Research

We undertake the first systematic analysis comparing and contrasting U.S. improved forest management (IFM) projects participating in the California regulated and global voluntary carbon offset markets. We link a novel geospatial dataset of IFM offset projects located in the U.S. Forest Northern Region to measurements of above-ground live carbon collected through U.S. Forest Service Forest and Inventory Analysis (FIA). Statistical and calibrated simulation analyses both provide evidence for market entrance selections and excessive offset credit issuance. As revealed by event study analysis and two-stage logistic regression, IFM projects on regulated and voluntary markets differ significantly in pre-market forest management relative to their statistical counterfactual forestlands with similar carbon storage capacities. Payoff estimations based on forest simulation modeling replicate this entrance outcome, illustrating that regulated market projects realize greater revenues under the regulated market rules than they would under the voluntary market rules, and likewise voluntary market projects realize greater revenues under the voluntary market rules. Using the simulation, we also find that real-world market entrance outcomes match with the generous lower baselines implied in the IFM projects' registry documentation, rather than the more appropriate business-as-usual baselines. Because of that, regulated market projects are non-additional and voluntary market projects also issue about 1.8 times the offset credits of their justified emission reduction. While current offset markets promote forest-based projects as nature-based climate solutions, they also raise serious integrity concerns that may weaken overall incentives for carbon reduction by corporate buyers. Based on our counterfactual analysis, switching to stricter business-as-usual baselines would solve the over-crediting problem, but also lower carbon offset market participation and reduce the potential amount of carbon mitigation by 15.4%.

Constructed primarily to defend coastal economies from severe storms and sea surges, seawalls have served as an effective protective measure across the world for thousands of years. In the past decade, as climate change has intensified projections of stronger, more frequent cyclones as well as significantly rising sea levels, seawalls have become even more critical for sustaining coastal economies. Many countries are already planning expansions of seawall infrastructure in preparation for future sea level rise. This study examines the current role of seawalls in protecting China's coastal economies from typhoons, sea level rise, and high sea waves during 2015-2024. Our results have shown that increasing the share of coastlines protected by seawalls has significantly reduced the negative impacts of sea risks on coastal economies both in the short-run, as reflected by changes in nightlight intensity, and in the long-run, as reflected by housing prices. Short-run impacts mostly arise from reduced disruptions to industrial, residential, and transportation activities, and are concentrated in districts that are not directly coastal but are the most economically active within each coastal city, implying that the defensive effects of seawalls spillover beyond directly protected coastal districts. We also find that seawall maintenance significantly improves protective effectiveness, while co-location with offshore mangroves can reduce the protective benefits. Long-run impacts of seawalls are capitalized into reducing the gap between coastal and non-coastal districts of land and second-hand housing prices in coastal Chinese cities. Overall, our findings highlight the importance of seawalls in strengthening coastal resilience to extreme climate events and underscore their relevance under future climate change.

The economic value of weather forecasts depends critically on how risk-averse agents incorporate forecast uncertainty relative to realized weather shocks into their decision-making. This paper investigates the safety–efficiency trade-off in air traffic control (ATC) decisions under tropical cyclones in China. Using high-frequency hourly flight trajectory data merged with real-time hourly typhoon forecasts of China, we document that physical observations of wind limits explain only a modest share of capacity reductions. Instead, aviation operational decisions exhibit pronounced behavioral asymmetry: for identical wind conditions, throughput is significantly lower when storms are approaching than receding, and flight cancellations occur well before physical conditions deteriorate beyond safety thresholds. Estimation using structural dynamic choice modeling further reveals that forecast uncertainty substantially amplifies perceived risk in the aviation industry, generating preemptive capacity suppression under forthcoming tropical cyclones beyond what physical constraints require for flight safety. Counterfactual simulations demonstrate that while reducing tropical cyclone forecast uncertainty yields efficiency gains for the aviation industry, the magnitude is constrained by the inherently conservative nature of aviation safety standards.

In light of escalating wildfire occurrences exacerbated by climate change, smoke related air pollution has become increasingly the concerns for public health and economic growth. This study analyze the impacts of short-term smoke forecasts issued by NOAA (National Oceanic and Atmospheric Administration) in California during 2015-2020, which exposes increasingly prolonged smoke hazards to densely populated areas. Utilizing the variations in realized and day-ahead forecast of smoke-related fine particular matters, I identify changes in residential electricity and water consumption under different levels of realized and forecast smoke exposures. Light smoke exposures lead to increased electricity and decreased water consumption, implying adaptations of indoor air filtering and avoidance of using polluted water. Heavy smoke exposures likely drive evacuations and large-scale cleaning afterwards, which are shown with the significant decrease in residential electricity and increase in water consumption. Accurate smoke forecasts complement these adaptations, in regular years (2015-2019) decrease electricity consumption and encourage evacuations, and in COVID stay-at-home year (2020) increase electricity consumption and encourage indoor air filtering. Further evidenced by economic and health outcome changes under quality smoke forecasts, including lowered unemployment rates and weakly reduced mortalities, these behavioral adjustments underscore the social benefits of adaptations by electricity and water consumption with high-quality smoke-related air quality predictions.