ECONOMICS: Think past the identification strategy!

If you've spent time in economics — as a student, a researcher, a practitioner — you already know the feeling I'm describing. A paper gets presented. The identification strategy is clever. The standard errors are tight. The result is policy-relevant. And then someone asks, quietly, but why does this actually happen? — and the room moves on, because the design can't answer that, and the discipline has quietly decided that's fine.

It isn't fine. And I don't think you think it is either, or you wouldn't be here.

I built this school because I kept encountering the same gap: technically sophisticated economists who had never been given the tools to think carefully about causal explanation as distinct from causal identification — about mechanisms, structural conditions, scope, and the political economy of which questions get funded, published, and treated as settled. The credibility revolution is a genuine intellectual achievement, and I want to be clear that this school takes it seriously. We work through what RCTs actually deliver, what instrumental variables require you to believe, what the difference between a LATE and an ATE commits you to philosophically. The critique here is earned, line by line. We don't dismiss the toolkit; we understand it well enough to know where it runs out.

What you'll find on the other side of that understanding is a richer analytical landscape than most economics training maps. Causal graphs and DAGs give you a more expressive formal language for causation than the potential outcomes framework alone. Structural models — often dismissed as pre-credibility-revolution relics — turn out to be indispensable for genuine explanation. Theories of social reproduction and institutional change let you ask how the arrangements economists measure came to be and how they are contested, rather than treating them as the background wallpaper of identification exercises. Class, race, and gender stop being nuisance controls and start being structural variables with their own causal logic.

None of this is hand-waving. Precision of argument is the minimum standard in this school — not as a performance of rigour, but because vague critique is worse than no critique. Every analytical move is earned, every claim is bounded by its scope conditions, and we spend real time on the philosophy of science underlying the debates, because you cannot argue well about causality without understanding what causality means.

By the time we reach the constructive portion of the curriculum — designing rigorous research questions, matching method to question, engaging across disciplinary boundaries — my hope is that you will feel not just more critical but more capable. More able to identify what a genuine research contribution looks like, more confident in interdisciplinary conversations, and more equipped to do economics that explains, not merely identifies! That is the transformation this school is built around. I'd like to walk you through it.