General Info

courseProgram

The course is organised in three blocks and fifteen modules. Its organising principle is that the economics is one and the institutions are many: the same analytical tools are applied to profoundly different agricultural settings and policy regimes, with no country treated as the default case.
Block A — Foundations (6 hours).
The economic problem and the logic of optimal choice (2 hours). Scarcity, opportunity cost and the production possibility frontier; the marginal rate of transformation. The farm problem as constrained optimisation: first-order conditions, the shadow price of the binding resource, the equimarginal principle. The production function and diminishing marginal returns; the value of the marginal product rule; the least-cost combination of inputs. The conditions under which the standard optimum fails to describe observed behaviour: risk, credit constraints, imperfect information, missing markets.
The global agri-food system (2 hours). Definition and structure of the agri-food system; supply chain and value chain. Coordination mechanisms: markets, hierarchies, hybrid arrangements. Property rights as a bundle; land tenure regimes worldwide and the empirical evidence on the link between tenure security and investment. The global farm size distribution and structural transformation. Concentration upstream and downstream; private standards; resources, yield gaps and price volatility.
Models, markets and evidence (2 hours). Positive and normative analysis. Demand, supply and equilibrium; elasticity and Engel's law. Economic incidence: who actually gains from a subsidy. Welfare analysis of price support: transfer, cost to consumers and taxpayers, deadweight loss, transfer efficiency. From theory to measurement: the fundamental problem of causal inference, selection bias and the main identification strategies; the measurement of technical efficiency and total factor productivity.
Block B — Sectors and markets (11 hours).
Comparing agricultural sectors (2 hours). A six-dimension method applicable to any country: macro position, land and farm structure, production mix, land and labour productivity, trade position, policy. The definitional traps in international comparison. Italy as a fully worked national case.
Measuring agri-food trade (2 hours). The accounting identity of apparent consumption; self-sufficiency ratio, import and export propensity, normalised trade balance; revealed comparative advantage and its fragility; concentration as a measure of exposure. Practical problems of trade data.
Why countries trade (2 hours). Absolute and comparative advantage; the gains from trade and their distribution; the sources of comparative advantage; intra-industry trade; the network structure of world staple trade; the limits of the theory and the food security argument.
Risk, uncertainty and insurance (3 hours). Risk and uncertainty; mapping farm risks and the distinction between idiosyncratic and systemic risk. Risk aversion, expected utility, the certainty equivalent and the risk premium; consequences for farm decisions. Risk layering and matching the instrument to the layer; on-farm strategies and market instruments. Why agricultural insurance markets fail; index insurance; risk at food system level.
Digital agriculture (2 hours). Technologies classified by the economic friction they remove. On-farm effects: the marginal principle at finer resolution. Off-farm effects: price dispersion and information asymmetry. Equity of adoption; environmental effects and the rebound effect. Ownership of farm data. Enabling conditions and governance.
Block C — Policy (14 hours).
Why governments intervene (2 hours). The market failures that actually occur in agriculture; the externality diagram; the three classic farm problems — the long-run price problem, volatility and structural adjustment. The equity case and the distinction between farm income support and rural poverty reduction. Multifunctionality. Government failure and the political economy of intervention.
The instrument catalogue (3 hours). Border measures, administered prices and public procurement, input subsidies, insurance-based support, decoupled payments, general services. For each: objective, who pays, incidence, transfer efficiency, production distortion, administrative requirements. Instruments for environmental objectives.
Measuring support (2 hours). Why the public budget does not measure support; support through the price and the gap against the border price; the OECD Producer Support Estimate and the family of indicators; the WTO Agreement on Agriculture and the amber, blue and green boxes; what these indicators cannot tell you.
Five regimes compared (3 hours). European Union, United States, Japan and Korea, India, Sub-Saharan Africa: instruments chosen, reasons for the choice, measured outcomes. New Zealand as the counterfactual. The political economy of the persistence of support.
Rural development and territorial policy (2 hours). The analytical case for territorial policy; top-down and bottom-up delivery models; the LEADER method and its counterparts worldwide; rural employment guarantees; the evaluation of territorial programmes.
Producer organisations and collective action (2 hours). The problem producer organisations solve; the free-rider problem and selective incentives; organisational forms; competition law across jurisdictions; empirical evidence and the causes of failure.
Trade policy and the multilateral system (2 hours). Welfare analysis of a tariff; comparison of border instruments; tariff escalation; non-tariff measures; export restrictions and food price crises; the Agreement on Agriculture and the open disputes.
Complementary teaching activities (7 hours). Every module includes at least one classroom exercise, carried out in pairs or small groups, in which students apply the analytical tools to a concrete case and discuss the outcome in plenary. Two sessions are held at computers and are devoted to retrieving and documenting data from the international databases (FAOSTAT, OECD.Stat, UN Comtrade). The final two hours are devoted to revision and preparation for the examination.

