Please also see my papers at SSRN (click here).

Revised February 2026 (CESifo Working Paper No. 11832, March 2025)

We conduct an artefactual field experiment in real-existing trade networks to analyze how individual network degree affects bargaining demands and outcomes. We combine data from a bilateral bargaining experiment with data of trade networks in 24 villages in Uganda. To identify the effect of individual degree in the village trade network we experimentally vary the disclosure of participants’ identities in a bargaining pair. We state hypotheses on how degree will affect behavior and find partial support for them. Specifically, we observe that individual degree affects bargaining demands in the predicted direction when one of the bargainers is informed about the network positions but not when either no or both sides are informed. Moreover, network degree affects the likelihood of agreements and earnings, irrespective of the knowledge of the network positions of bargaining partners.
:: Available at SSRN Download paper.

Revised October 2025 (CESifo Working Paper No. 10595, July 2023)

We investigate how preferences have been affected by exposure to the COVID-19 crisis. Our main contributions are: first, our participant pool consists of a large general population sample; second, we elicited a wide range of preferences (risk, time, ambiguity, and social preferences) using different incentivized experimental tasks; third, we elicited preferences before the onset of the crises and in three additional waves during the crises over a time period of more than a year, allowing us to investigate both short-term and medium-term preference responses; fourth, besides the measurement of causal effects of the crisis, we also analyze within each wave during the crisis, how differential exposure to the crisis in the health and financial domain affects preferences. We find that preferences remain remarkably stable during the crisis. Comparing them before the start and during the crisis, we do not observe robust differences in any of the elicited preferences. Moreover, individual differences in the exposure to the crisis at best show only weak effects in the financial domain.
:: Available at SSRN Download paper.

CESifo Working Paper No. 12195, August 2025

In a laboratory experiment, we study the role of fairness ideals as focal points in coordination problems in homogeneous and heterogeneous groups. We elicit the normatively preferred behavior about how a subsequent coordination game should be played. In homogeneous groups, people share a unique fairness ideal how to solve the coordination problem, whereas in heterogeneous groups, multiple conflicting fairness ideals prevail. In the coordination game, homogeneous groups are significantly more likely than their heterogeneous counterparts to sustain efficient coordination. The reason is that homogeneous groups coordinate on the unique fairness ideal, whereas heterogeneous groups disagree on the fairness ideal to be played. In both types of groups, equilibria consistent with fairness ideals are most stable. Hence, the difference in coordination success between homogeneous and heterogeneous groups occurs because of the normative disagreement in the latter types of group, making it much harder to reach an equilibrium at a fairness ideal.
:: Available at SSRN Download paper.

CESifo Working Paper No. 12102, August 2025

We conduct an online experiment to study how the unfairness of chances leading to wage inequality affects labor supply decisions. We find that, at a given wage, disadvantageous wage inequality reduces labor supply, but whether this inequality stems from fair or unfair chances does not matter. That is, a procedure with fair chances does not compensate for wage inequality. Our results stand in stark contrast to prior empirical evidence showing that individuals care about fair chances when making equity judgments.
:: Available at SSRN Download paper.

CESifo Working Paper No. 11841; April 2025

Using an artefactual field experiment, we elicit revealed preferences for solidarity of different age groups towards the same and other age groups among a large and heterogeneous sample of the Dutch population. Preferences are elicited with a solidarity game and linked to a rich and unique administrative database, enabling us to explore demographic and socio-economic correlates of the elicited preferences. In the solidarity game a winner of a money amount is asked ex-ante how much they are willing to transfer to a loser who receives no money. We find that participants on average have a strong preference for ex-ante solidarity, as they are willing to transfer about 40% of the money they receive. At the same time, there is a mismatch between belief in solidarity and actual solidarity. Participants are overly pessimistic about what others will transfer. Moreover, we observe age-based discrimination because a significant share of participants exhibits stronger solidarity preferences with their own age group than with other age groups. Using questionnaires, we also measure stated solidarity preferences in various domains and observe that revealed solidarity preferences correlate with some self-reported attitudes about general solidarity. We also correlate revealed solidarity preferences with opinions on social security systems and self-reported field behavior involving solidarity and find some relation between them.
:: Available at SSRN Download paper.
This paper has formerly been circulated as Netspar Design Paper No. 128; 2019

CESifo Working Paper No. 10932, January 2024 (Reject & Resubmit The Economic Journal)

We investigate experimentally how the menstrual cycle affects bargaining behavior and bargaining outcomes of women. Female participants negotiate in an unstructured bilateral bargaining game with asymmetric information about the allocation of a surplus ('pie size'). We find that the menstrual cycle affects bargaining behavior and that the effects depend on players’ information. Players who are informed about the pie size are less compromising during ovulation and receive higher payoffs conditional on reaching an agreement. Uninformed players achieve higher final payoffs during ovulation, which is mainly driven by higher agreement rates. Our study provides first evidence that biological factors affect bargaining.
:: Available at SSRN Download paper.

