“Are Inspections Going to Waste? Using Machine Learning to Improve EPA Inspection Targeting of Hazardous Waste Facilities”

Seminar | September 18 | 12:10-1:30 p.m. | 88 Dwinelle Hall

 Katherine Meckel, UC San Diego

 Energy Institute at Haas

Abstract: Machine learning (ML) algorithms are increasingly used to model and predict economic outcomes. Using 15 years of data and nearly 10,000 variables, we build an ML model to predict the likelihood that manufacturing facilities will violate EPA regulations on hazardous waste. Given that the EPA can inspect a limited number of these facilities per year, we simulate the case in which the EPA’s inspection choices are replaced by facilities predicted to be high risk by our model.

 CA, ei-haas@berkeley.edu, 510-642-9590