examMode

Assessment consists of a single final written examination, in English, lasting two hours.
The examination comprises three open-answer questions, chosen by the student from a wider set of tracks. The tracks do not call for the memorised exposition of a topic, but for the application of the analytical tools of the course to a concrete situation in the agri-food system.
The final mark is expressed out of thirty. Each of the three questions contributes equally to the mark. The examination is passed with a mark of at least 18/30. In marking each answer, account is taken, in this order, of analytical correctness, of the relevance of the application to the case proposed, of the documentation of the data used, and of clarity of exposition. Distinction (lode) is awarded to students who, having obtained the maximum score, demonstrate command of the analytical tools and the ability to connect the contents of different modules autonomously.
Students are advised of one marking criterion that follows from the nature of the discipline itself: making the limits of one's own analysis explicit contributes positively to the mark. An answer that states which figure it considers least sound, or which objective its recommendation sacrifices, scores above an answer that presents every element as settled.
The exercises carried out in class during the course are not separately assessed, but their content forms part of the examination syllabus.
The examination is held entirely in English.

books

he course does not adopt a single textbook. For each module the relevant chapters and pages are indicated; slides and links to the sources are made available on the university teaching platform for the course.
Foundations of agricultural economics and applied microeconomics
• Norton, G. W., Alwang, J., Masters, W. A. (2021), Economics of Agricultural Development, 4th ed., Routledge — Ch. 1-5 and Ch. 8. Main reference text of the course.
• Nguyen, B., Wait, A. (2024), Essentials of Microeconomics, 2nd ed., Routledge — Ch. 1 (pp. 3-6), Ch. 2 (pp. 9-13), Ch. 4 (pp. 29-36), Ch. 7 (pp. 55-64), Ch. 9 (pp. 71-79).
• Drummond, H. E., Goodwin, J. W. (2010), Agricultural Economics, 3rd ed., Pearson — Ch. 4 (pp. 50-59), Ch. 5 and appendices (pp. 60-83), Ch. 6 (pp. 89-92), Ch. 9 (pp. 131-143).
Comparative agricultural policy
• Anderson, K. (ed.) (2009), Distortions to Agricultural Incentives: A Global Perspective 1955-2007, World Bank — Introduction and the regional chapter on Africa or Asia. Open access: https://openknowledge.worldbank.org/handle/10986/2653
• OECD (annual), Agricultural Policy Monitoring and Evaluation, OECD Publishing — overview chapter and the country notes for the two assigned countries. Open access: https://www.oecd.org/agriculture/topics/agricultural-policy-monitoring-and-evaluation/
• WTO, Agreement on Agriculture — Articles 4-6 and Annex 2, to be read in the original. Open access: https://www.wto.org/english/docs_e/legal_e/14-ag.pdf
• Swinnen, J. (ed.) (2018), The Political Economy of Agricultural and Food Policies, Palgrave Macmillan.
Risk and insurance
• OECD (2009), Managing Risk in Agriculture: A Holistic Approach, OECD Publishing — the risk-layering framework.
• Carter, M., de Janvry, A., Sadoulet, E., Sarris, A. (2017), "Index insurance for developing country agriculture: a reassessment", Annual Review of Resource Economics, 9, pp. 421-438. https://doi.org/10.1146/annurev-resource-100516-053352
Digital agriculture
• Wolfert, S., Ge, L., Verdouw, C., Bogaardt, M.-J. (2017), "Big data in smart farming — a review", Agricultural Systems, 153, pp. 69-80. https://doi.org/10.1016/j.agsy.2017.01.023
• Klerkx, L., Jakku, E., Labarthe, P. (2019), "A review of social science on digital agriculture, smart farming and agriculture 4.0", NJAS — Wageningen Journal of Life Sciences, 90-91, 100315. https://doi.org/10.1016/j.njas.2019.100315
Supplementary teaching material
• Lecture slides, bibliographic references and links to the sources are made available on the university teaching platform for the course.
• Databases used in the computer sessions: FAOSTAT (https://www.fao.org/faostat/), OECD.Stat — Producer and Consumer Support Estimates (https://stats.oecd.org/), UN Comtrade (https://comtrade.un.org/), World Bank World Development Indicators (https://databank.worldbank.org/).

