The two-dimensional circular structure model by Kauermann, Teuber, and Flaschel (2011) will be extended to estimate more than two time series simultaneously. It will be assumed that the multivariate time series follow a cycle over the time. However, the radius and the angle are allowed to...

Various forms of instability can be observed in macroeconomic and financial data including changes in variance, changes in cycle properties, or both. Traditional tests do not allow to distinguish between these different cases. This paper proposes and compares two alternative approaches. The...

Business cycles, the ups and downs observed somewhat simultaneously in numerous macroeconomic variables in an economy and often measured using real GDP, are important and, despite much economic research, still incompletely understood. A method for ex-post dating of the business cycle in the Euro...

The main objective of this paper is to assess how mutual information as a measure of global dependence between stock markets and macroeconomic factors can overcome some of the weaknesses of the traditional linear approaches commonly used in this context. One of the advantages of mutual...

We introduce a flexible copula-based semi-parametric test of financial contagion that is capable of capturing structural shifts in the transmission channel of shocks across a network of financial markets beyond the increase in the intensity of time-varying dependence. We illustrate the...

This paper develops a testing framework for comparing the predictive accuracy of competing multivariate density forecasts with different predictive copulas, focusing on specific parts of the copula support. The tests are framed in the context of the Kullback–Leibler Information Criterion,...

This paper investigates the dynamic causal link between exports and economic growth using both linear and nonlinear Granger causality tests. We use annual South African data on real exports and real gross domestic product from 1911-2011. The linear Granger causality result shows no evidence of...

In the presence of heteroscedasticity and autocorrelation of unknown forms, the covariance matrix of the parameter estimator is often estimated using a nonparametric kernel method that involves a lag truncation parameter. Depending on whether this lag truncation parameter is specified to grow at...

Multiple time series data may exhibit clustering over time and the clustering effect may change across different series. This paper is motivated by the Bayesian non-parametric modelling of the dependence between clustering effects in multiple time series analysis. We follow a Dirichlet process...

Since the pioneering work by Granger (1969), many authors have proposed tests of causality between economic time series. Most of them are concerned only with “linear causality in mean”, or if a series linearly affects the (conditional) mean of the other series. It is no doubt of primary...