Publications

The expansion of marine protected areas (MPAs) is a core focus of global conservation efforts, with the “30x30” initiative to protect 30% of the ocean by 2030 serving as a prominent example of this trend. We consider a series of proposed MPA network expansions of various sizes, and we forecast the impact this increase in protection would have on global patterns of fishing effort. We do so by building a predictive machine learning model trained on a global dataset of satellite-based fishing vessel monitoring data, current MPA locations, and spatiotemporal environmental, geographic, political, and economic features. We then use this model to predict future fishing effort under various MPA expansion scenarios compared to a business-as-usual counterfactual scenario that includes no new MPAs. The difference between these scenarios represents the predicted change in fishing effort associated with MPA expansion. We find that regardless of the MPA network objectives or size, fishing effort would decrease inside the MPAs, though by much less than 100%. Moreover, we find that the reduction in fishing effort inside MPAs does not simply redistribute outside—rather, fishing effort outside MPAs would also decline. The overall magnitude of the predicted decrease in global fishing effort principally depends on where networks are placed in relation to existing fishing effort. MPA expansion will lead to a global redistribution of fishing effort that should be accounted for in network design, implementation, and impact evaluation.

The replication crisis in empirical research calls for a more mindful approach to how we apply and report statistical models. For empirical research to have a lasting (policy) impact, these concerns are crucial. In this paper, we present Probabilistic Programming (PP) as a way forward. The PP workflow with an explicit data-generating process enhances the communication of model assumptions, code testing and consistency between theory and estimation. By simplifying Bayesian analysis, it also offers advantages for the interpretation, communication and modelling of uncertainty. We outline the advantages of PP to encourage its adoption in our community.

This paper studies how the North American Free Trade Agreement (NAFTA) affected the wage gap between high and low-paid workers within Mexico, considering internal migration. In low-skilled, labor-abundant developing countries, trade liberalization should theoretically increase the wages of low-skilled workers, decreasing income inequality. However, anecdotal evidence indicates that NAFTA increased the gap between rich and poor in Mexico, and empirical evidence is mixed (Hirte et al. 2020; Brülhart 2011; Bosch and Manacorda 2010; Nicita 2009; Chiquiar 2008; Hanson 2007; Gonzalez-Rivas 2007). Because trade may affect wages differently across regions within the country, accurate measures of wage effects must incorporate internal migration; otherwise, apparent wage convergence or divergence might only reflect a geographic resorting of workers. We evaluate wage changes by considering rural-to-urban migration. We first find a slight decrease in both internal and external migration in the years after NAFTA. Then, we find that all male workers see a wage reduction from trade openness, although the harm of high-wage workers almost doubled that of their counterparts with low wages. NAFTA also mitigated some of the wage differentials between the North and South. In summary, trade liberalization has reduced wage differentials among working-age men in urban areas.

Sustainable fisheries are crucial to Indonesia’s economic growth and the nutritional needs and livelihoods of millions of Indonesians. Evidence suggests that Indonesia's fisheries have yet more to offer. Key regulatory instruments and strategic documents—including the Medium-Term National Development Plan 2020-2024 and Indonesia’s Ocean Policy (Presidential Regulation 16/2017)—outline targets for the fisheries sector to deliver growth, jobs, food security, and government and export revenues. An important target is the goal of increasing total fishery production by one-third. Achieving these targets will require policies and investments that align interests: short- and long-term interests, industry and regulator interests, and national and sub-national interests. This report examines policy options to support higher-performing fisheries, defined as those fisheries that deliver maximum sustainable potential in line with the Government of Indonesia’s goals. The government is taking important steps towards a high-performing fisheries sector with reforms such as Penangkapan Ikan Terukur, or Quota-Based Sustainable Fisheries, introduced by the Ministry of Marine Affairs and Fisheries (MMAF) at the end of 2021 and stipulated by Government Regulation No.11/2023. This policy, which would see fishers or firms given well-defined harvest allocations in return for meeting certain conditions, represents a shift to align incentives for greater economic and social returns from fisheries. This policy, along with other enhancements in governance and management capacity underway, offer opportunities for important gains. The report quantifies the costs and benefits of management enhancements and considers policy measures that could contribute towards the realization of these benefits. A bioeconomic model was developed focusing on three demonstration fisheries (skipjack tuna, snapper-grouper, and scads) spanning three fishery management areas (WPP-714, WPP-715, and WPP-718) that together encompass most of Eastern Indonesia. These fisheries have contrasting biological, commercial, and food security characteristics, enabling the costs and benefits of management reforms to be examined under a range of scenarios. Fisheries were selected based on their: (1) overall significance (value and volume); (2) representativeness of multiple government objectives (e.g., food security and export earnings); and (3) analytical tractability and data availability. Four stylized levels of management performance were modeled: (i) lowperforming; (ii) moderately-well performing; (iii) high performing; and (iv) very high performing. Higher performing fisheries were defined as those with the ability to match fishing capacity and effort with stated management objectives (e.g., to control harvests in line with reference points such as maximum sustainable yield) and to maximize efficiency (i.e., maximize the harvest revenues retained after accounting for the costs of fishing effort). Modeling results were complemented with detailed insights from fishery stakeholder consultations including government, private sector, academia, and civil society.

