Daniel Watt

Daniel graduated from the University of Canterbury in 2019 with a Bachelor of Science in Economics and Computer Science, receiving the Sir Frank Holmes Prize for the top undergraduate economist in New Zealand. After graduating, he joined Sapere Research Group as a consultant, working on projects related to healthcare policy and public infrastructure. In this role, he co-authored several publications, contributed to Cabinet advice and electoral campaigns, and was seconded to the Ministry of Health’s COVID-19 response team. In 2022, Daniel received a Master of Commerce in Economics from the University of Canterbury, where his thesis was judged the best economics dissertation in New Zealand and received the prestigious A R Bergstrom Prize in Econometrics. In 2023, he began research as a Predoctoral Research Fellow at Stanford University under the supervision of Jann Spiess. At Stanford, he completed PhD coursework in econometrics and statistics and is co-authoring forthcoming publications in causal inference with Spiess. Daniel’s current research focuses on developing causal inference and machine learning methods that improve our understanding of key health policy decisions and medical interventions. Outside of research, he enjoys long walks with his wife and practicing classical guitar.