development of adjacent age groups is assured allowing for consistent forecasts. We develop an appropriate Markov Chain Monte … Carlo algorithm to estimate the parameters and the latent variables in an efficient one-step procedure. Via the Bayesian …

estimate a Markov switching VAR for the euro area and the US, including additionally GDP, CPI and a short-term interest rate …

This paper investigates the merger wave hypothesis for the US and the UK employing a Markov regime switching model …

multivariate GARCH model has undesirable properties for the Monte Carlo simulations and involves estimating a large number of …, but also quite easy using Monte Carlo simulations. My methodology to estimate covariance matrices is preferable to … alternatives like estimating a multivariate GARCH model or using a Nadaraya-Watson estimator for the following reasons: The …

We analyze the impact of short-run economic fluctuations on age-specific mortality using Bayesian time series …

the underlying yield factors. We propose a Markov chain Monte Carlo (MCMC) algorithm to efficiently estimate the SVNS …In this paper, we develop and apply Bayesian inference for an extended Nelson-Siegel (1987) term structure model … work efficiently and is easily adapted to alternative specifications of dynamic factor models revealing (multivariate …

chain Monte Carlo algorithm to estimate the parameters and the latent variables in an efficient one-step procedure. Via the … similar development of adjacent age groups is assured, allowing for consistent forecasts. We develop an appropriate Markov … Bayesian approach we are able to assess uncertainty intuitively by constructing error bands for the forecasts. We observe that …

using Markov chain Monte Carlo techniques. …A Bayesian model averaging procedure is presented that makes use of a finite mixture of many model structures within …

macroeconomic time series. The coincident economic indicator is based on a multivariate trend-cycle decomposition model that … account for all the heteroskedasticity present in the data. The empirical results are based on a Bayesian analysis and show …

posterior inference of a basic PC model are analyzed using a Bayesian simulation based approach. Next, structural time series … favorably with existing Bayesian Vector Autoregressive and Stochastic Volatility models in terms of fit and predictive …