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Predicting Firm Exits with Machine Learning: Implications for Selection into COVID-19 Support and Productivity Growth
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. →

Wealth, gifts, and estate planning at the end of life
We show that gifts made to heirs before death are substantial and highly responsive to taxation. Therefore, characterising them and understanding their determinants is crucial for tax design. We use high-quality, intergenerationally-linked data on wealth, gifts, and medical expenses from the Netherlands. Exploiting variation in the timing of death, we find that the wealthiest half of singles (including widows) with children transfer over 10% of their wealth to their children in anticipation of death. Giving is highly sensitive to how heavily gifts are taxed, relative to bequests. →

Temporal Patterns in Economics Research
Can skill differences explain the gap in the track recommendation by socio-economic status?
Tracking early in the school career can influence a student's further educational path significantly. We study the track advice at the end of primary school in the Netherlands, where teachers give a track advice based on a student's previous performance and their impression of the student's ability. →
