Mark Kattenberg

Programmaleider, Sector 4 Marktordening en zorg
Photo of Mark Kattenberg
Centraal Planbureau

Bezuidenhoutseweg 30
2594 AV Den Haag


Publications

November 28, 2023

Causal forests with fixed effects for treatment effect heterogeneity in difference-in-differences

Recently developed heterogeneity-robust two-way fixed effects (TWFE) estimators do not quantify the full heterogeneity in treatment effects in a difference-in-differences research design....

November 28, 2023

Hoe economische effecten te schatten voor individuen bij difference-in differences

Het schatten van het effect van economisch beleid vormt een belangrijk onderdeel van economisch onderzoek. Vaak richt onderzoek zich daarbij op het gemiddelde effect, maar beleidsmakers willen ook inzicht of bepaalde...

July 5, 2023

Rechtvaardige algoritmes

Het is mogelijk om een selectie-algoritme representatiever keuzes te laten maken. Het is dan nodig dat van tevoren goed wordt nagedacht over de verhoudingen waarin verschillende groepen in de selectie worden opgenomen.

computer screen
March 1, 2023

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.

Corona
October 4, 2022

Forecasting World Trade Using Big Data and Machine Learning Techniques

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...