In customer relationship management, practitioners are often faced with the task of valuing customers in terms of inter-purchase times and purchase quantities. Some customers represent steady revenue streams, while others exhibit a great deal of variation in their interaction with a firm through...

This paper builds an innovative composite world trade cycle index (WTI) by means of a dynamic factor model to monitor and perform short-term forecasts in real time of world trade growth of both goods and (usually neglected) services. The selection of trade indicator series is made using a...

This paper builds an innovative composite world trade cycle index (WTI) by means of a dynamic factor model to perform short-term forecasts of world trade growth of both goods and (usually neglected) services. The selection of trade indicator series is made using a multidimensional approach,...

We propose new forecast combination schemes for predicting turning points of business cycles. The combination schemes deal with the forecasting performance of a given set of models and possibly providing better turning point predictions. We consider turning point predictions generated by...

This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In the empirical application, we forecast U.S. business cycle turning points with state-level employment data. We find that forecasts...

Historically, time series forecasts of economic variables have used only a handful of predictor variables, while forecasts based on a large number of predictors have been the province of judgmental forecasts and large structural econometric models. The past decade, however, has seen considerable...

This paper compares within-sample and out-of-sample fit of a DSGE model with rational expectations to a model with adaptive learning. The Galí, Smets and Wouters model is the chosen laboratory using quarterly real-time euro area data vintages, covering 2001Q1-2019Q4. The adaptive learning model...

To date, only annual information on economic activity is published for the 16 German states. In this paper, we calculate quarterly regional GDP estimates for the period between 1995 to 2021, thereby improving the regional database for Germany. The new data set will regularly be updated when...

We propose new forecast combination schemes for predicting turning points of business cycles. The combination schemes deal with the forecasting performance of a given set of models and possibly providing better turning point predictions. We consider turning point predictions generated by...

This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms