How did you end up in behavioural or experimental economics?
I wasn’t fully aware of this field when I began graduate school. My initial interests were in
environmental economics and questions about cooperation, externalities, and the role of
markets. Then I took a course in Experimental Economics and was immediately drawn in.
Traditional models often felt too limited to capture the richness of human behaviour—
especially in areas like public goods, norms, and environmental or social dilemmas.
Experimental methods offered a clean, causal way to uncover the mechanisms driving these
behaviours. Once I began running experiments, I was hooked by the combination of
methodological rigor and the creativity the field demands.
What question or problem currently motivates your research the most, and why?
My research currently centres on two main themes. The first is inspired by social and
environmental dilemmas, where I examine mechanisms that promote cooperation within and
across groups and the roles played by guilt, normative principles, and redistribution.
The second theme focuses on norms, institutions, and the behavioural drivers of inequality,
particularly gender inequality. Many economic outcomes are shaped not only by incentives but
also by social expectations, confidence, and evaluation practices. My work investigates how
these behavioural and institutional factors interact, and how we can design environments—
whether in workplaces, communities, or markets—where individuals can thrive regardless of
their identity or background.
What do you see as the most important developments or challenges for behavioural and
experimental economics over the next 5–10 years?
A key development in the field is large-scale experiments which now allows researchers to
study behaviour in settings with higher external validity. A related emerging challenge is the
influence of AI on data quality, particularly as many researchers rely on online platforms for
participant recruitment and experimental execution. Understanding and addressing how
AI-generated responses or AI-mediated behaviour may distort data will be increasingly
important for the discipline. In this context, laboratory experiments under controlled conditions
can play a crucial benchmarking role, helping researchers compare behaviour observed online
with behaviour in more tightly controlled environments.
How has your research evolved over time?
My research began with a focus on environmental markets, social preferences, cooperation,
and competition, often using laboratory experiments. Over time, I expanded this work to
examine topics related to corruption, gender, leadership, performance evaluation, and
institutional design. I now conduct laboratory, online, and field experiments and also
collaborate with scholars across disciplines. My research, in general, aims to generate
behavioural insights, with a particular focus on how norms and institutions can be strengthened
to promote fairness and efficiency.
What are the biggest challenges you’ve faced in your research?
An important challenge has been to design experiments that capture the complexity of
real-world decision-making while maintaining strong internal validity. We are also
increasingly expected to translate our findings into meaningful policy recommendations—by
journals, grant agencies, and policymakers. This can take time, as policy-relevant insights often
emerge only after multiple related projects accumulate enough evidence to clarify what is both
effective and scalable.
What advice would you give to PhD students or early-career researchers entering the
field today?
Choose research questions that matter to you—curiosity and a sense of purpose will sustain
you through setbacks. Build strong methodological foundations in experimental design, theory,
and empirical methods, and don’t hesitate to draw on insights from other disciplines when they
strengthen your research. Learn how to design clean identification strategies.
Build collaborations, both vertical (with more senior scholars) and horizontal (with your peers).
Apply for grants periodically; even unsuccessful applications can be valuable because they
force you to clarify your ideas, articulate why your work matters, and refine your research
agenda. And finally, patience and humility will serve you well throughout an academic career.
If you could redirect £10m of research funding tomorrow, what area would you direct it
to?
What a luxury that would be! I would invest in a large-scale research program examining the
behavioural drivers of inequality—particularly how identity and social norms operate within
rapidly evolving institutional and technological environments. A substantial portion would
support building experimental infrastructure across countries and sectors, enabling researchers
to track how preferences, beliefs, norms, and behaviours evolve over time. Such longitudinal,
cross-context data would be useful for designing policies that meaningfully improve
cooperation, reduce inequality, and strengthen institutions. The program would also actively
support and involve many junior scholars, helping develop the next generation of researchers
in the field.
