• Graduate Program
    • Why study Business Data Science?
    • Research Master
    • Admissions
    • Facilities
    • Browse our Courses
    • PhD Vacancies
  • Research
  • Browse our Courses
  • Events
    • Events Calendar
    • Events archive
    • Tinbergen Institute Lectures
    • Summer School
      • Deep Learning
      • Economics of Blockchain and Digital Currencies
      • Foundations of Machine Learning with Applications in Python
      • Machine Learning for Business
      • Marketing Research with Purpose
      • Sustainable Finance
      • Tuition Fees and Payment
      • Tinbergen Institute Summer School Program
    • Annual Tinbergen Institute Conference archive
  • News
  • Alumni
Home | News | Max Coveney, Aksel Erbahar, Anita Kopányi-Peuker, Chen Li and Julia Rose awarded with NWO Open Competition SSH XS grant
News | December 11, 2025

Max Coveney, Aksel Erbahar, Anita Kopányi-Peuker, Chen Li and Julia Rose awarded with NWO Open Competition SSH XS grant

Fellows Max Coveney, Aksel Erbahar, Anita Kopányi-Peuker, Chen Li and Julia Rose have been awarded an XS grant of up to 50,000 euro by the Dutch Research Council (NWO), in the Call for the Open Competition – Domain Social Sciences and Humanities.

Max Coveney, Aksel Erbahar, Anita Kopányi-Peuker, Chen Li and Julia Rose awarded with NWO Open Competition SSH XS grant

The NWO Open Competition SSH XS Call is specifically intended to encourage curiosity-driven and bold research that involves the relatively rapid exploration of a promising idea (12 months maximum). The research projects must be ground-breaking and are high risk-high gain. Most important is that the result of each project contributes to the advancement of science.

Awarded projects

Max Coveney
Project: Improving school tracking decisions with machine learning predictions

Schools place pupils into tracks (VMBO/HAVO/VWO). These choices shape study and work opportunities, yet initial placements can be inaccurate, leading to costly switches. This project tests whether a transparent algorithm—trained on primary-school learning trajectories—can shed light on the sources of misallocation and lead to more accurate placement decisions. Using anonymised Dutch education data, the study compares the algorithm’s recommendations with actual placements, quantifies potential gains and trade-offs for different groups, and highlights student characteristics associated with misallocation

Aksel Erbahar
Project: Internal Bridges or National Walls? Home Bias in EU Defence Spending

In 2023, the European Union spent €279 billion on defence, yet about three-quarters of this spending went to non-EU suppliers. The European Defence Industrial Strategy (EDIS) mandates 50% EU sourcing by 2030, but risks creating national walls instead of internal bridges. This research examines whether EU governments, shifting from non-EU suppliers, increasingly favour domestic over other EU firms—a “home bias” that could fragment Europe when unity is needed most. Using government-to-firm procurement data across three periods, I test if security shocks and policies designed to reduce external dependence undermine internal integration, directly informing the 2027 EDIS review.

Anita Kopányi-Peuker
Project: Price efficiency and price manipulation: the effect of different closing auction designs in call markets

The closing auction determines the ‘closing price’ in asset markets. These prices affect the distribution of crucial resources, such as corn or oil, with potentially severe consequences for the world population. In practice auctions might differ in several aspects at the same time, making it more difficult to investigate the separate design effects on price efficiency and manipulation. This project provides a clean comparison among three auction designs by using controlled laboratory experiments. The results provide a better understanding of how market design affects closing prices, providing insights to market designers and regulators on which auction design to implement.

Chen Li
Project: She is aggressive and he deserves better: gendered effects of anger expression on negotiation outcomes

While strategic emotional displays like anger can improve negotiation outcomes, they are often perceived negatively when expressed by women. This project investigates this hidden penalty by integrating the Emotions as Social Information (EASI) theory into a behavioral economics model. Through a controlled experiment, it will quantify how emotional expressions from men and women differentially affect proposers' beliefs, tastes, and attitudes. It will decompose the welfare costs of this gendered effect, moving beyond simplistic prescriptions to provide a nuanced understanding of the emotional underpinnings of the gender negotiation gap.

Julia Rose
Project: Image Investing

Despite the well-known benefits of stock market participation, many households still choose not to invest. While barriers like limited financial literacy and risk perception have received much attention, recent research shows that moral and reputational concerns also play a significant role. This project examines whether Socially Responsible Investing can address these concerns by enabling individuals to align investments with their social or ethical values. Through innovative experiments, I investigate how visible signals of social responsibility shape participation and market outcomes. The results help policymakers and financial institutions to design practical tools that empower individuals and promote socially responsible financial engagement.

View all Granted projects 2025 Round 3