Agriculture is the product of a complex mixture of behavioural, biophysical and market drivers. Understanding how these factors interact to produce crops and livestock for food has been the focus of economic investigation for many years. The advent of optimisation algorithms and the exponential growth in computing technology has allowed significant growth in mathematical modelling of the dynamics of agricultural systems. The complexity of approaches has grown in parallel with the availability of data at increasingly finer resolutions. Farm-level models have been widely used in agricultural economic studies to understand how farmers and land owners respond to market and policy levers. This book provides an in-depth description of different methodologies and techniques currently used in farm-level modelling. While giving an overview of the theoretical grounding behind the models, an applied approach is also used. Case studies range from the application of modelling to policy reforms and the subsequent impacts on rural communities and food supply. This book also provides descriptions of the use of farm-level models in much wider fields such as aggregation and linking with sectoral models. Its purpose is to show the reader the methods that have been employed to inform decision-makers about how to improve the economic, social and environmental goals required to achieve the aims of multidimensional policy.

This book, which is the first to be published in the emerging field of farm-level microsimulation, highlights the different methodological components of microsimulation modelling: hypothetical, static, dynamic, behavioural, spatial and macro–micro. The author applies various microsimulation-based methodological tools to farms in a consistent manner and, supported by a set of Stata codes, undertakes analysis of a wide range of farming systems from OECD countries. To these case studies, O’Donoghue incorporates farming policies such as CAP income support payments, agri-environmental schemes, forestry planting incentives and biomass incentives – in doing so, he illuminates the merits of microsimulation in this environment.

Food Systems Modelling emphasizes sustainability, including the impact of agriculture and food production on profits, people and environment, with a particular focus on the ability of humanity to continue producing food in the midst of global environmental change. Sections introduce the purpose of models, the definition of a food system, the importance of disciplinary, interdisciplinary, and transdisciplinary inquiry, cover specific branches of modeling in the sustainability of food systems, and wrestle with the challenge of communicating modeling research and appropriately integrating multiple dimensions of sustainability. This book will be a welcomed reference for food scientists, agricultural scientists, nutritionists, environmental scientists, ecologists, economists, those working in agribusiness and food supply chain management, community and public health, and urban and regional planning, as well as academicians and graduate students interested in the sustainability of food systems. - Emphasizes sustainability, including the impact of agriculture and food production on profits - Focuses on the ability of humanity to continue producing food in the midst of global environmental change - Deciphers what models can teach us about food system sustainability

Systems approaches for agricultural development are needed to determine rational strategies for the role of agriculture in national development. Mathematical models and computer simulation provide objective tools for applying science to determine and evaluate options for resource management at field, farm and regional scales. However, these tools would not be fully utilizable without incorporating social and economic dimensions into their application. The second international symposium, Systems Approaches for Agricultural Development, held in Los Baños, 6-8 December 1995, fostered this link between the bio-physical sciences and the social sciences in the choice of keynote papers and oral presentations, a selection of which is included in this book. The book's contents further reflect how systems approaches have definitely moved beyond the research mode into the application mode. The large number and high quality of interdisciplinary research projects reported from different parts of the globe, to determine land use options that will meet multiple goals and yet sustain natural resource bases, is a key indicator of this `coming of age'. At the farm level, where trade-off decisions between processes and products (commodities) feature strongly, much progress is also evident in the development of systems-based tools for decision making. This book will be of particular interest to all agricultural scientists and planners, as well as students interested in multidisciplinary and holistic approaches for agricultural development.

Microsimulation Modelling involves the application of simulation methods to micro data for the purposes of evaluating the effectiveness and improving the design of public policy. The field has been applied to many different policies within both government and academia. This handbook describes and discusses the main issues within the field.

When talking about modelling it is natural to talk about simulation. Simulation is the imitation of the operation of a real-world process or systems over time. The objective is to generate a history of the model and the observation of that history helps us understand how the real-world system works, not necessarily involving the real-world into this process. A system (or process) model takes the form of a set of assumptions concerning its operation. In a model mathematical and logical assumptions are considered, and entities and their relationship are delimited. The objective of a model – and its respective simulation – is to answer a vast number of “what-if” questions. Some questions answered in this book are: What if the power distribution system does not work as expected? What if the produced ships were not able to transport all the demanded containers through the Yangtze River in China? And, what if an installed wind farm does not produce the expected amount of energyt? Answering these questions without a dynamic simulation model could be extremely expensive or even impossible in some cases and this book aims to present possible solutions to these problems.

Agricultural households, both in the European Union and world-wide, have experienced important changes during the last three decades. This book covers recent advances both in family economics and in modelling the relationship between the farm-household and the farm-firm. Both theoretical and empirical aspects of Agricultural Household Modelling and Family Economics are also discussed, providing a timely contribution to research in this area.

Types of economic deforestation models. Household and firm-level models. Regional-level models. National and macro-level models. Priority areas for future research.

The study presented in this report was commissioned by the Technical Centre for Agricultural and Rural Cooperation (CTA) as a member of the Global Open Data for Agriculture & Nutrition (GODAN) initiative, and was conducted by SB Consulting (SBC4D). The objective of the research is to understand the role of farmer organisations (FO) and cooperatives in the agriculture data ecosystem. These organisations have long been recognised to play an important role in society that translates into the improvement of living conditions of their members, particularly the low-income earning population. More than 40% of households in Africa are member of a cooperative society ([ILO-2000]) and the cooperative movement is Africa’s biggest nongovernmental organisation. The key question this report explores is the role of these organisations in the emergent “data revolution.” How can they ensure that this data revolution benefits their members and the smallholder farmers in general, and at the same time contribute to the revolution by providing valuable information to policy makers or other stakeholders of the ecosystem?