Risk Analysis and Risk Management in Agriculture: Updates on Modelling and Applications - 3 ECTS
The farm sector is affected by a large and changing set of risk sources including more volatile producer prices, unusual weather patterns, upstream and downstream market power along the value chain, increasing dependence on financial institutions, and political risks. This induces the need for (new) risk management tools. Also the Common Agricultural Policy is considering risk management as an important component of agricultural policy.
Participants will learn theories concerning risk analysis and risk coping strategies and will develop proficiency with software to facilitate the initiation of their own research in topics related to risk in agriculture. The course deals with both conceptual and methodological issues.
Target group and learning outcomes
The course is oriented toward PhD candidates, postdoctoral researchers and others with background in agricultural and applied economics.
After successful completion of this course students are expected to be able to:
- Understand theories underlying risk measurement and risk management decision making.
- Critically assess econometric analyses with regard to adoption of risk management tools.
- Model whole-farm income and risk management decisions.
- Estimate the impact of weather shocks on agricultural production.
- Reflect on current (EU) policy developments with regard to risk management and resilience.
Assumed prior knowledge:
Before the start of the course students are required to have a basic understanding of statistics (Appendix A, B, and C from Wooldridge, 2015), econometrics (Chapters 1 and 2 from Wooldridge, 2015) and mathematical notation (Appendix D and E from Wooldridge, 2015). Further reading on Limited Dependent Variables Models (Chapter 17 from Wooldridge, 2015) and Panel Data Models (Chapters 13 and 14 from Wooldridge, 2015) is optional but highly suggested. We will work primarily with the software packages Stata and R. In order to get familiar with this software, please have a look at (i) introductory guides 1 ; 2 or more detailed tutorials 1 ; 2 for Stata and (ii) this introduction page for R.
Wooldridge, J. M. (2015). Introductory econometrics: A modern approach. Nelson Education.
The course consists of theory and method sessions, divided in interactive plenary sessions and breakout sessions for the presentation of theoretical aspects, and practical sessions to provide exposure to analytical exercises, simulations, and econometric estimations. Practical sessions will include applications of the theory, computer analyses with actual data sets, and interpretations in practice.
Outline of the course in hours
The course will involve daily sessions in which sessions on theory are alternated with practical sessions. There will be two take-home exams which need to be handed in on Tuesday (Part I) and Thursday (Part II) at 20.00 h. Students can work in groups (maximum 3 students per group).
Reading materials prepared by the authors will be sent to participants in advance of the course. Articles and other accompanying materials will be distributed during the course.
Requirements and ECTS
Before the start of the course, participants submit a sheet with their expectations and background, and a definition of ‘risk’ in their own words (send to firstname.lastname@example.org before 20 June 2022). During the course, participants will hand in two take-home exams. A mark of > 5.5 makes them eligible to obtain the amount of 3 credits (according to ECTS).
|WGS PhDs with TSP||€ 300|
|a) All other PhD candidates b) Postdocs and staff of the above mentioned Graduate Schools||€ 640|
|All others||€ 900|
The course fee includes additional training material, coffee/tea, lunches, a social dinner and informal reception.