Farm-Level Modelling : Techniques, Applications and Policy.

Intro -- Farm-level Modelling: Techniques, Applications and Policy -- Copyright -- Contents -- Contributors -- Foreword -- Reference -- Preface -- Acknowledgements -- 1 Policy Impact Assessment -- 1.1 Introduction -- 1.2 Evolution of EU Agricultural Policies and Parallel Development of Impact Models -- 1.3 The Widening Role of Farm-level Modelling in Impact Assessment -- 1.3.1 Interactions between activities -- 1.3.2 Farm heterogeneity -- 1.3.3 Agriculture-environment interactions -- 1.3.4 Dynamics and structural change -- 1.3.5 Market feedback -- 1.4 What Models Do We Need to Assess Tomorrow's Agricultural Policies? -- Notes -- References -- 2 Positive Mathematical Programming -- 2.1 Introduction -- 2.2 Review of Existing Methods -- 2.2.1 PMP, calibration and cost estimates -- 2.2.2 PMP and cost function characteristics -- 2.2.3 PMP models and latent activities -- 2.3 PMP Application for Policy Assessments -- 2.4 Conclusions -- Notes -- References -- 3 Modelling Farm-level Adaptations Under External Shocks -- 3.1 Introduction -- 3.2 Review of Existing Methodologies -- 3.3 LP Modelling -- 3.3.1 Land -- 3.3.2 Feed -- 3.3.3 Labour -- 3.3.4 Herd size -- 3.3.5 Exogenous adaptation measures -- 3.3.6 Modelling runs -- 3.3.7 Input data -- 3.4 Limitations -- 3.5 Application -- 3.5.1 Irish farms under climate change -- 3.5.2 The case of alternative farrowing housing for sows in the UK -- 3.6 Summary -- References -- 4 Farm-level Modelling, Risk and Uncertainty -- 4.1 Introduction -- 4.2 Review of Existing Models -- 4.3 The Utility Efficient Programming Model -- 4.3.1 Gross margin distributions -- 4.3.2 Calculation of spot price gross margins -- 4.3.3 Calculation of gross margins using futures markets -- 4.4 Application -- 4.4.1 Run 1: coupled area payments -- 4.4.2 Run 2: the decoupled Single Farm Payment (SFP).

4.4.3 Runs 3 and 4: spot prices and average prices -- 4.5 Limitations of the Model and Conclusions -- Notes -- References -- 5 Modelling Farm-level Biosecurity Management -- 5.1 Introduction -- 5.2 Review of Existing Methods -- 5.3 The Core Model: Adoption Decisions in Biosecurity Management -- 5.3.1 Multiple correspondence analysis (MCA) -- 5.3.2 Hierarchical clustering analysis (HCA) -- 5.3.3 Logistic regression -- 5.4 Empirical Application -- 5.4.1 Description of data -- 5.4.2 Analysis of data by MCA and hierarchical clustering -- 5.4.3 MCA and interpretation of the dimensions it generates -- 5.4.4 Additional explanatory variables -- 5.4.5 Clustering and characterization of the biosecurity practices -- 5.4.6 Logistic regression -- 5.5 Limitations and Discussion -- Notes -- Acknowledgements -- References -- 6: Modelling Farm Efficiency -- 6.1 Introduction -- 6.1.1 Policy context -- 6.1.2 Defining efficiency -- Technical efficiency -- Cost efficiency -- Total factor productivity -- 6.2 Review of Alternative Methodologiesto Examine Efficiency -- 6.2.1 Stochastic frontier analysis (SFA)2 -- 6.3 Examining the Efficiency of Irish Dairy Farms -- 6.3.1 Background to the research question -- 6.3.2 The theoretical model -- 6.3.3 Data sources -- 6.3.4 Model outputs -- Technical efficiency of Irish dairy farms: 1979-2012 -- Model validation -- 6.4 Conclusions and Relevance of Research Findings to Policy Makers -- Notes -- References -- 7: Quantifying Agricultural Greenhouse Gas Emissions and Identifying Cost-effective Mitigation Measures -- 7.1 Introduction -- 7.2 Quantifying On-farm GHGE missions -- 7.2.1 Moving beyond the farm gate: life cycle analysis (LCA) -- What is LCA? -- Why use LCA? -- What are the main steps in LCA? -- Guidance for undertaking LCA of food supply chains -- 7.2.2 Existing studies of GHG emissions in food supply chains.

