Using a uniquely compiled database concerning rental prices of commercial real estates, which are property of the largest broker in the Netherlands, we examine whether these prices have predictive value for quarterly economic growth. In contrast to related studies, we document that the mean...

In this article it is advocated to select a model only if it significantly contributes to the accuracy of a combined forecast. Using hold-out-data forecasts of individual models and of the combined forecast, a useful test for equal forecast accuracy can be designed. An illustration for real-time...

This note gives a few practical guidelines for cointegration analysis. The focus is on testing the cointegration rank in a VAR model and on how an intercept and a trend should be incorporated in the testing model. Only two cases appear relevant for most economic data.

We develop a panel model for regional house prices, for which both the cross-section and the time series dimension is large. The model allows for stochastic trends, cointegration, cross-equation correlations and, most importantly, latent-class clustering of regions. Class membership is fully...

We demonstrate that the Data Generating Process (DGP) of China's cumulated quarterly Gross Domestic Product (GDP, current prices), as it is reported by the National Bureau of Statistics of China (NBSC), can be (very closely) approximated by a simple rule. This rule says that the annual growth in...

In this article, we correlate the key features of the distribution of wealth of the 500 wealthiest individuals in the Netherlands with economic growth and stock market returns for the period 1998 to 2009. We show that each year the distribution obeys a power law and that the key parameter...

This article seeks to find an answer to the question: 'How many stamps are still around, given that we know their prices at issue, the current price and the amount then issued?' For this purpose, I develop a simple statistical model, the parameters of which are estimated for over 1000 postwar...