classRoomMode

Attendance is not compulsory, but it is strongly recommended.
The reason lies in the structure of the course itself. The course is organised in intensive teaching days, and a part of the teaching consists of classroom exercises in which the analytical tools are applied to concrete cases and the results discussed collectively. The slides made available on the university platform report the content of the exercises but not their discussion, which is the part in which analytical competence is actually built. The two computer sessions devoted to the international databases are likewise difficult to replace with individual study.
The examination syllabus is the same for attending and non-attending students and includes the content of the classroom exercises. There is no difference in assessment arrangements.
Students who are unable to attend regularly are invited to contact the lecturer at the beginning of the course, so that a reading path covering the applied part of the programme can be agreed. Slides, bibliographic references and links to the sources are made available to all students on the university platform.

bibliography

The following works are not required for the examination. They constitute the scientific basis on which the course is built and are indicated for students who wish to explore a topic in depth, or who intend to write a dissertation on agricultural economics and policy.
Farm structure, productivity and structural transformation
• Lowder, S. K., Sánchez, M. V., Bertini, R. (2021), "Which farms feed the world and has farmland become more concentrated?", World Development, 142, 105455. https://doi.org/10.1016/j.worlddev.2021.105455
• Ricciardi, V. et al. (2018), "How much of the world's food do smallholders produce?", Global Food Security, 17, pp. 64-72. https://doi.org/10.1016/j.gfs.2018.05.002
• Gollin, D., Lagakos, D., Waugh, M. E. (2014), "The agricultural productivity gap", Quarterly Journal of Economics, 129(2), pp. 939-993. https://doi.org/10.1093/qje/qjt056
• Hayami, Y., Ruttan, V. W. (1985), Agricultural Development: An International Perspective, Johns Hopkins University Press.
Property rights and land institutions
• Deininger, K., Feder, G. (2001), "Land institutions and land markets", in Handbook of Agricultural Economics, vol. 1, Elsevier, pp. 288-331.
• Goldstein, M., Udry, C. (2008), "The profits of power: land rights and agricultural investment in Ghana", Journal of Political Economy, 116(6), pp. 981-1022. https://doi.org/10.1086/595561
Policy instruments, incidence and welfare
• Just, R. E., Hueth, D. L., Schmitz, A. (2004), The Welfare Economics of Public Policy, Edward Elgar.
• Ciaian, P., Kancs, d'A., Swinnen, J. (2010), EU Land Markets and the Common Agricultural Policy, CEPS, Bruxelles.
• Jayne, T. S., Rashid, S. (2013), "Input subsidy programs in sub-Saharan Africa: a synthesis of recent evidence", Agricultural Economics, 44(6), pp. 547-562. https://doi.org/10.1111/agec.12073
• Anderson, K., Rausser, G., Swinnen, J. (2013), "Political economy of public policies: insights from distortions to agricultural and food markets", Journal of Economic Literature, 51(2), pp. 423-477. https://doi.org/10.1257/jel.51.2.423
• OCSE (2016), OECD's Producer Support Estimate and Related Indicators of Agricultural Support: Concepts, Calculations, Interpretation and Use (The PSE Manual), OECD Publishing.
International trade
• Balassa, B. (1965), "Trade liberalisation and 'revealed' comparative advantage", The Manchester School, 33(2), pp. 99-123.
• Martin, W., Anderson, K. (2012), "Export restrictions and price insulation during commodity price booms", American Journal of Agricultural Economics, 94(2), pp. 422-427. https://doi.org/10.1093/ajae/aar105
• WTO-UNCTAD (2012), A Practical Guide to Trade Policy Analysis, Cap. 1-2. Open access: https://www.wto.org/english/res_e/publications_e/wto_unctad12_e.pdf
Collective action and producer organisations
• Olson, M. (1965), The Logic of Collective Action, Harvard University Press — Cap. 1.
• Bellemare, M. F., Bloem, J. R. (2018), "Does contract farming improve welfare? A review", World Development, 112, pp. 259-271. https://doi.org/10.1016/j.worlddev.2018.08.018
• Ostrom, E. (1990), Governing the Commons, Cambridge University Press.
Rural development and policy evaluation
• Barca, F., McCann, P., Rodríguez-Pose, A. (2012), "The case for regional development intervention: place-based versus place-neutral approaches", Journal of Regional Science, 52(1), pp. 134-152. https://doi.org/10.1111/j.1467-9787.2011.00756.x
• Imbert, C., Papp, J. (2015), "Labor market effects of social programs: evidence from India's employment guarantee", American Economic Journal: Applied Economics, 7(2), pp. 233-263. https://doi.org/10.1257/app.20130401
Information, technology and empirical methods
• Jensen, R. (2007), "The digital provide: information technology, market performance and welfare in the South Indian fisheries sector", Quarterly Journal of Economics, 122(3), pp. 879-924. https://doi.org/10.1162/qjec.122.3.879
• Angrist, J. D., Pischke, J.-S. (2015), Mastering 'Metrics: The Path from Cause to Effect, Princeton University Press.
• Cunningham, S. (2021), Causal Inference: The Mixtape, Yale University Press. Open access: https://mixtape.scunning.com/

