I'm Michaela Theilmann — a development economist and global-health researcher. I help teams find out whether their work is making a difference, and understand why. Evidence rigorous enough to defend, clear enough to act on.
I've spent the last decade at the intersection of economics and global health — as a PhD researcher, and now as a postdoctoral researcher affiliated with Harvard Medical School, after years at the Heidelberg Institute of Global Health and the Technical University of Munich. My training is in development economics; my work is about the health and livelihoods of people in the places where good measurement is hardest and matters most.
Underneath the methods, the belief is simple: the people a program is meant to serve deserve to know if it's actually helping. Honest evidence is a form of respect. That's the standard I bring to every evaluation — the same designs and scrutiny I'd put into work headed for peer review, in service of a decision you have to make on the ground.
This page isn't a pitch. It's an introduction — so if we ever work together, we start from something real.
Most of my work sits somewhere along the line from "what are we really trying to change?" to "here's what we found, and here's what to do with it." Depending on where you are, that can look like any of these.
Sharpening the questions, building an honest theory of change, and choosing methods that fit the program and the decision — not a template.
Establishing whether a program actually caused the change you see — through randomized and quasi-experimental designs, done carefully and reported plainly.
Working with large, individual-level survey data — including pooling nationally representative datasets across many countries to see patterns single studies miss.
Indicators and frameworks a team can actually run with — light enough to maintain, honest enough to learn from, built for the people who'll use them.
The part that too often gets skipped: translating results into something a program lead can act on, a board can weigh, or a donor can trust — without flattening the nuance that makes them true.
My research and evaluation work has taken me across health systems and questions of access to care in low- and middle-income countries — in the field, and through large multi-country datasets.
Who reaches care and who is left out — the socioeconomic and rural–urban gradients that decide whether a health system is fair.
Hypertension, diabetes and cardiovascular care in settings where the need is rising fastest and the data is thinnest.
Field experiments — including cash-transfer trials — testing what actually moves people to seek and stay in care.
No pitch, no obligation — just a first conversation about what you're trying to learn and whether I'm the right person to help. The best collaborations I've had started exactly this way. Say hello.
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