ODISSEI Lunchlezing: The Equitability of Policy Interventions: The Dutch Decentralization of the Social Domain

Op donderdag 13 oktober van 12-13 uur geeft Mark Verhagen (Universiteit van Oxford) een online lunchlezing over zijn gebruik van Nederlandse registerdata bij het CBS en machine learning om de effecten te bestuderen van het decentraliseren van regeringstaken: ‘Using Causal Trees and Registry Data to Study the Equitability of Policy Interventions: The Dutch Decentralization of the Social Domain‘.

We nodigen je van harte uit om deze online lezing bij te wonen en meer te weten te komen over registerdata, machine learning en het doen van onderzoek naar de effecten van regeringsbeleid. Na de lezing is er ruimte voor vragen en discussie. Meer informatie over de lezing hieronder (Engels).

Registratie voor dit evenement is gesloten. Als je het nog wil bijwonen, kan je een mail sturen naar communications@odissei-data.nl om de link aan te vragen.


Decentralization of governmental tasks is frequently applied in social care systems, but key questions regarding its merits and risks remain. Chief among them is the question of how the transfer of responsibility from central to local entities affects equity. Existing research often makes use of aggregate measures to study the effects of the decentralisation but those measures do not provide sufficient insights into how an intervention might have differently effected certain groups in the population. As a consequence, those studies do not provide policymakers with the necessary information to fully judge whether the effects of a policy change have been equitable across demographic groups. 

Machine learning methods allow for identification of demographic groups that are reacting differently to a policy intervention and can provide a more complete picture of effects of decentralisation in a population. To illustrate the potential of those methods, Mark Verhagen studies the decentralization of the social domain in The Netherlands, using rich administrative data of Statistics Netherlands (CBS). During his talk, Verhagen will describe the application of causal trees and causal forests methods to address the question of equity of policy interventions. In his study he found considerable heterogeneity in the policy’s effect on social assistance use, both across geographic regions and demographic groups.


Mark Verhagen is a PhD candidate at Nuffield College and the Leverhulme Centre for Demographic Science, University of Oxford. He has a background in Sociology (Oxford) and Econometrics (University of Amsterdam). In his research he applies methods from the domains of machine learning and pattern recognition to answer a wide range of social science questions.


The ODISSEI Lunch Lectures highlight methodological issues and innovations in Social Science.


Foto door AltumCode op Unsplash