courseProgram

1. Importance of integrated pest management
2. Traditional monitoring strategies and potential innovations
3. Decision support systems (DSS)
Mathematical models for the description and prediction of insect populations
Statistical and mathematical models for the study of species distribution (MAXENT, Random Forest etc)
Measurement and estimation of insect populations
Monitoring strategies with innovative traps
Case studies
4. Proximal sensing in monitoring of main insects in agriculture and forestry
Monitoring with automated traps
YOLO technology and machine learning for pests detection and recognition
Case studies
5. Remote sensing in monitoring of main insects in agriculture and forestry
UAVs and sensors, data collection and processing
The use of satellite-collected data for assessing the activity of phytophagous insects
Case studies

examMode

The evaluation of knowledge will take place through a final written examination related to the course programme and the seminars held.

books

Students will be provided with ppt slides. The study will be integrated with scientific papers provided by the teacher

mode

Classes will take place in presence. However streaming will allow students to take the class

classRoomMode

Attendence is not required but strongly recommended

bibliography

Below are some of the scientific publications suggested to students:
- Review of CLIMEX and MaxEnt for studying species distribution in South Korea - Journal of Asia-Pacific Biodiversity (2018) - Dae-hyeon Byeon, Sunghoon Jung, Wang-Hee Lee
- A review: application of remote sensing as a promising strategy for insect pests and diseases management - Environmental Science and Pollution Research (2020) - Nesreen M. Abd El-Ghany, Shadia E. Abd El-Aziz, Shahira S. Marei
- Recent Advances in Forest Insect Pests and Diseases Monitoring Using UAV-Based Data: A Systematic Review - Forests (2022) - André Duarte, Nuno Borralho, Pedro Cabral, Mário Caetano
- Automatic Detection and Monitoring of Insect Pests—A Review - Agriculture (2020) - Matheus Cardim Ferreira Lima, Maria Elisa Damascena de Almeida Leandro, Constantino Valero, Luis Carlos Pereira Coronel, Clara Oliva Gonçalves Bazzo