Netspar Design Paper No. 183; September 2021

The pension industry, much like the rest of the financial industry, is increasingly adopting data science and artificial intelligence-based solutions. Applications range from leaner and faster operations (“doing the same thing better”) to completely new value propositions. However, the available literature suggests that the pension industry appears to be relatively conservative and cautious when it comes to adopting new and dynamically changing machine learning (ML) techniques. The black box nature of most ML techniques also appears to contribute to the skepticism of the pension sector. Hence, there seems to be a gap between the potential applications of data science solutions proposed by researchers and their application in the pension industry. This article provides (i) a review of what has been reported in the data science literature, (ii) a taxonomy of ML techniques that can be applied for challenges in the pension industry, and (iii) a categorization of the different aspects of the pension industry that are covered in state-of-the-art applied data science.
We surveyed 25 papers and presentations on the application of data science in the pension industry and highlight the major machine learning techniques that were used and their applicability in the pension sector. These techniques are concisely introduced to provide a basis for stakeholders to gain an understanding of their potential applicability to tackle challenges in the pension industry. Based on the existing research, three areas of the pension industry are identified as most relevant for the application of machine learning techniques: customer focus, organizational process optimization, and personnel optimization. Open issues and further opportunities regarding the application of data science in the pension sector are discussed.
We surveyed the existing body of literature to summarize how data science is being currently leveraged to deal with issues related to pensions. Prominent developments appear along the fronts of prediction and chatbot development. Our analysis suggests that there remains ample room in the pension industry to explore the use of other machine learning and data mining methodologies, such as clustering, natural language processing, and reinforcement learning. This includes gleaning insights from unconventional sources such as social media activity, and developing new customer-focused and business development applications.
:: Available at Netspar Download paper.

Netspar Survey Paper No. 58; July 2021

Many economic and financial decisions involve risk. A crucial question in this context is how much risk people are willing to take. The importance of measuring the willingness of people to take risk is acknowledged by Dutch law, which requires financial institutions to take into account their customers' risk preferences when offering products and services. Additionally, knowledge of participants’ risk preferences play an important role in the recent pension agreement in the Netherlands, since it requires pension providers to invest in line with the age composition and risk attitudes of participants. Here we discuss the concept of risk preferences and common ways to measure them as proposed in the economics literature. We summarize traditional and behavioral economics perspectives on decisions under risk. Next, we present several incentivized experimental measures and non-incentivized survey measures of risk preferences and describe how they correlate with field behavior, and we discuss advantages and disadvantages of the different methods. We also discuss what is known, according to the economics literature, about the relationship between risk preferences and age.
:: Available at Netspar Download paper.
:: Media coverage Pensioen Pro PDF

CESifo Working Paper No. 8809, IZA Discussion Paper No. 13991; December 2020

The gender gap in income and leadership positions in many domains of our society is an undisputed pervasive phenomenon. One explanation for the disadvantaged position of women put forward in the economic and psychology literature is the weaker response of women to competitive incentives. Despite the large amount of literature trying to explain this fact, the precise mechanisms behind the gender difference in competitive responsiveness are still not fully uncovered. In this paper, we use laboratory experiments to study the potential role of stereotype threat on the response of men and women to competitive incentives in mixed-gender competition. We use a real effort math task to induce an implicit stereotype threat against women in one treatment. In additional treatments we, respectively, reinforce this stereotype threat and induce a stereotype threat against men. In contrast to much of the literature we do not observe that women are less competitive than men, neither when there is an implicit nor when there is an explicit stereotype threat against women. We attribute this to two factors which differentiates our experiment from previous ones. We control, first, for inter-individual performance differences using a within-subject design, and, second, for risk differences between non-competitive and competitive environments by making the former risky. We do find an adverse stereotype threat effect on the performance of men when there is an explicit stereotype threat against them. In that case any positive performance effect of competition is nullified by the stereotype threat. Overall, our results indicate that a stereotype threat has negative competitive performance effects only if there is information contradicting an existing stereotype. This suggests that the appropriate intervention to prevent the adverse effect of stereotype threat in performance is to avoid any information referring to the stereotype.
:: Available at SSRN Download paper.

