This book addresses from a methodological perspective a research problem, how to forecast the international migration component in a way that could be then used for population forecasts using the probabilistic approach. All forecasts are made in the conditions of uncertainty, which is an...

We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model is calibrated at a quarterly frequency for ten European countries. We also use maximum-likelihood estimates and Bayesian estimates to account for parameter uncertainty. We find...

State space models play a key role in the estimation of time-varying sensitivities in financial markets. The objective of this book is to analyze the relative merits of modern time series techniques, such as Markov regime switching and the Kalman filter, to model structural changes in the...

It is well known that the correlation between financial series varies over time. Here, the forecasting performance of different time-varying correlation models is compared for cross-country correlations of weekly G5 and daily European stock market indices. In contrast to previous studies only...

For the Euro 2000 Soccer Championships an experimental asset market was condueted, with traders buying and selling contracts on the winners of individual matches. Market-generated probabilities are compared to professional bet quotas, and factors that are responsible for the quality of the...