courseProgram

Importance of digital approach and technological innovations in plant disease management.
Detection and monitoring of diseases and pathogens:
• Critical approach to diagnosis: when traditional techniques are enough and when not
• Advanced diagnostic methods:
o immunological techniques (ELISA, DBTIA, Lateral flow, etc.)
o molecular (standard PCR, Real-Time PCR (qPCR), loop-mediated isothermal amplification (LAMP), digital droplet PCR (ddPCR).
o biosensors
Assessment of the incidence of the disease and the damage caused by remote sensing:
satellite images, ultralight aircrafts and drones.
Assessment of structural damages to trees and risk related to plant stability in urban environments and control:
VTA, instrumental diagnosis (resistograph, tomograph, pulse hammer, Pressler’s pacifier, fracking meter, use of infrasound, Ground Probing Radar (GPR), Compressed Air Digging Systems (Air-Spade®, Dendrotherapy).
Bioinformatics approach to understanding pathogen biology through omics sciences (genomics, transcriptomics, proteomics, etc.);
Strategies for disease prevention and management in precision agriculture:
• forecast models
• monitoring networks
• decision support systems (DSS) for plant protection.
Optimization of the distribution of active ingredients: advantages and problems
Latest tools in plant protection:
• the genome editing
• nanotechnologies in plant protection
Disease control and improvement of their resilience to stress through biological agents:
• antagonistic micro-organisms,
• natural microbial communities (endophytes and epiphytes),
• supporting micro-organisms: PGPR and mycorrhizae

examMode

The exam, as a whole, will aim to verify the following educational objectives:
KNOWLEDGE AND ABILITY TO UNDERSTAND
The student must demonstrate to have acquired a comprehensive knowledge of the basics of plant protection in the context of digital agriculture; have clearly understood the basics of vegetal pathology. The student must demonstrate that he understood the ways of occurrence and spread of plant diseases and how to evaluate them with innovative tools; to have understood the main innovative diagnostic strategies and how to apply them correctly; to have a solid knowledge of the most technological innovations for preventive and containment defense from phytosanitary adversities, as described in the course.
ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING
Have understood how the management of phytosanitary problems must be carried out through digital and innovative approaches, such as pre- and post-onset strategies must be implemented to minimize phytopathological damage.
AUTONOMY OF JUDGMENT
Be able to face a phytopathology with the methodologies discussed in class or similar to them and show to be able to draw on the knowledge acquired in the course to better manage these issues.

CONDITIONS OF THE EXAMINATION:
• The Final Oral Exam focuses mainly on the topics of the Course Program and the knowledge acquired during seminars and exercises. To this the discussion of a topical topic assigned by the teacher at the end of the lessons can be added.
• If during the course of the Final Oral Exam cognitive gaps emerge on the part concerning the basics of plant pathology, a fundamental prerequisite for access to the course, the teacher reserves the right to deepen the assessment of the knowledge of these topics by the students, and to partially take them into account in the final score.
• The final score is made up of 90% of the outcome of the oral exam and 10% of the student’s teacher’s assessment of: active participation during the course and related activities; modalities of expression and mastery of the correct terminology; critical vision of the opportunities offered by technological innovations to address phytopathological problems; global mastery of matter (link between different topics).
• The calendar of exam session and the registration for exam is made through the University portal GOMP.
• Each student has the right to take the exam no more than 3 times per year (academic).

books

On the MOODLE portal the PowerPoint presentations of the lessons are made available, with graphic illustrations, photographs, videos and animations.
It also offers in-depth studies and examples related to some lessons, selection of scientific bibliography on the subject, and a forum for the exchange of views and information with the teacher.

mode

Frontal lessons in the classroom, presentations in PowerPoint with graphic illustrations, photos, video and animations. On Google Classroom will be offered: insights and examples of specific topics related to lectures, a selection of related scientific literature, exchange of information.
Practical lessons and laboratory training are also scheduled

classRoomMode

Although the attendance at the lessons of the Course in question is optional, a regular participation is strongly recommended.

