Conference Agenda

Food security lags economic development, raising questions of whether food insecure households can leverage local economic development of higher-return activities. In a dynamic model incorporating production and utility risk, household consumption and their livelihood portfolio are jointly optimized. The optimal portfolio depends on household proximity to a stochastic perceived minimum consumption threshold, conditional on past consumption. Using highly granular data on livelihood choices of smallholder farmers, severely food insecure households are found to smooth income ex-ante by allocating approximately 20\% more land to subsistence crops. The results help explain the lack of progress on global food security targets.

The agglomeration bonus (AB) consists of payments conditional on the contiguity of landowners' conservation areas. It is widely accepted that, because ABs encourage landowners to cooperate, they promote more cost-effective biodiversity conservation than homogeneous payments. This article challenges this conclusion by studying the impact of different AB designs, which may or may not encourage cooperation. Specifically, we show that differentiating the bonus between internal (within-landholding) and external (between-landholdings) boundaries affects the AB cost-effectiveness. Using an economic-ecological model and game theory, our simulations on realistic landscapes show that the most cost-effective ABs are those presenting relatively larger internal bonuses. Conversely, ABs with relatively larger external bonuses are less cost-effective, even if they foster cooperation across landowners.

Agri-environmental-climate schemes (AECS) can improve the provision of environmental goods and services from agriculture by compensating farmers for either implementing environmentally friendly management practices or obtaining ecological results. We contribute to the ongoing discussion on cost-effective designs of AECS by comparing the technical and environmental efficiency of farms participating in result-based and action-based schemes with a two-output Data Envelopment Analysis (DEA) model. This model also allows estimating shadow prices of biodiversity under each type of scheme. We use the Federal State of Bavaria (Germany), where a pilot result-based grassland conservation scheme has been implemented since 2015, as case study. In contrast to previous research, we uniquely measure farm ecological performance with a farm-level biodiversity index to test trade-offs between biodiversity provision and agricultural production. Our results show that there is room for simultaneously improving the economic and the biodiversity output without financial compensation. Farms participating in result-based schemes show higher efficiency scores but also higher opportunity costs for providing additional grassland species, likely due to different baselines. Building on our findings, further studies should strive to develop more advanced and generalizable empirical models.

Collective schemes for biodiversity conservation are seen as promising tools to encourage the connectivity of habitat conservation across landowners. Yet, despite being at the core of their design, cooperation and its underlying mechanisms have seldom been addressed in the literature on those schemes. We here assess the value of cooperation among landowners for biodiversity conservation, in the particular case of the agglomeration bonus (AB). Coupling an economic-ecological model with a coalition formation game, we explicitly assess the impacts of different rules governing group enrollment within the schemes on the AB cost-effectiveness. We show that the level of cooperation (groups' size) is a major determinant of AB cost-effectiveness. As it leads to the highest degree of cooperation, we demonstrate that open-list enrollment in the AB is the most cost-effective scheme, compared to closed-list AB, individual AB, or homogeneous payment.