Abstract: Large-scale projects often require assembling adjacent parcels from multiple landowners, which often leads to severe holdout problems. This paper models landowners as a neighborhood network to identify sources of market frictions. I introduce pivotality, assembly centrality, and benchmark order to capture how network structure and bargaining sequence affect outcomes. The key findings show that (1) pivotal agents gain significantly higher surplus, with payoffs reflecting the relative bargaining power between the developer and landowners; (2) the order of negotiation also matters—starting with central agents lowers overall acquisition costs. Evidence from over 300,000 U.S. land assembly transactions supports the model’s predictions.
Creative Destruction or Lasting Decline: Recovery from Wildfires with Ariel Ortiz-Bobea and Jiong Wu
Abstract: Why do some cities rebound after destructive disasters while others stagnate or decline? Linking over one thousand wildfires that occurred across the United States to parcel-level tax assessments, we estimate land and building value dynamics in burned and surrounding areas. On average, wildfires reduce land and building values in the long run, but impacts vary systematically with pre-disaster local productivity. Ranked within counties, parcels in low productivity areas suffer persistent losses, middle-ranked areas recover quickly, and upper-ranked areas undergo “creative destruction,” experiencing sustained gains. Nearby unburned areas exhibit similar growth or decline trajectories due to spillovers from burned areas, with effects persisting for more than a decade. Depending on the quality of rebuilding, disasters can hinder, restore, or accelerate growth, underscoring the importance of spillovers and coordinated investment policies in shaping urban resilience.
Getting Endorsement from Heterogeneous Experts with Suraj Malladi
Abstract: An agent has a quality initially unknown to her and a set of experts. The experts vary in their ability to discern the agent’s quality, and the agent chooses who to approach for approval. An expert only wants to approve a high type agent, whereas the agent wants to get approval regardless. There is an N-shaped relationship between the prior belief about the agent's quality and her choice of expert. When experts are very pessimistic, the agent approaches a careful expert to avoid outright rejection. When experts are moderately pessimistic, the agent wants less scrutiny, hoping that errors play in her favor. At moderately optimistic beliefs, the agent seeks careful scrutiny, as she is confident in her quality. When the market is very optimistic, the agent again seeks a less careful expert who would rubber stamp her case.
Assembly in a Network: A Mechanism Design
Global Agriculture R&D Needs under Climate Change with Ariel Ortiz-Bobea and David Lobell
Climate Change, Pollen, and Respiratory Allergies: Evidence from the US Healthcare with Qingli Fan, Jing Li, Daniel Katz, and Ariel Ortiz-Bobea
Large increases in public R&D investment are needed to avoid declines of US agricultural productivity with Ariel Ortiz-Bobea, Robert G Chambers, David B Lobell (2024)
Proceedings of the National Academy of Sciences (PNAS)
[code + data]
Agricultural credit association efficiencies over time and with mergers with Loren W. Tauer (2023) [Master’s Thesis]
Agricultural and Resource Economics Review
Cornell Dyson Best Master Thesis Award
The Northeastern Agricultural and Resource Economics Association Outstanding MS Thesis Award of Merit
A vulnerability index for priority targeting of agricultural crops under a changing climate with Calum G. Turvey, Jiajun Du, Ariel Ortiz-Bobea (2021)
Climatic Change