bibliography

A selection of scientific bibliography on the subject is offered by the teacher.

courseProgram

The course is organised in three modules, for a total of 20 sessions of 2 hours each. Five sessions are practical Excel labs that progressively build the examination project on a single farm.
1. Presentation of the course (1 session). Objectives, structure of the contents, teaching materials, the Moodle platform and assessment rules. The farm as a decision unit: firm, household and manager of natural resources. The specificities of the sector (biological lags, risk, land as a fixed factor, family labour and capital) and their implications for management.
2. Foundations and production economics (Module A — 4 sessions). The production function: total, average and marginal product; the stages of production; optimal input use (factor-product relationship, VMP = MFC). Combining two inputs: isoquants and least-cost combination (factor-factor). Combining enterprises: the production possibility frontier (product-product), returns to scale, and cost concepts (fixed/variable, short and long run, economies of scale and scope). Farm accounting and data: balance sheet, income statement, the FADN/RICA system and key indicators (FNVA, FNI, gross margin, AWU/FWU).
3. Planning and farm decision-making (Module B — 7 sessions). Measuring farm performance: profitability, technical and allocative efficiency, productivity (partial and total factor), benchmarking. Budgeting: gross margins, enterprise budgets, partial budgeting for marginal decisions, whole-farm and cash-flow budgeting, break-even analysis. Linear programming: formulation, constraints, objective function, shadow prices and sensitivity analysis applied to the farm-planning problem (with Excel Solver). Risk and uncertainty: sources of risk, representation through probability distributions, expected value and variance, risk aversion and expected utility, decision trees. Risk management and agricultural insurance: diversification, contracts, hedging, insurance markets (moral hazard, adverse selection, index insurance).
4. Investment analysis (Module C — 8 sessions). The time value of money: discounting and compounding, present and future value, annuities; why farm investments are difficult (lumpiness, irreversibility, long life). Appraisal criteria: net present value (NPV), internal rate of return (IRR), benefit-cost ratio, payback period; mutually exclusive projects, capital rationing, equivalent annual annuity, replacement decisions. Financing the investment: debt and equity, cost of capital, leverage, loan amortisation, liquidity and solvency ratios. Risk in investment appraisal: sensitivity analysis, scenarios, switching values, Monte Carlo simulation (in Excel) and an introduction to real options. Cost-benefit analysis: private and social appraisal, externalities, valuation of environmental costs and benefits, shadow prices and the social discount rate.
Concluding session. Project presentation and synthesis in preparation for the written test.
Complementary teaching activities. Five sessions are guided computer-lab exercises carried out entirely in Excel: building farm accounts and ratios from an FADN-like dataset (session 5); partial and whole-farm budgeting (session 7); linear programming with Solver, shadow prices and sensitivity (session 9); computing NPV, IRR and payback (session 14); Monte Carlo simulation of NPV using data tables and random functions (session 18). The exercises build the examination project cumulatively.

examMode

Assessment consists of two components of equal weight: an individual project and a final written test.
The project is a Microsoft Excel assignment on a single farm, built cumulatively through the computer-lab exercises carried out during the course. Starting from an FADN-like dataset, students progressively build the farm accounts and performance ratios, a partial and whole-farm budget, the appraisal of an investment using net present value and internal rate of return, and the risk analysis of that investment through simulation. The project is assessed on the correctness of the calculations, the consistency of the assumptions, and the ability to interpret the results and to argue the proposed decisions. It counts for 50% of the final mark.
The final written test takes place at the end of the course and covers the whole programme. It consists of closed-answer and open-answer questions: the former assess knowledge of the concepts, definitions and analytical relationships presented in the lectures and in the texts; the latter require students to apply those concepts to a concrete situation — for instance, to determine the optimal use of an input, to interpret the shadow prices of a farm plan, to rank risky alternatives on the basis of expected utility, or to appraise an investment and discuss its sensitivity — and to argue their answer. The number of questions and the time available are communicated to students at the beginning of the course and stated on the Moodle page of the course. The written test counts for 50% of the final mark.
This structure follows from the nature of the expected learning outcomes: the written test assesses knowledge and understanding and, in the open questions, the ability to apply that knowledge; the project assesses the ability to apply knowledge and understanding to a real case autonomously, the appropriate use of quantitative tools, and communication skills in presenting the results.
The final mark, expressed out of thirty, is the average of the two components, each counting for 50%. The examination is passed with a mark of at least 18/30, and a pass is required in both components. Distinction (lode) is awarded to students who, having obtained the maximum score, demonstrate a particular command of the analytical tools and the ability to connect the contents of the different modules autonomously.
The written test is held in English and the project is written in English.

