Farm Structural Change: Exploring Patterns and Drivers in European Farming Systems

The primary objective of this thesis is to develop and apply methodologies for analyzing farm structural change, utilizing both sample and census data, and incorporating information from various domains. The question of how farms operate and interact with their environment relates to adaptation and transformation, which drive structural change in farms. This change encompasses several dimensions, including the number of active farms and how farmers alter their production, such as their specialization or economic size. The thesis is divided into two main parts, with the first part presenting a novel framework for estimating farm structural change at both the farm and regional levels. This framework, known as the market share model, is adapted from marketing science and is shown to be effective in tracking, explaining, and predicting farm structural change. The model is improved through data augmentation and country-specific representations, enabling a better understanding of farm structural developments in Germany, European Union countries, and Norway. The thesis also addresses the importance of accounting for path dependency in farm structural change, as farm structures are relatively stable due to the medium- to long-term nature of investment decisions regarding agricultural land and machinery. The second part of the thesis focuses on farm interactions and land market competition, and develops new indicators to measure the competitiveness of neighboring farmers, considering historic growth and contemporary competition. The results demonstrate that increased competition, as measured by these new indicators, is associated with higher exit rates, highlighting the importance of considering farmer interactions and differentiating among farm groups. Overall, the thesis shows that individual farm-level decisions collectively shape the trajectory of structural change in the farming sector, and that accounting for path dependency and neighborhood effects is crucial for understanding farm structure developments. The findings have significant implications for understanding farmers' exit decisions and the resulting changes in farm structure. The methods presented in this thesis provide a valuable toolkit for analyzing changes in farm structure, enabling researchers and policymakers to gain a deeper understanding of the complex factors driving these changes.