After decades of fits and starts, the ambition to protect 30% of land and sea by 2030 (30x30) (1) is gaining some momentum, but only modest progress has been made. One reason is that signing on to protect 30x30 will be much more costly for some nations than others; many nations facing low costs of conserving have already protected, while other nations foresee enormous costs and are reluctant to sign on. Focusing on the context of marine habitats contained by nation’s exclusive economic zones (EEZs), we propose an alternative approach to meeting these ambitious conservation targets in a way that lowers the costs to all nations: allowing nations to trade their conservation obligations with other nations. Some nations would voluntarily end up conserving more than 30% of their waters and others would end up conserving less, all within well-defined and ecologically informed constraints that ensure protection across marine habitats.

We price the transboundary externality of mobile public bads such as diseases and invasive species. We focus on the marginal cost to country B of an increase in the stock (i.e. an “outbreak”) in country A. These cross-jurisdiction marginal costs depend not only on economic, ecological, and spatial features of both jurisdictions but also on jurisdictions’ strategic reactions to the outbreak. Using a spatial dynamic game, we calculate the “cross-jurisdiction shadow costs” of an outbreak of mobile public bad under the Markov-perfect Nash equilibrium of control efforts. We find that under reasonable conditions, the source country has private incentives to control the outbreak itself, which can lead to a situation where the cross-jurisdiction shadow cost is, in fact, zero. We also derive conditions where a country optimally fails to control the outbreak (for example, damages in that country are small), in which case cross-jurisdiction shadow costs are positive. Finally, we note that since cooperative control of the mobile public bad delivers substantially higher welfare than non-cooperative control, we derive an externality pricing instrument that perfectly internalizes the externality and induces cooperative control among all countries.

Voluntary Sustainability Standards (VSS) are transnational governance instruments that can be leveraged to pursue sustainable development in global value
chains. They have proliferated since the 1990s in terms of their number and the
share of global production they govern. This paper shares some key insights arising from the considerable body of literature that has analysed the role of these
instruments for sustainable production and trade. First, it introduces VSS, traces
the evolution of their adoption and takes stock of the research on their sustainability impacts. Next, some major developments in the VSS realm are discussed,
related to public policy and the emergence of national sustainability standards.
The paper then zooms in on the challenges and limitations of VSS in transforming
value chains towards sustainability, focusing on the shortcomings related to inclusiveness and the problems arising from their proliferation. The paper concludes
by distilling recommendations on overcoming these challenges, especially in light
of recent policy developments, and outlines what different stakeholders can do to
make VSS more effective and inclusive instruments for sustainable value chains.

Credit markets and property rights are fundamental for modern economies, but their implications for the commons are unknown. Using a dynamic model of competitive resource extraction, we show that improving property right security unambiguously increases conservation incentives, but the effect of credit markets on resource extraction effort hinges on the security of property rights. We test these predictions using data on global fisheries, credit markets, and the largest ever marine property rights assignment. We find that property right security reduces resource extraction and that credit market development increases resource extraction under insecure property rights but reduces resource extraction under secure property rights.