arXiv:1908.02287, 2019

In this paper we present our preliminary work on monitoring data License accoUntability and CompliancE (LUCE). LUCE is a blockchain platform solution designed to stimulate data sharing and reuse, by facilitating compliance with licensing terms. The platform enables data accountability by recording the use of data and their purpose on a blockchain-supported platform. LUCE allows for individual data to be rectified and erased. In doing so LUCE can ensure subjects' General Data Protection Regulation's (GDPR) rights to access, rectification and erasure. Our contribution is to provide a distributed solution for the automatic management of data accountability and their license terms.
:: Available at arXiv.org Download paper.

GSB_RM13034, 2013 (revised June 2017)

We elicit reciprocal preferences in a firm-worker gift-exchange setting and relate them to actual behavior in a repeated gift-exchange game. We find that only a small minority of 10 percent of workers is materially selfish whereas 90 percent exhibit reciprocal preferences. However, the intensity of reciprocal preferences is weak in the sense that firms maximize profits by not relying on gift-exchange but by offering the lowest possible wage. Workers behavior in the repeated gift-exchange game is predicted by their elicited preferences, but the correlation between preferences and behavior is imperfect. Together with profit maximizing behavior of firms these observations can explain the observed unraveling of gift-exchange over time in our experiment and some recent field experiments.
:: Download paper.

Maastricht University, GSBE Research Memorandum No. 16024, 2016

Social identity has been shown to successfully enhance cooperation and effort in cooperation and coordination games. Little is known about the causal effect of social identity on the propensity to engage in group conflict. In this paper we explore theoretically and experimentally whether social identity increases investments in group contests. We show theoretically that increased social identity with the own group implies higher investments in Tullock contests. Empirically we find that induced social identity does increase group closeness but does not increase conflict investments.
:: Download paper.

(July 2013)

To accurately predict behavior economists need reliable measures of individual time preferences and attitudes toward risk and typically need to assume stability of these characteristics over time and across decision domains. We test the reliability of two choice tasks for eliciting discount rates, risk aversion, and probability weighting and assess the stability of these characteristics over time and across situations. We find high reliability and that individual characteristics are remarkably stable over time. The estimated parameters correlate well with self-reported decisions in financial domains, but are largely uncorrelated with decisions in other important life domains involving intertemporal trade-offs and risk.
:: Download paper.

(revised December 2008; first version: April 2004)
An abridged version of this paper is published in Journal of Public Economics under the title
We study the effects of competition in a context in which people's actions can not be contractually fixed. We find that in such an environment the very presence of competition does neither increase efficiency nor does it yield any payoff gains for the short side of the market. We also find that competition has a strong negative impact on social well-being, the disposition towards others, and individually experienced well-being, the emotional state, of those on the long side of the market. We conjecture that this limits the possibilities of satisfactory interaction in the future and, hence, has negative implications for efficiency in the longer-run.
:: Download paper. : Experimental instructions available upon request.

(Revised June 2004)

We investigate experimentally whether emotions affect bidding behavior in a first price auction. To induce emotions, we confront subjects after a first auction series with a positive or negative random economic shock. We then explore the relation between emotions and bidding behavior in a second auction series. Our main results are: (i) the economic shock has a substantial impact on the experienced emotions of bidders; (ii) the emotional state systematically influences bidding behavior. Our results clearly suggest that emotions should not be excluded as an explanatory factor of behavior in competitive environments like auctions.
: Paper available upon request.

(2003)

We extend the standard ultimatum game to a three person game where the proposer chooses a three-way split of a pie and two responders independently and simultaneously choose to accept or reject the proposal. We investigate whether a responder perceives the other responder as a reference person. We do this by varying the other responder's payoff in case the responder rejects. Hence, we explore whether reciprocal behavior towards the proposer is affected by the presence of the third player. In three treatments, the third player is either negatively affected, unaffected, or positively affected by the responder's choice to punish the proposer. We find that responders are very heterogeneous in their actions. Around one half of subjects submit strategies showing no concern for the other responder's payoffs. Another half of the subject pool submits strategies sensitive to the distribution of the pie among all three players. Preferences for equal splitting of the pie are expressed by less than 10 percent of all responders.
: Paper available upon request.