Ruth Sofie Hillesund (p), Lennart Kokemohr, Klaus Mittenzwei

Raja Chakir

The four strategic goals for agricultural policy in Norway are food security, maintaining agriculture across the country, increased value creation, and sustainable agriculture with lower emissions of greenhouse gases. In this paper, we will investigate how organic agriculture could be a possible manner to reach the goal of agriculture across the country. We observe a structural change in Norwegian agriculture, highlighted by a decline in the number of conventional and organic active farms. In Norway, agriculture receives direct payments for the production of animals and plants, and support for more environmental manners. Organic farms receive an additional payment on top of general direct payment. On average, an organic farm receives more subsidies than a conventional farm. We use data from the entire Norwegian farm population, including subsidies, both organic and conventional, numbers of animal, crop area, and location. We will investigate the difference in the probability of an organic and a conventional farm exiting the agriculture sector. We find that being an organic farm has a lower probability to exit compared to a conventional farm. We control for factors such as age, farm area, production types, direct payment, rurality etc.. Organic farms have a lower exit rate, which could imply less structural change for organic farms and, hence, indicate a more sustainable and robust type of farming.

Tamás Krisztin (p), Felicity Addo, Gregor Kastner, Alexander Mozdzen

Klaus Mittenzwei

The global climate crisis has conceived the need for impactful policies reducing greenhouse gas emissions across all sources, including emissions stemming from agricultural expansion. In order to study the effectiveness of mitigation policies, statistical methods need to take into account complex biophysical and socio-economic processes. We propose a Bayesian spatio-temporal model for exploring the impact of agricultural subsidies on land usage while simultaneously controlling for other relevant drivers. We combine recent developments in the literature on land use models with a Bayesian nonparametric prior in order to cluster areas which exhibit similar results of the policy in question. We control for individual impacts of essential spatial processes and explicitly model spillovers between regions. Additionally, we develop a suitable Markov chain Monte Carlo (MCMC) algorithm and test the model in an extensive simulation study.

Using European regional data, we investigate the effectiveness of mitigation policies concerning agricultural expansion across Europe and reveal the diversity of the problem. Our model offers a novel approach in understanding the geographical variability in policy impacts, taking into account local environmental, economic, and social conditions. By identifying regions with similar policy outcomes, our study not only aids in assessing current policy effectiveness but also provides valuable insights for future policy formulation. This is particularly crucial in tailoring location-specific strategies that can more effectively address the unique challenges and opportunities in different areas.

The outcomes of our research have wide-reaching implications for policymakers, environmentalists, and agricultural stakeholders. By offering a nuanced understanding of how agricultural subsidies influence land use across varied European regions, our study contributes to the global effort in combating climate change through more informed and effective agricultural policies. Our findings highlight the importance of considering spatial heterogeneity in policy impacts, advocating for more regionalized approaches in environmental planning and management.

François Bareille, Raja Chakir (p), Derya Keles

Tamás Krisztin

This study addresses the pressing issue of land use adaptation to climate change. With unprecedented shifts in temperature, precipitation patterns, and extreme weather events, understanding how human activities, particularly land use change, will respond and adapt is essential. We assess how land use changes in Europe adapt to climate change both in the short term and long term using panel data models and long-differences analyses respectively. The study integrates data from Corine Land Cover changes observed between 1990 and 2018 and ERA5-land sub-daily climate reanalysis data spanning from 1660 to 2019. Using these detailed data at very fine spatial resolution (10km*10km) and over a long time period (1990-2018), we examine the impacts of climate on changes on land allocation between agriculture, forest, urban and other uses. Simulations of climate change scenarios will provide how the land sector will react in face of new climate conditions.