An Investigation of Auctions in the Regional Greenhouse Gas Initiative

The Regional Greenhouse Gas Initiative (RGGI), as the largest cap-and-trade system in the United States, conducts quarterly auctions to distribute emissions permits to firms. This study examines the behavior of firms and the performance of RGGI auctions from both theoretical and empirical perspectives. We begin by providing a theoretical model that offers insights regarding the optimal bidding behavior of firms participating in RGGI auctions. We then analyze data from 58 RGGI auctions to assess the relevant parameters, employing panel random effects and machine learning models. Our findings indicate that most significant policy changes within RGGI, such as the Cost Containment Reserve, positively impacted the auction clearing price. Furthermore, we identify critical parameters, including the number of bidders and the extent of their demand in the auction, demonstrating their influence on the auction clearing price. This paper offers valuable policy insights for all cap-and-trade systems that allocate permits through auctions, as it substantiates the efficacy of policies and the importance of specific parameters using data from an established market