I am an environmental economist at Columbia University's School of International and Public Affairs (SIPA). I am affiliated with CEEP, the Climate School, and the Institute for the Study of Labor (IZA). From 2023 to 2024, I was a Senior Advisor in the Office of Information and Regulatory Affairs (OIRA). I study how forecasts and other types of information affect actions in settings including adaptation to climate change, risk-taking in research, and time use. These days, I am especially fascinated by how people perceive and use weather forecasts—a decades-long information intervention going on every hour of the day, all around the world.

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Running weather regressions and using clustered standard errors? I have a modest proposal to cluster at the National Weather Service (NWS) County Warning Area (CWA) level. (...more)

Temperature exhibits high temporal autocorrelation. Regressing daily, county average temperature in the continental U.S. on its own first lag yields a coefficient of 0.95, a t-stat of 730 (standard errors clustered at the National Weather Service County Warning Area level) and an R^2 of 0.9. Regressing temperature on its own first 7 lags yields the following coefficients. (...more)

What is the economic justification for government production of weather forecasts? The question has gained particular relevance during the first and second Trump administrations, and this is my place to collect and clarify economic reasoning related to the question, focusing on "classic" economic rationales for public policy. (...more)

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