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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 2020 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.
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:
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 @Risk. 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 @risk.
|Intended credits||3 ECTS|
|Course organisation||Wageningen School of Social Sciences (WASS)|
|More information||Course website|