A Sampling-Based Approach to Emissions Pricing

Emissions must be quantified in order to be priced. For emission sources that are challenging to measure, such as methane pollution from the natural gas supply chain, random sampling may be employed to reduce measurement costs. This paper develops a novel approach to emissions pricing that involves taking measurements at a randomly selected subset of each firm’s facilities to construct firm-level estimates of emissions. A theoretical model demonstrates that under realistic assumptions, applying an emissions price to these firm-level estimates preserves the efficiency benefits of emissions pricing with comprehensive monitoring. A simulation calibrated to be representative of methane emissions from the U.S. oil and gas industry predicts that this approach can achieve net climate mitigation benefits roughly two orders of magnitude greater than measurement costs. JEL Classification: H23