMC-sampler for the joint...