FG Volkswirtschaftslehre, insbesondere Umweltökonomie
Agri-environment schemes (AES) are typically measure-based, meaning that farmers are rewarded based on the implementation of specified conservation measures. However, result-based schemes have emerged as a promising alternative, whereby farmers are rewarded based on the achievement of specified conservation goals such as the occurrence of a particular species on their land. An advantage of result-based AES, which has received insufficient attention in the literature, is that they incentivise the spatial targeting of farmers to areas with most suitable habitat conditions. In our analysis, we focus on the presence of pre-existing landscape elements such as hedges, trees and water bodies, as an important habitat condition that positively impacts many species and therefore increases the likelihood of their occurrence. Farmers are likely to consider this aspect in their decision-making process and conduct spatial targeting when participating in result-based schemes. In contrast, the presence of landscape elements and the resulting likelihood of species occurrence does not play a role in farmers’ participation in measure-based schemes. This paper develops a generic ecological-economic model to gain an understanding of the extent to which different ecological and economic parameters affect the comparative cost-effectiveness of result-based and measure-based AES against this newly analysed aspect of landscape elements as an example of spatial targeting. In terms of policy recommendations, the paper provides general insights into the extent to which the analysed parameters affect the comparative cost-effectiveness of the two schemes.
Limiting global warming in line with the Paris Agreement requires net-zero emissions by mid-century. To address uncertainties in this transition, prior research has developed low-carbon scenarios. We contribute by eliciting expert judgement through online surveys with 21 experts and applying the Cross Impact Balances method to construct exploratory qualitative scenarios for the European Union. These scenarios complement quantitative approaches and reflect interactions among financial markets, technological innovation, political economy, and climate policy variables. We identify two internally consistent scenarios: one aligned with mitigation goals and one diverging. The mitigation scenario leads to 1.5 °C warming and features high and stable CO2 prices, a green mandate from the European Central Bank, high-quality climate risk data, accelerated economic development, and reduced inequality, despite public resistance and corporate lobbying by high-carbon sectors. Within the expert-based scenario analysis, results indicate that green financial policies are not essential for shifting market expectations towards the low-carbon transition.
Jordan, among the world’s most water-scarce countries, faces severe irrigation challenges in Jordan Valley (JV), its primary agricultural hub. We examine the successful establishment of Water Users Associations (WUA) in JV, focusing on how unwritten social norms, values, and social networks – known as informal institutions – affected and shaped this process. Employing qualitative methods and a customized institutional analysis and development (IAD) framework, we analyse how historical experiences and tribalism influenced institutional change. We find that integrating tribal values, such as collective responsibility, into the WUA implementation process played a pivotal role in their successful establishment.
Restoration of degraded rangelands through rainwater harvesting (RWH) is an important intervention in arid and semi-arid regions to sustain rangeland productivity and ecosystem services. We conducted a cost-benefit analysis (CBA) to assess the economic viability of implementing contour ridges as an in situ rainwater harvesting technique to restore degraded rangelands in Jordan. Jordan has vast pastoral areas and faces significant water scarcity, which is expected to intensify under climate change. We assessed the benefits of three essential ecosystem services: forage production, water availability, and prevention of soil erosion, and compared them with the costs of implementing and maintaining contour ridges and the initial forage loss incurred during the establishment of the forage shrubs. Our research design combined model-based biophysical simulation and economic valuation. For the biophysical simulation, we used the Global Range (G-Range) model to estimate the increase in forage production and the Soil and Water Assessment Tool (SWAT) model to estimate improvements in water availability and soil erosion prevention. The CBA was conducted across five distinct rangeland classes, differentiated by average annual rainfall, land slope, and soil organic carbon (SOC), which allowed us to cover 75% of Jordanian rangelands. Economic valuation was performed by monetizing benefits and costs to 2022 U.S. dollars over a 15-year project lifespan and by calculating the net present value (NPV) using an 8% discount rate, with sensitivity analyses at 5% and 12%. We considered two scenarios: the first incorporated the benefit of increased water availability from shallow groundwater aquifers, while the second excluded this benefit to reflect the current policy restrictions on groundwater extraction. The results of the CBA revealed positive NPVs in the first scenario and negative NPVs in the second scenario across all rangeland classes. These findings highlight the importance of the benefit of increased water availability when evaluating large-scale restoration projects.
Economic experiments related to biodiversity conservation policies provide valuable insights into how individuals respond to specific policy designs. However, they provide limited guidance on how to design cost-effective conservation policies at the landscape level. Ecological-economic models – integrating ecological dynamics with economic decision-making in optimization procedures – are well-suited to this purpose. Yet they nearly always assume purely profit-maximizing behaviour, overlooking deviations from this behaviour observed in practice. Our methodological aim is to combine these two approaches by incorporating behavioural data from a charitable-giving based laboratory experiment with student participants into an established decision-support software based on an ecological-economic model. We empirically explore how pro-environmental motives might influence participation in agri-environment schemes (AES) through decision support software applied to meadow bird conservation. Adjusting the modelling procedure to reflect intrinsic motives, we compare outcomes with those generated under standard profit-maximization assumption. The results indicate that while behavioural motives can increase participation, their overall impact on cost-effective AES design recommendations remain modest.
Rising temperatures may negatively impact rural landscapes in temperate climates due to reduced yields in agriculture and forestry, an increased risk of biodiversity loss, changes in the local climate and a decrease in recreational value. One promising way to mitigate increasing land surface temperatures (LST) in rural landscapes is to implement land-use and land-cover changes as adaptation measures that retain precipitation in soils, water bodies, and groundwater to allow vegetation to evaporate more water to reduce LST in summer. We develop an integrated modelling procedure to identify cost-effective spatially differentiated adaptation measures in agriculture and forestry to mitigate LST increases. We define cost-effective adaptation in a landscape as maximizing LST mitigation for given costs. The procedure combines the results of a model that predicts the spatially differentiated effects of adaptation measures on LST with the results of an economic model that estimates the respective spatially differentiated costs in an optimisation algorithm. We demonstrate how the procedure works by applying it to the Elbe-Elster-county in Germany. We find that a substantial share of results can only be explained by considering spatially differentiated costs and mitigation impacts and not average values showing the importance of taking into account costs and impacts of measures in a spatially differentiated manner. We also compare results from our integrated modelling procedure with a (purely natural science) approach that selects those adaptation measures first which perform best in terms of LST mitigation and find that our approach leads to a better heat mitigation effect by a factor of 3.5 – 4.8.
