Patrick Baylis
Bio: Patrick is a Ph.D. Candidate in Agricultural and Resource Economics at UC-Berkeley, specializing in environmental and climate change economics. He won the Outstanding Graduate Student Instructor award for his work as a teaching assistant for Max Auffhammer's graduate econometrics course. Patrick graduated from Carleton College with a degree in Political Science and has worked as a consultant on a variety of projects from health care to green building. He also likes building things and baking sourdough.
Research: Patrick specializes in developing new datasets to answer questions of foundational importance to environmental economics. His research supplements more traditional techniques in applied econometrics with modern approaches from computer science, psychology, and computational linguistics. In his job market paper he builds a rich dataset on human emotion from nearly half a billion Twitter posts to precisely estimate the relationship between experienced temperature and human mood. He documents a negative relationship between high temperature and mood, and connects his findings to a larger literature on the impacts of climate change on economic outcomes, suggesting how appropriate policy responses might be tailored to combat the negative effects of rising temperatures.
Fields of interest: Environmental economics, climate change economics, energy economics, machine-learning and econometrics
Personal page here
Burke, Gonzalez, Baylis, Heft-Neal, Baysan, Basu, Hsiang, Nature Climate Change (2018)
Link to paper (ungated here)
Selected coverage: TIME, USA Today, Bloomberg, Scientific American, the Atlantic, SF Chronicle, CNN, World Economic Forum, Reuters, Technology Review, Fortune, Financial Times