I'm an economist who builds causal evidence for questions that resist easy answers — how behavior, institutions, and shocks interact in real systems. If a team needs to know whether an effect is real or a comfortable illusion, that's the work I do.
I hold myself to one standard: an estimate is only worth reporting if I can defend exactly why it's causal. That means taking identification seriously — difference-in-differences, event studies, instrumental variables, regression discontinuity, synthetic control — and being explicit about the assumption each one lives or dies by.
Most of that evidence comes from field experiments I've designed and run myself: lab-in-the-field trials on payments for ecosystem services and commons governance in Ethiopia and Zambia, and online experiments on behavior, emotion, and sustainable choice. Where the experimental data runs out, I turn to agent-based simulation to ask "what if" beyond the range of what I collected.
I'm currently a researcher at the Beijer Institute of Ecological Economics in Stockholm, affiliated with the Stockholm Resilience Centre ecosystem, working at the intersection of ecological economics, causal inference, and commons governance. I got there by way of a postdoc at the Swedish University of Agricultural Sciences and a detour into software — a full-stack diploma and a stint building product at a Stockholm AI startup — that's now baked into how I work, from analysis pipelines to this site. I'm cautiously optimistic about what AI changes for research, not credulous about it.
I grew up in a farming community in Tigray, Ethiopia, which still grounds my intuition for the agricultural and pastoral systems I study — and shapes how I think about building tools that serve people far from the institutions where knowledge usually lives.