Inequities in access to energy efficiency programs for public sector entities such as schools and local government directly impact the communities they serve. Using California as a case study, we assess the distributional justice within energy efficiency programs by investigating disparities in program budgets targeting public sector entities, specifically local governments (cities, n = 417; and counties, n = 58) and kindergarten to 12th grade (K−12) public schools (student ages 5/6 to 17/18 years, n = 58). We employ t-tests and multivariate regressions to investigate potential drivers of differences in program budget including rurality, tax revenues, income, race, and disadvantaged status indicators. Our results show that both local governments and K-12 public schools in more rural counties have lower total program budgets because of their lower population compared to more urban counties. Furthermore, energy efficiency programs in local governments and K-12 public schools in counties with a higher share of disadvantaged communities have a lower budget per capita. For K-12 public schools, counties with a higher proportion of students from lower income households or disadvantaged communities have both lower program budgets overall and per capita. These results highlight inequities in energy efficiency program budgets for local governments and K-12 public schools. Better targeting of programs at rural, low income, and disadvantaged communities is essential to ensure equitable access to energy efficiency program resources across communities and regions.

Understanding the costs and the spatial distribution of health and employment outcomes of low-carbon electricity pathways is critical to enable an equitable transition. We integrate an electricity system planning model (GridPath), a health impact model (InMAP), and a multiregional input–output model to quantify China’s provincial-level impacts of electricity system decarbonization on costs, health outcomes, employment, and labor compensation. We find that even without specific CO2 constraints, declining renewable energy and storage costs enable a 26% decline in CO2 emissions in 2040 compared to 2020 under the Reference scenario. Compared to the Reference scenario, pursuing 2 °C and 1.5 °C compatible carbon emission targets (85% and 99% decrease in 2040 CO2 emissions relative to 2020 levels, respectively) reduces air pollution-related premature deaths from electricity generation over 2020–2040 by 51% and 63%, but substantially increases annual average costs per unit of electricity demand in 2040 (21% and 39%, respectively). While the 2 °C pathway leads to a 3% increase in electricity sector-related net labor compensation, the 1.5 °C pathway results in a 19% increase in labor compensation driven by greater renewable energy deployment. Although disparities in health impacts across provinces narrow as fossil fuels phase out, disparities in labor compensation widen with wealthier East Coast provinces gaining the most in labor compensation because of materials and equipment manufacturing, and offshore wind deployment.

In response to growing scrutiny surrounding commodity-driven deforestation, companies have introduced zero-deforestation commitments (ZDCs) with ambitious environmental and social targets. However, such initiatives may not effectively reduce deforestation if they are not aligned with the spatial extent of remaining forests at risk. They may also fail to avert socio-economic risks if ZDCs do not consider smallholder farmers’ needs. We assess the spatial and functional fit of ZDCs by mapping commodity-driven deforestation and socio-economic risks, and comparing them to the spatial coverage and implementation of ZDCs in the Indonesian palm oil sector. Our study finds that companies’ ZDCs often underperform in four areas: traceability, compliance support for high-risk palm oil mills, transparency, and smallholder inclusion. In 2020, only one-third of companies sourcing from their own mills, and just 6% of those sourcing from external suppliers, achieved full traceability to plantations. Comparing the reach of ZDCs adopted by downstream buyers with those adopted by mill owners located further upstream, we find that high-quality ZDCs from buyers covered 62% of forests at risk, while mill owners’ ZDCs only covered 23% of forests at risk within the mill supply base. In Kalimantan and Papua, the current and future deforestation frontiers, the forests most at risk of conversion were predominantly covered by weak ZDCs lacking in policy comprehensiveness and implementation. Additionally, we find that only 46% of independent smallholder oil palm plots are in mill supply sheds whose owners offer programs and support for independent smallholders, indicating that smallholder inclusion is a significant challenge for ZDC companies. These results highlight the lack of spatial and functional alignment between supply chain policies and their local context as a significant gap in ZDC implementation and a challenge that the EU Deforestation Regulation will face.

