Data science team

In this paper, we use machine learning techniques to predict whether a company would have left the market in a world without corona. These predictions show that unhealthy companies applied for support less often than healthy companies. But we also show that the COVID-19 support has prevented most exits among unhealthy companies. This indicates that the corona support measures have had a negative impact on productivity growth. →

We compare machine learning techniques to a large Bayesian VAR for nowcasting and forecasting world merchandise trade. We focus on how the predictive performance of the machine learning models changes when they have... →

We study the duration of topics in economics research by looking at how much time passes between publication of textually similar papers.... →

Het strategisch meerjarenonderzoeksplan 2022-2024 (mjop) geeft aan welke onderzoeksambities het CPB heeft. In lijn met dit plan worden de jaarlijkse werkplannen opgesteld, waarin de onderzoeksprojecten die dat jaar... →

In this paper we show that the prediction errors for unemployment vary over the business cycle. We initially use a macroeconomic data for the United States, because these data are available for a longer period than for... →

Dit achtergronddocument beschrijft de gebruikte data en methoden bij de CPB-publicatie ‘Investeren in de arbeidsmarktintegratie van statushouders’. Vanaf 1 januari 2022 krijgen gemeenten weer een regierol bij de... →