Conference Agenda

Disaster recovery can reshape local economic incentives and shift adjustment costs onto natural capital. We study this in rural Indonesia, where earthquakes repeatedly damage assets and infrastructure in forested places. We combine remotely sensed forest loss data with ground-shaking maps for 638 earthquakes between 2001 and 2014 in a community-year panel of more than 50,000 communities. The empirical design compares within-community changes in forest loss after severe shaking, conditional on community and year fixed effects, long-run seismic risk, and initial forest cover. Results show a broad land-use response in the wake of a disaster. Communities exposed to Modified Mercalli Intensity VII/VIII shaking experience about 35% higher forest losses. Land-use evidence points to post-shock forest conversion, including selected oil-palm outcomes and residual other deforestation. This is accompanied by a rise in violent resource and land-rights conflicts, while population and nightlight outcomes do not support broad local growth or large in-migration as the main explanation. The findings show that disaster recovery in forested communities can create environmental externalities when shocks redirect adjustment pressure toward forests.

Endangered species face growing threats from climate change and ecosystem degradation, prompting calls to shift from traditional species-specific protections to more holistic, ecosystem-based approaches. This paper evaluates a prominent example of such a shift: the 2011 U.S. Revised Recovery Plan for the Northern Spotted Owl (NSO), which relaxed restrictions on fuel treatments in protected habitat to reduce wildfire risk. Using high-resolution spatial data from 2006–2023 and a matched difference-in-differences framework, we find that the policy led to a substantial increase in fuel treatment activity—approximately 91,000 additional acres—within NSO-designated habitat, with no evidence of reallocation away from other areas. These treatments generated over $1 billion in economic benefits, primarily through reduced wildfire suppression costs. However, ecological benefits were limited: the policy prevented moderate- to high-severity fire on only 1,000–2,000 acres of NSO habitat and old-growth forest, reflecting their limited effectiveness in reducing burn severity. These findings underscore the potential for ecosystem-based conservation reforms to deliver economic returns, while highlighting the persistent challenges of meeting ecological objectives under existing regulatory, funding, and capacity constraints.

Can a forest-policy reform deliver both higher economic use and ecological sustainability? This paper studies this question in the context of Finland's mid-2010s forest-policy shift, which combined a deregulation of private forest management with a government strategy that promoted the bioeconomy and increased wood use. I develop a simple forest-harvest framework in which legal constraints and transaction costs affect the private return to cutting, and I test its predictions using satellite-measured annual forest loss near the Finnish-Russian border. The empirical design combines a geographic regression discontinuity with a difference-in-discontinuities strategy, exploiting the sharp jurisdictional break at the border and the timing of the Finnish reform. I then use local private-ownership exposure to decompose the post-reform increase into a Finland-wide government-period component and a private-owner law channel. The results show a clear increase in Finnish-side forest loss after the reform, with the largest effects during 2016-2019. The decomposition indicates that this peak reflects both a broad government-period increase and a private-owner law channel. After the 2019 government change, the common component contracts, while the private-owner channel remains positive and statistically meaningful.

Colombia is one of the world’s most biodiverse countries, home to over 10% of the planet’s biodiversity. Much of this richness is found in the Amazon biome, which spans over 43% of the country’s land surface. Despite its ecological importance, the region faces growing threats from deforestation, leading to biodiversity loss and degradation of ecosystem services. Key drivers of this deforestation include socio-environmental conflicts, such as land conversion, coca cultivation, and illegal mining, all of which are compounded by Colombia’s longstanding internal armed conflict. Socioeconomic conditions in local communities add to these drivers, yet a lack of reliable data limits understanding and has led to a gap in the literature. This study explores the links between socioeconomic factors, socio-environmental conflicts, and deforestation in the Colombian Amazon Biome. Using both traditional econometric methods and machine learning (ML) techniques, we analyze a broad set of indicators to identify the main drivers of forest loss. The models reveal that while the impact of coca cultivation on deforestation has decreased, land grabbing and, more recently, illegal mining have become leading contributors. Other consistent predictors include poverty and the presence of basic trails and roads. The analysis further confirms that the northwestern zone remains the most threatened subregion.