Interactions between eurozone and United States booms and busts and among major eurozone economies are analyzed by introducing a panel Markov-switching VAR model. The model is well suitable for a multi-country cyclical analysis and accommodates changes in low and high data frequencies and...

Interactions between the eurozone and US booms and busts and among major eurozone economies are analyzed by introducing a panel Markov-switching VAR model well suitable for a multi-country cyclical analysis. The model accommodates changes in low and high data frequencies and endogenous...

Patton and Timmermann (2012, 'Forecast Rationality Tests Based on Multi-Horizon Bounds', Journal of Business & Economic Statistics, 30(1) 1-17) propose a set of useful tests for forecast rationality or optimality under squared error loss, including an easily implemented test based on a...

Patton and Timmermann (2012, 'Forecast Rationality Tests Based on Multi-Horizon Bounds', <I>Journal of Business & Economic Statistics</I>, 30(1) 1-17) propose a set of useful tests for forecast rationality or optimality under squared error loss, including an easily implemented test based on a...</i>

Patton and Timmermann (2011, 'Forecast Rationality Tests Based on Multi-Horizon Bounds', <I>Journal of Business & Economic Statistics</I>, forthcoming) propose a set of useful tests for forecast rationality or optimality under squared error loss, including an easily implemented test based on a...</i>

Patton and Timmermann (2011, 'Forecast Rationality Tests Based on Multi-Horizon Bounds', Journal of Business & Economic Statistics, forthcoming) propose a set of useful tests for forecast rationality or optimality under squared error loss, including an easily implemented test based on a...

A flexible predictive density combination model is introduced for large financial data sets which allows for dynamic weight learning and model set incompleteness. Dimension reduction procedures allocate the large sets of predictive densities and combination weights to relatively small sets....

A flexible predictive density combination is introduced for large financial data sets which allows for model set incompleteness. Dimension reduction procedures that include learning allocate the large sets of predictive densities and combination weights to relatively small subsets. Given the...

Several Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time series....