I am a Senior Lecturer (Associate Professor) in Economics at the University of Essex. I am the director of the Essex Centre for Behavioural Science which houses the state-of-the-art Essex Behavioural Science Laboratory (ESSEXLab) . In addition, I serve as an Associate Editor at Journal of Economic Behavior & Organization .
I am a behavioral economist. In my research, I use a broad portfolio of research methods–including experiments and advanced microeconometric techniques–to further our understanding of human judgment and decision making. Whereas most empirical research in this area relies on experiments or surveys, I often employ large and rich data sets from carefully selected field settings that can be characterized as natural (or “naturally occurring”) experiments.
I completed my PhD in Economics at Erasmus University Rotterdam and Tinbergen Institute under the supervision of Peter Wakker and Han Bleichrodt . Before joining Essex, I held positions at the University of Nottingham and the Vrije Universiteit (VU) Amsterdam. I have been a visiting researcher at, amongst others, the University of Chicago, Carnegie Mellon University, and the Max Planck Institute for Human Development in Berlin
Here you can read a slightly longer introduction to my work and here you can find selected summaries of my papers. Furthermore, here are my CV, my Google Scholar profile , and my Parkrun profile .
New papers:
PhD in economics, 2014
Erasmus University Rotterdam
MSc in behavioural economics, 2009
University of Nottingham
MSc in sociology and social research, 2008
Utrecht University
BSc in sociology, 2006
Utrecht University
Crowdsourcing a solution to an open-ended question often results in a wide range of answers. A challenge then is to identify the correct or most accurate answer. We propose a simple strategy: select the answer of the person who responded fastest. Using answers of TV game show contestants to quiz questions and diagnoses of physicians assessing a series of medical cases, we find that this algorithm performs better than random selection and following the slowest individual, but worse than following the most confident one. The method also outperforms following the best performing individual on other questions, unless this expert is selected from a large crowd and their skill can be reliably assessed. The accuracy of the follow-the-fast algorithm improves with crowd size. These findings show that following the fast can be an effective method for extracting wisdom from crowds, using a cue that is often readily available.
We directly compare the influences of impact and responsibility considerations on giving behavior. In moral philosophy, utilitarianism emphasizes the importance of the former, whereas theories of equity and desert argue for the importance of the latter. Our data are from a television show where an audience of one hundred people divides ten thousand euros among three financially distressed candidates, and from independent raters who evaluated various attributes of the candidates and their financial predicaments. We find that the well-being benefit of a donation (“impact”) outweighs the degree to which the candidate had control over the cause of their situation (“responsibility”). Giving increases more with impact than it decreases with responsibility, and the contribution of impact to the fit of our regression models is approximately two-and-a-half times that of responsibility. Additionally, our analysis shows no evidence of discrimination on age, gender, or physical attractiveness.
Conditional cooperation is usually investigated in experiments where others’ choices are known. In this study, we explore conditional cooperation under uncertainty. Using a novel experimental design, we exogenously manipulate the likelihood that a subject’s partner in a Prisoner’s Dilemma will cooperate. Information about the partner’s cooperation is either presented descriptively or learned through experiential sampling. We find a description-experience gap: subjects are more likely to cooperate under experience than description when the likelihood of their partner’s cooperation is low, while the opposite holds when it is at least 50%. This finding is contrary to expectations from individual choice literature, where rare events typically receive less weight in experiential-based decisions. Our findings indicate that conditional cooperators are less responsive to social information when obtained experientially rather than descriptively, and illustrate how stronger priors under social than under individual uncertainty can account for this disparity.
A sizable literature shows that many people are loss averse, being more sensitive to losses than to commensurate gains. Furthermore, it has been shown that an individual’s level of loss aversion is an important driver of their investment decisions. Based on these findings, regulators are encouraging financial institutions to incorporate clients’ loss aversion in risk profiling classifications. The most critical obstacle to doing so is the lack of a valid measurement method that can straightforwardly be integrated into existing processes.