As the climate changes, efficient climate policy requires a better understanding of how individuals adapt. Despite extensive research on various climate adaptation frictions, including financial and technological constraints, models of adaptive decision-making assume that agents have perfect information and accurate beliefs about climate. Combining rural household data in Bangladesh with a meteorological measure of dryness, this paper studies the role of individual drought beliefs and their accuracy in irrigation decisions as a key adaptive margin. In a theoretical model, I introduce a behavioral friction to document how heterogeneous beliefs differentially influence responsiveness to the same meteorological signal in dryness. The empirical analysis reveals an asymmetric response to dry shocks in irrigation conditional on the accuracy of prior beliefs. A counterfactual analysis shows lower technology adoption levels and higher monetary losses when beliefs are inaccurate.

Efficiently managing agricultural irrigation is vital for food security today and into the future under climate change. Yet, evaluating agriculture’s hydrological impacts and strategies to reduce them remains challenging due to a lack of field-scale data on crop water consumption. Here, we develop a method to fill this gap using remote sensing and machine learning, and leverage it to assess water saving strategies in California’s Central Valley. We find that switching to lower water intensity crops can reduce consumption by up to 93%, but this requires adopting uncommon crop types. Northern counties have substantially lower irrigation efficiencies than southern counties, suggesting another potential source of water savings. Other practices that do not alter land cover can save up to 11% of water consumption. These results reveal diverse approaches for achieving sustainable water use, emphasizing the potential of sub-field scale crop water consumption maps to guide water management in California and beyond.

The application of quasiexperimental impact evaluation to remotely sensed measures of deforestation has yielded important evidence detailing the effectiveness of conservation policies. However, researchers have paid insufficient attention to the binary and nonrepeatable structure of most deforestation datasets. Using analytical proofs and simulations, we demonstrate that many commonly employed econometric approaches are biased when applied to binary and nonrepeatable outcomes. The significance, magnitude and even direction of estimated effects from many studies are likely incorrect, threatening to undermine the evidence base that underpins conservation policy adoption and design. To address these concerns, we provide guidance and new strategies for the design of panel econometric models that yield more reliable estimates of the impacts of forest conservation policies.

Forest fire frequency, extent, and severity have rapidly increased in recent decades across the western United States (US) due to climate change and suppression-oriented wildfire management. Fuels reduction treatments are an increasingly popular management tool, as evidenced by California's plan to treat 1 million acres annually by 2050. However, the aggregate efficacy of fuels treatments in dry forests at regional and multi-decadal scales is unknown. We develop a novel fuels treatment module within a coupled dynamic vegetation and fire model to study the effects of dead biomass removal from forests in the Sierra Nevada region of California. We ask how annual treatment extent, stand-level treatment intensiveness, and spatial treatment placement alter fire severity and live carbon loss. We find that a ∼30% reduction in stand-replacing fire was achieved under our baseline treatment scenario of 1,000 km² year⁻¹ after a 100-year treatment period. Prioritizing the most fuel-heavy stands based on precise fuel distributions yielded cumulative reductions in pyrogenic stand-replacement of up to 50%. Both removing constraints on treatment location due to remoteness, topography, and management jurisdiction and prioritizing the most fuel-heavy stands yielded the highest stand-replacement rate reduction of ∼90%. Even treatments that succeeded in lowering aggregate fire severity often took multiple decades to yield measurable effects, and avoided live carbon loss remained negligible across scenarios. Our results suggest that strategically placed fuels treatments are a promising tool for controlling forest fire severity at regional, multi-decadal scales, but may be less effective for mitigating live carbon losses.

Marine protected areas (MPAs) are widely used for ocean conservation, yet the relative impacts of various types of MPAs are poorly understood. We estimated impacts on fish biomass from no-take and multiple-use (fished) MPAs, employing a rigorous matched counterfactual design with a global dataset of >14,000 surveys in and around 216 MPAs. Both no-take and multiple-use MPAs generated positive conservation outcomes relative to no protection (58.2% and 12.6% fish biomass increases, respectively), with smaller estimated differences between the two MPA types when controlling for additional confounding factors (8.3% increase). Relative performance depended on context and management: no-take MPAs performed better in areas of high human pressure but similar to multiple-use in remote locations. Multiple-use MPA performance was low in high-pressure areas but improved significantly with better management, producing similar outcomes to no-take MPAs when adequately staffed and appropriate use regulations were applied. For priority conservation areas where no-take restrictions are not possible or ethical, our findings show that a portfolio of well-designed and well-managed multiple-use MPAs represents a viable and potentially equitable pathway to advance local and global conservation.

