We consider the effects of 'precision' screening policies for cancer guided by algorithms. We first show that complex machine learning models can indeed predict cancer better than simpler models that use established risk factors. We then tackle the evaluation challenge: an algorithm that can...

This paper presents a weekly GDP indicator for Switzerland, which addresses the limitations of existing economic activity indicators using alternative high-frequency data created in the wake of the COVID-19 pandemic. The indicator is obtained from a Bayesian mixed-frequency dynamic factor model...

In this paper we evaluate whether the accuracy of Finnish unemployment rate forecasts can be improved by utilising the information in the flows into and out of unemployment. We compare and contrast different methodologies for constructing the flows. Our results indicate that Bayesian vector...

This paper takes stock of the ECB's macroeconometric modelling strategy by focusing on the models and applications used in the Forecasting and Policy Modelling Division. We focus on the guiding principles underpinning the current portfolio of the main macroeconomic models and illustrate how they...