Conference Agenda

Protected areas are the most widely used instrument for biodiversity conservation, yet their socioeconomic effects on nearby populations remain contested, particularly in low income contexts where livelihoods depend heavily on natural resources. This paper evaluates the impact of terrestrial protected areas on rural household well being in Madagascar, exploiting geolocated socio-demographic surveys covering the period of rapid protected area expansion between 2008 and 2021. To support identification, we draw on an earlier survey wave from 1997 to assess the plausibility of parallel trends prior to treatment. We combine spatially derived socio environmental indicators with genetic matching and difference in difference to construct a credible counterfactual. The study follows a pre analysis plan registered before any outcome analysis, including an ex ante power calculation indicating the ability to detect effects of approximately 7.5 wealth percentiles. We find no statistically significant average effect of protected area creation on the wealth index of households located within 10 km of protected areas established after 2008. A series of robustness checks using alternative data sources and specifications supports this result. The absence of an average effect may reflect offsetting positive and negative mechanisms, heterogeneous impacts across households or sites, or limited implementation capacity in a context of weak governance and chronic underfunding of protected areas.

Wildlife hunting is a major driver of biodiversity losses, but its relationship with poverty alleviation remains poorly understood. Using nationally representative data (the 2019/20 Cambodia Socio-Economic Survey), this paper presents augmented inverse probability weighting (AIPW) estimates of the impact of benefiting from the Equity Card, the largest poverty-alleviation program in Cambodia, on wildlife hunting in rural areas within 20km of Protected Areas. We find that the Equity Card leads to a ~14% reduction in wildlife hunted (as measured by the monetary value of hunted wildlife), driven mostly by reductions in subsistence hunting (which drops by ~28%); results which are robust to the influence of unobserved confounders. Calculating the implicit monetary benefit obtained by a household through the Equity Card on average, we find that for each riel spent on poverty alleviation in rural regions near Conservation Areas the value of wildlife hunted for subsistence drops by ~0.42 riels, indicating the cost-effectiveness of such programs. We conclude that poverty policy can complement conservation policy and discuss further policy options.

International trade in food commodities is a major driver of global biodiversity loss through the conversion of forests to agriculture. Yet conventional deforestation metrics overlook ecological variation. We introduce a Biodiver- sity Risk indicator that weights deforested hectares by species vulnerability and endemism, offering a more nuanced assessment of biodiversity impacts from agricultural land-use change. Linking spatially explicit deforestation data with food trade flows, we uncover strong mismatches between countries’ Deforestation Footprint and Biodiversity Risk. Indonesia, despite lower deforestation volumes than Brazil, emerges as the most impacted country due to high species vulnerability and specific crop conversion patterns. Commodity-level analysis distinguishes locally consumed crops (e.g., meat, cassava, rice) from globally traded biodiversity-intensive commodities (e.g., palm oil, soy, natural rubber), offering new insights for targeted interventions. Our findings underscore the need to integrate biodiversity metrics into supply-chain governance and deforestation policies to promote more ecologically responsible trade.

Higher-income households generate disproportionately large environmental footprints, yet most studies focus solely on climate change and rely on input-output methods with limited product-level granularity. This paper introduces a novel life cycle assessment (LCA) model that combines EU Household Budget Survey microdata with the JRC Consumption Footprint database, assessing 16 environmental impact categories and converting them into monetised externalities.

Our results reveal substantial footprint inequality across the EU: households in the top income quintile generate a footprint 1.77 times larger than those in the bottom quintile, with considerable variation across countries. Food consumption contributes most to this inequality (49%), followed by mobility (21%) and housing (18%). Inequality in mineral and metal depletion is particularly pronounced (ratio of 2.39), driven mainly by mobility choices. Higher-income households not only consume more but also select more environmentally intensive products, particularly meat and private car transport.

When assessed against planetary boundaries, high-income households transgress seven boundaries while low-income households transgress five. Only high-income households exceed safe operating limits for freshwater and marine eutrophication, and they transgress the minerals and metals boundary by 2.6 times while lower-income households remain within safe limits.

These findings carry direct policy implications. Green transition measures in food, mobility and resource extraction may disproportionately affect those contributing least to environmental degradation. Policies targeting climate change and particulate matter should account for food-driven inequality, while measures addressing mineral depletion should focus on mobility patterns. Monetising external costs reveals that wealthy households impose substantially higher absolute damages on society, supporting pricing mechanisms aligned with the polluter pays principle.

Stated preference methods are central to non-market valuation but remain vulnerable to hypothetical bias, raising concerns about the credibility of resulting welfare estimates. This study provides a randomized, prospective evaluation of widely used ex-ante hypothetical bias mitigation techniques within a large discrete choice experiment (DCE) on coastal bathing-site management. The DCE is administered to 3,312 recreational users in the Gulf of Gdańsk and the Vistula Lagoon region and elicits willingness to travel for improvements in safety and information attributes, with travel distance serving as the numéraire. The experimental design varies four mitigation levers: (i) pre-task scripts (cheap talk, solemn oath, none), (ii) the presence of opt-out reminders, (iii) the position of the distance attribute within the choice task, and (iv) DCE menu size (two versus three alternatives). A novel embedded stress test choice featuring an extreme travel distance is used as an artificial indicator of respondents’ susceptibility to hypothetical bias. The results show that placing the distance attribute first consistently increases the share of respondents failing the stress test, suggesting that attempts to enhance cost salience through attribute ordering may backfire. Among the evaluated countermeasures, the solemn oath script performs best, substantially reducing the proportion of bias-prone respondents across both menu sizes. Cheap talk and opt-out reminders exhibit weaker and more context-dependent effects and, in some cases, prove counterproductive. Overall, the findings demonstrate that hypothetical mitigation techniques not only affect the prevalence of implausible responses but also shape baseline preferences and cost sensitivity. The study underscores the importance of careful experimental design and highlights solemn oath scripts as a particularly robust tool in non-monetary DCE contexts.

Coastal bathing delivers large welfare benefits but exposes recreationists to low-probability, high-salience microbial risks that are likely to become more frequent under climate change. Because these risks are largely invisible, behaviour and welfare depend on beliefs and the effectiveness of risk communication. We provide causal evidence on how pathogen-risk information affects preferences and recreation demand using a three-wave panel survey of users of the Gulf of Gdańsk and the Vistula Lagoon (Poland). A stratified national sample identified 3,312 active coastal users in Wave 1 (spring 2024); 2,588 respondents returned in Wave 2 (summer 2024), where they were randomly assigned to receive either minimal information or increasingly detailed pathogen-risk scripts, and then completed a repeated beach-site discrete choice experiment. Approximately one year later (spring 2025), 1,507 users completed a policy-referendum discrete choice experiment on programs combining water-quality improvements, monitoring frequency, and household costs, alongside a repeated travel-cost module capturing multi-day trips and beach outings. Information treatments significantly increased objective and self-assessed knowledge and selectively raised willingness to travel/pay for risk-relevant attributes – especially frequent water-quality monitoring and water-quality improvements – while leaving unrelated attributes largely unchanged. Travel-cost models indicate that information affects trip-taking behaviour, yet the marginal travel-cost sensitivity remains stable, consistent with a demand shift rather than a change in the “price” slope. The results imply that welfare estimates are information-dependent and that credible risk communication can function as a scalable, low-cost complement to traditional coastal health-risk management.