Clean-cooking transitions have the potential to generate large public health, environmental and societal gains for 2.6 billion people in the Global South. Here we use data from Ghana’s largest household energy survey (n = 7,389) to provide two main insights. First, regression analysis of 13 commonly cited socio-economic and demographic determinants of household fuel use indicates remarkably different relationships with clean-fuel use at different stages of the transition process. We propose a stage-based transition framework that can help inform the rollout of clean-cooking interventions. Second, we identify factors that are associated with the exclusive use of liquefied petroleum gas (LPG) using a statistically powered sample of exclusive LPG users (n = 693). We show that, all else equal, increases in wealth and urbanicity are not—contrary to conventional wisdom—associated with a transition from primary to exclusive LPG use. Whereas further research is needed to determine causality, our findings highlight the potential for more careful measurement, isolating each stage of the clean-cooking transition, to inform new insights and policy opportunities.

Emerging evidence suggests that air pollution may play a role in shaping suicide risk by altering brain function. However, this link is difficult to quantify and has yet to be investigated in China, where 16% of global suicides occur. Here we apply a statistical model that leverages random increases in particulate pollution (PM_2.5) due to meteorological conditions to comprehensive data on suicide rates across Chinese counties. We find that a 1 s.d. (σ) increase in PM_2.5 raises weekly suicide rates by ∼25%. This effect occurs without delay, consistent with neurobiological evidence that PM_2.5 influences emotional regulation and impulsive–aggressive behaviour. Effects are sex and age specific; women over 65 exhibit significantly higher vulnerability. We estimate that PM_2.5 reductions under China’s Air Pollution Action Plan prevented 13,000–79,000 (95% confidence interval) suicides over 2013–2017, accounting for ∼10% of this period’s observed suicide rate decline. Our findings uncover a causal link between particulate pollution and suicide, adding urgency to calls for pollution control policies across the globe.

Offshore renewable energy, particularly wind farms, is rapidly expanding globally and has become an essential component of many coastal nations’ decarbonization plans, including the United States. The addition of these physical structures to the marine space may impact fish production and may preclude fishers from traditional fishing grounds - both of which have the potential to affect fisheries outcomes. Understanding the socioeconomic and sociocultural impacts of implementing offshore wind is crucial to determining appropriate mitigation strategies and to developing data collection, monitoring, and adaptive management strategies. This review synthesizes quantitative and qualitative indicators that have been used to assess the impact of fisheries preclusion and shifts in fished species’ biomass on fishery participants. By providing a description of the indicator, a list of the datasets required to calculate its value, and a list of studies that used the indicator, this review can serve as a guide to those designing monitoring plans to determine socioeconomic and sociocultural offshore wind impacts.

Human–wildlife conflict is an important factor in the modern biodiversity crisis and has negative effects on both humans and wildlife (such as property destruction, injury, or death) that can impede conservation efforts for threatened species. Effectively addressing conflict requires an understanding of where it is likely to occur, particularly as climate change shifts wildlife ranges and human activities globally. Here, we examine how projected shifts in cropland density, human population density, and climatic suitability—three key drivers of human–elephant conflict—will shift conflict pressures for endangered Asian and African elephants to inform conflict management in a changing climate. We find that conflict risk (cropland density and/or human population density moving into the 90th percentile based on current-day values) increases in 2050, with a larger increase under the high-emissions “regional rivalry” SSP3 - RCP 7.0 scenario than the low-emissions “sustainability” SSP1 - RCP 2.6 scenario. We also find a net decrease in climatic suitability for both species along their extended range boundaries, with decreasing suitability most often overlapping increasing conflict risk when both suitability and conflict risk are changing. Our findings suggest that as climate changes, the risk of conflict with Asian and African elephants may shift and increase and managers should proactively mitigate that conflict to preserve these charismatic animals.