books

The course does not adopt a single textbook. For each module the relevant chapters and pages are indicated; teaching material, slides, lab datasets and links are made available on the Moodle platform of the course.
Foundations and production economics (Module A)
• Barkley, A. (2019), The Economics of Food and Agricultural Markets, 2nd ed., New Prairie Press — to review the foundations of production and cost economics. Open access (CC BY-NC): https://kstatelibraries.pressbooks.pub/economicsoffoodandag/
• Kay, R. D., Edwards, W. M., Duffy, P. A., Farm Management, McGraw-Hill — chapters on production economics, farm accounting and financial statement analysis (current edition).
Planning and farm decision-making (Module B)
• Kay, R. D., Edwards, W. M., Duffy, P. A., Farm Management, McGraw-Hill — chapters on gross margins, partial and whole-farm budgeting, linear programming.
• OECD (2009), Managing Risk in Agriculture: A Holistic Approach, OECD Publishing — Ch. 2 (risk concepts and management instruments). https://doi.org/10.1787/9789264075313-en
• Bertolozzi-Caredio, D., Severini, S., Pierre, G., Zinnanti, C., Rustom, R., Santoni, E., Bubbico, A. (2023), Risks and vulnerabilities in the EU food supply chain, Publications Office of the European Union, Luxembourg — Ch. 3 (EU empirical evidence on risk). doi:10.2760/171825. https://publications.jrc.ec.europa.eu/repository/handle/JRC135290
Investment analysis (Module C)
• Kay, R. D., Edwards, W. M., Duffy, P. A., Farm Management, McGraw-Hill — chapters on the time value of money, investment appraisal criteria and financing.
• OECD (2020), "Global value chains in agriculture and food: A synthesis of OECD analysis", OECD Food, Agriculture and Fisheries Papers, No. 139 — for context on the position of the farm in the value chain. http://dx.doi.org/10.1787/6e3993fa-en
Supplementary teaching material
• Lecture slides, Excel lab datasets and links to multimedia content are available on the Moodle platform of the course.

classRoomMode

Attendance is not formally compulsory, but it is strongly recommended.
The computer-lab exercises and the classroom discussion of their results are an integral part of the teaching and cannot be entirely replaced by individual study of the material available on Moodle: the examination project, which counts for half of the assessment, is built cumulatively precisely during the lab sessions. Regular participation is therefore the most effective way to achieve the expected learning outcomes and to prepare adequately for both components of the assessment.
Slides, datasets and lab materials are nonetheless made available on the Moodle platform of the course, so that students who are unable to attend regularly can still follow the development of the course and of the project.

bibliography

For a more extensive and formal treatment of farm management, investment appraisal and risk analysis:
• Boehlje, M. D., Eidman, V. R., Farm Management, Wiley — a classic treatment of farm planning and investment analysis.
• Hardaker, J. B., Lien, G., Anderson, J. R., Huirne, R. B. (2015), Coping with Risk in Agriculture: Applied Decision Analysis, 3rd ed., CABI — for decision analysis under risk.
• Barnard, C. S., Nix, J. S., Farm Planning and Control, Cambridge University Press — for budgeting and farm programming.
• Barkley, A. (2019), The Economics of Food and Agricultural Markets, 2nd ed., New Prairie Press — Ch. 1, to review the prerequisites. https://kstatelibraries.pressbooks.pub/economicsoffoodandag/
Further online material: FAO farm-management and investment-analysis resources on the Knowledge portal; OECD databases and publications on agricultural policy and risk management.