We extract tone-adjusted, time-varying and hierarchically ordered topics from a large corpus of Dutch financial news and investigate whether these topics are useful for monitoring the business cycle and nowcasting GDP growth in the Netherlands. The financial newspaper articles span the period...

We conduct a systematic comparison of the short-term forecasting abilities of eleven statistical models and professional analysts in a pseudo-real time setting, using a large set of monthly indicators. Our analysis covers the euro area and its five largest countries over the years 1996-2011. We...

We investigate to what extent it is feasible to improve model-based near-term GDP forecasts by combining them with judgmental (quarterly) forecasts by professional analysts (Consensus survey) in a real-time setting. Our analysis covers the G7 countries over the years 1999-2013. We consider as...

This paper examines the accuracy of short run forecasts of Dutch GDP growth by several linear statistical models and private sector analysts. We focus on the financial crisis of 2008-2009 and the dot-com recession of 2001-2002. The dynamic factor model turns out to be the best model. Its...

This paper compares the ability of several econometric and machine learning methods to nowcast GDP in (pseudo) real-time. The analysis takes the example of Dutch GDP over the years 1992-2018 using a broad data set of monthly indicators. It discusses the forecast accuracy but also analyzes the...