In 2016, my co-authors and I published a paper introducing a novel theoretically valid way to elicit an individual’s loss aversion in the Journal of Risk and Uncertainty. This brought me in contact with Jurgen Vandenbrouke, an expert general manager at a large Belgian bank, looking for a way to measure loss aversion. I collaborated with him and his team to integrate our method for eliciting loss aversion into their risk profiling application. This approach was trailed in Belgium and implemented in the actual risk profiling application of the bank in Ireland. The paper describing this implementation is now forthcoming in the Journal of Banking & Finance.
Jurgen Vandenbrouke is now the director of Everyone Invested, a wealth tech spinoff of the Belgian bank. One product they market is their Profiler, which includes our method to elicit loss aversion. As a result, more financial institutions will likely adopt our method over the coming years.
At the University of Essex, I teach EC955: Experimental Economics at the master level. This module equips students with the tools to critically access experimental methods. Students put their theoretical knowledge into practice, learning how to design experiments and interpret their results. For this, students will be grouped into teams who will collaborate to design an experiment and present it in class. Students will also critically assess another group’s experimental design. In addition, I also supervise undergraduate dissertations.
Previously, at the Vrije Universiteit Amsterdam, I taught at the undergraduate, graduate, and postgraduate levels.
At the bachelor level, I lectured in the course Behavioral Finance and Real Estate (BSc, 3rd year). This course provides a behavioral perspective on real estate decision-making and markets. Students learn how behavioral biases affect participants’ decisions in real estate markets and how the bounded rationality of market participants can explain real estate market dynamics. In the course, I provided students with a psychological perspective on negotiations, property valuations, and mortgage choices.
At the master level, I provided lectures in behavioral ethics and negotiation in the course Behavioral Finance.
At the executive education level, I lectured on behavioral ethics in the program Compliance and Integrity Management.
I also supervised MSc theses on topics related to behavioral finance and provided tutorials in Finance (BSc, 2nd year). In this latter course, we built the foundation for the study of corporate finance and investments. The focus was on financial decision-making in theory and practice. Our coverage of core finance topics included: i) capital budgeting, ii) asset pricing, and iii) financial investment.
During my Ph.D. at Erasmus University Rotterdam, I designed and taught tutorials in behavioral economics and supervised both BSc and MSC thesis in topics related to behavioral economics and behavioral finance.
Here, I provide a selected overview of the coverage that my research has received in popular media:
For the paper Does Losing Lead to Winning? An Empirical Analysis for Four Sports: NRC (Dutch)
For the paper Gender and Willingness to Compete for High Stakes: Süddeutsche Zeitung (German)
For the paper Can the Market Divide and Multiply? A Case of 807 Percent Mispricing: Wall Street Journal
For the paper The Wisdom of the Inner Crowd in Three Large Natural Experiments: Bloomberg; Cosmos Magazine; Yahoo
For the papers Measuring Loss Aversion under Ambiguity: A Method to Make Prospect Theory Completely Observable and Behavioral Risk Profiling: Measuring Loss Aversion of Individual Investors: De Tijd (Dutch) ; L’Echo (French)
For the paper The Evil Eye: Eye Gaze and Competitiveness in Social Decision Making: The Conversation
For the paper Number Preferences in Lotteries: Wall Street Journal; NOS (Dutch); Algemeen Dagblad (Dutch); BNR (Dutch); De Morgen (Dutch); RTL (Dutch)
For the paper Risky Choice in the Limelight: Financial Times; The Times; The Conversation
For the paper Beyond Chance? The Persistence of Performance in Online Poker: Newsweek; The Independent (1/2); The Independent (2/2); The Times; Daily Mail; The Conversation
For the paper Split or Steal? Cooperative Behavior When the Stakes Are Large: FSR Forum; Tijdschrift voor het Economisch Onderwijs (Dutch)