The paper compares the cointegration methods of Johansen and Bierens by means of simulations and a real world example. Drawing on the fact developed in a companion paper that the Johansen procedure has robustness properties against ARMA systems and the Bierens procedure is designed for ARMA...

In systems of variables with a specified or already identified cointegrating rank, stationarity of component variates can be tested by a simple restriction test. The implied decision is often in conflict with the outcome of unit root tests on the same variables. Using a framework of Bayes...

Bivariate time series data often show strong relationships between the two components, while both individual variables can be approximated by random walks in the short run and are obviously bounded in the long run. Three model classes are considered for a time-series model selection problem:...

We use data generated by a macroeconomic DSGE model to study the relative benefits of forecast combinations based on forecast-encompassing tests relative to simple uniformly weighted forecast averages across rival models. Assumed rival models are four linear autoregressive specifications, one of...

Empirical evidence suggests a sharp volatility decline of the growth in U.S. gross domestic product (GDP) in the mid-1980s. Using Bayesian methods, we analyze whether a volatility reduction can also be detected for the German GDP. Since statistical inference for volatility processes critically...

We introduce a multivariate multiplicative error model which is driven by componentspecific observation driven dynamics as well as a common latent autoregressive factor. The model is designed to explicitly account for (information driven) common factor dynamics as well as idiosyncratic effects...

The fixed-b asymptotic framework provides refinements in the use of heteroskedasticity and autocorrelation consistent variance estimators. We show however that the fixed-b limiting distributions of t-statistics are not pivotal when the variance of the underlying data generating process changes...

Motivated by the conjectured existence of trends in the intensity of tropical storms, this paper proposes new inferential methodology to detect a trend in the annual pattern of environmental data. The new methodology can be applied to data which can be represented as annual curves which evolve...

This paper investigates if the impact of uncertainty shocks on the US economy has changed over time. To this end, we develop an extended Factor Augmented VAR model that simultaneously allows the estimation of a measure of uncertainty and its time-varying impact on a range of variables. We find...

We use a factor model with stochastic volatility to decompose the time-varying variance of Macro economic and Financial variables into contributions from country-specific uncertainty and uncertainty common to all countries. We find that the common component plays an important role in driving the...