This week, Indu Roychowdhury, PhD candidate in Geography, and Robert Reaser, PhD candidate in Economics, each presented their ongoing work. 

In Indu's joint work with Fran Moore, she tests whether credits traded in wetland mitigation markets offer equivalent flood protection benefits. Wetland mitigation markets aim to offset environmental damage by allowing developers to purchase credits from previously restored wetlands. Using newly developed, high-resolution estimates of wetland flood protection for 915 wetland markets within the continental U.S., she documents a likely decline in flood-protective value due to wetland loss over the 1985 to 2021 period. Consistent with standard models of urban economic geography, wetlands lost to development exist near prior developed areas and therefore provide relatively high levels of downstream flood protection compared to wetlands created in compensation--on average ~4.1 times as much, though in some cases up to 78 times. She then documents a high concentration of lost flood protection in Florida. While wetland markets may succeed in preserving total wetland acreage, they may systematically fail to preserve downstream flood protection services. More generally, this suggests that designing environmental markets to preserve complex bundles of spatially-heterogeneous ecosystem services while still allowing meaningful compliance flexibility may be challenging.

Robert's work, joint with Reid Taylor of the Dallas Fed, seeks to understand the bidding behavior of battery storage operators in the Texas electricity market. Batteries have emerged as a solution to the intermittency of renewable generation. However, they are different from traditional generation sources due to their role as arbitrageurs. Using novel, high-frequency data, Rob and Reid recover the dynamic marginal costs that rationalize the real-time bidding behavior of battery operators. They extend the seminal supply-function framework of Hortacsu and Puller (2008) to incorporate the dynamic decision-making of grid-scale battery storage. At their core, these estimates uncover the strategic nature of battery behavior. In forthcoming work, Rob and Reid plan to evaluate operator performance relative to optimal benchmarks, explore heterogeneity across firms, and investigate the growing role of machine-learning and AI-based bidding strategies. Their approach also offers regulatory value: because market-power mitigation in electricity markets traditionally relies on cost-based tests, our method provides a transparent, data-driven way to infer the underlying costs that batteries reveal through their bids.