By: Nancy Moseley
Posted Aug. 2026

Pragati Dahal's research interests are applied microeconomics, applied econometrics, health economics, and labor economics, with a focus on how digital infrastructure shapes quality of life and well-being in rural and underserved communities.

She is currently analyzing the effects of broadband expansion on mental health in the United States. Outside of school, Pragati enjoys yoga and running and loves to hike, travel, and explore new places with her husband, Abhi.

Professional profile and contact

2026 award and recognitions

  • Kline Graduate Fellowship
  • Selected to present at the Southern Economic Association (SEA) annual meeting
  • Competing in the AAEA Data Visualization Challenge and with the USDA Agricultural Marketing Service
  • Graduate Lead, Data Science for the Public Good 

Q&A

What real-world problem are you most passionate about solving through your research, and why?

Most of my work is about whether public investment/policy actually reaches the people it's meant to help, and whether we can measure that credibly. The policy has already been written, and the money has already moved, but what did it actually do? I care about that because the answer isn't obvious, and getting it wrong has real costs for the communities and people these policies were designed to help.

What inspired you to pursue your Ph.D.?

I started with a bachelor's in agricultural science in Nepal, but I found I was less interested in the lab and field side of it than in the policy questions sitting behind it, the human implications, the social aspect. So, I decided to pursue my master's in agricultural economics at the University of Idaho, where I was introduced to the world of applied econometrics and causal inference.

Difference-in-differences, in particular, struck me: the design is so sophisticated in what it lets you claim, yet the concept is surprisingly simple to understand, even for someone with a non-econ background. I wanted to keep working with and expanding on those tools, and increasingly to bring machine learning methods into that same framework, using them to strengthen my causal work.

Girl on lane stadium field wearing white and pointing to scoreboard
Photo courtesy of Pragati Dahal.