7.2.3 Identifying ways of reducing GHG emissions -- 7.2.4 Challenges and limitations in the quantification of emissions -- Improving the comparability of results -- Dealing with interactions between measures -- Characterizing variability and uncertainty -- Data quality and availability, particularly in developing countries -- 7.3 Application -- 7.3.1 The Global Livestock Environmental Assessment Model (GLEAM) -- 7.3.2 The CAPRI model and the MITERRA-Europe assessment tool -- 7.3.3 The Livestock Environmental Assessment and Performance (LEAP) partnership -- 7.4 Concluding Remarks -- References -- 8: Moving Beyond the Farm: Representing Farms in Regional Modelling -- 8.1 Introduction -- 8.2 Review of Regional Modelling -- 8.2.1 Overview of aggregation issues under mathematical programming -- 8.2.2 Representing farms in farm-based regional modelling: conceptual issues -- 8.3 The Core Model -- 8.3.1 Limitations and challenges of the regional model -- Loss of farm-level accuracy -- Aggregation of farms -- Endogeneity of prices in product and input markets -- Calibration of the model -- Other limitations -- 8.4 Review of Regional Modelling Applications -- 8.4.1 Climate effects -- 8.4.2 Water resources -- 8.4.3 Environmental loadings from agriculture -- 8.4.4 Policy analysis -- 8.5 Application -- 8.5.1 Edwards Aquifer management -- EDSIM model structure -- Simulation results -- Main findings -- 8.5.2 Economic and groundwater use implications of climate change in the Ogallala Aquifer region -- Structure of the model -- Results -- Implications -- 8.6 Summary and Conclusions -- References -- 9: Farm-level Microsimulation Models -- 9.1 Introduction -- 9.1.1 Modelling complexity -- 9.2 Applications of Farm-level Microsimulation Modelling -- 9.2.1 Hypothetical analyses -- 9.2.2 Static modelling -- 9.2.3 Behavioural modelling -- 9.2.4 Dynamic modelling.

9.2.5 Impact of macroeconomic change -- 9.2.6 Spatial models -- 9.2.7 Environmental analysis -- 9.3 Conclusions and Future Directions -- Note -- References -- 10: Scaling Up and Out: Agent-based Modelling to Include Farmer Regimes -- 10.1 Introduction -- 10.2 Review of Approaches to Scaling -- 10.3 Core Model -- 10.4 Application -- 10.4.1 The Lunan catchment, east Scotland -- 10.4.2 Evaluation of regimes -- 10.4.3 Model verification -- 10.4.4 Results -- 10.4.5 Limitations -- 10.5 Summary and Conclusions -- Note -- References -- 11: Catchment-level Modelling -- 11.1 Introduction -- 11.2 Review of Existing Methodologies -- 11.2.1 Output-based integration -- 11.2.2 Scenario-based integration -- 11.2.3 Dynamic integration -- 11.3 Core Model -- 11.3.1 Estimating silt costs to the downstream water users -- Direct silt-related costs -- Indirect silt-related costs -- 11.4 Application -- 11.4.1 Case study of Dwangwa catchmentin central Malawi -- 11.4.2 Linear optimization model assumptions -- Model activities -- Household characteristics -- Slope of farmland -- 11.4.3 Results -- Payments for watershed services and land under SLM -- Silt costs savings and climate variation -- Silt costs savings from engaging in PWS in perspective -- 11.4.4 Limitations -- 11.5 Conclusion -- 11.5.1 Policy implications -- 11.5.2 General conclusions -- Notes -- References -- 12: Modelling Food Supply Chains -- 12.1 Introduction -- 12.2 Overview of Reasons to Model Supply Chains -- 12.2.1 Marketing margins models -- 12.2.2 Price transmission from farmers to consumers -- 12.2.3 Market structure models -- Processors' oligopoly -- Processors' oligopsony -- Farmers' cooperatives market power -- Successive oligopoly and oligopsony models covering the whole supply chain -- Bilateral oligopoly between cooperatives and processors and between processors and retailers.

12.3 Extension: a Supply Chain Model Considering Inventories -- 12.3.1 Derivation of the supply of storage equation -- 12.3.2 Econometric estimates -- 12.4 Final Remarks: Limitations in Modelling Supply Chains -- Notes -- References -- 13: Linkage of a Farm Group Model to a Partial Equilibrium Model* -- 13.1 Introduction -- 13.2 Review of Existing Models -- 13.3 The CAPRI Approach -- 13.3.1 Farm types in the CAPRI-FT layer -- 13.3.2 Output market linkage -- 13.3.3 Land market linkage -- 13.4 Limitations -- 13.5 Application -- 13.5.1 Results -- 13.6 Summary and Conclusions -- Notes -- References -- 14: Conclusions: The State-of-the-art of Farm Modelling and Promising Directions -- 14.1 A Look Across the State-of-the-art: Why All This Development? -- 14.2 Fostering Farm-level Modelling -- 14.2.1 Changes in (agricultural) policy instruments -- 14.2.2 Changes in relevance and understanding of policy impact indicators -- 14.2.3 Key biophysical or economics processes do not aggregate linearly -- 14.2.4 Simultaneous development of databases, computing power and techniques -- 14.3 Subjective View on Current Limitations and Promising Future Directions -- References -- Index.

This book describes the application of a wide variety of mathematical modelling techniques used to help carry out crucial tasks and decision making in farm management.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.