Jonas Schmitt: Catalogue data in Autumn Semester 2024 |
| Name | Dr. Jonas Schmitt |
| Address | Agrarökonomie und -politik ETH Zürich, SOL C 10.1 Sonneggstrasse 33 8092 Zürich SWITZERLAND |
| jonas.schmitt@usys.ethz.ch | |
| Department | Environmental Systems Science |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | ||||||||||||||||||||||||||||||||||||||||||||||||||
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| 751-0423-00L | Risk Analysis and Risk Management in Agriculture | 3 credits | 2G | R. Finger, J. Schmitt | ||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Agricultural production is exposed to various risks and risk management is indispensable. This course introduces modern concepts on farmers' decision making under risk and risk management. We present innovative insights, emprical example from European agriculture. You gain hands-on experience using R. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | -to develop a better understanding of decision making under uncertainty and risk; - gain hands-on experience in risk analysis and management using R -to gain experience in different approaches to analyze risky decisions; -to develop an understanding for different sources of risk in agricultural production; -to understand the crucial role of subjective perceptions and preferences for risk management decisions; -to get an overview on risk management in the agricultural sector, with a particular focus on insurance solutions -to get insights in the role of big data and machine learning for agricultural risk management | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | - Quantification and measurement of risk - Risk preferences, Expected Utility Theory, Cumulative Prospect Theory - Production and input use decisions under risk - Portfolio Theory and Farm Diversification - Forwards, Futures, Crop Insurance - Weather Index Insurance and Satellite Imagery - Big data and machine learning for agricultural risk management - Empirical Applications using R | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Handouts will be distributed in the lecture and available on the moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | knowledge of basic concepts of probability theory and microeconomics | |||||||||||||||||||||||||||||||||||||||||||||||||||||
Competencies |
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| 751-1010-00L | Introduction to Scientific Methods Part II: Scientific Writing  | 3 credits | 4G | R. Kölliker, J. Anderegg, A. K. Gilgen, B. Keller, M. Laub, A. Oberson Dräyer, J. Schmitt, B. Studer, F. Tamburini | ||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Die Studierenden kennen die Grundlagen und die Konventionen des wissenschaftlichen Schreibens in den Naturwissenschaften, können wissenschaftliche Literatur suchen und verwalten sowie wissenschaftliche Publikationen analysieren. Sie setzen das Gelernte beim Schreiben eines eigenen Textes um. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Die Studierenden kennen die Grundlagen und die Konventionen des wissenschaftlichen Schreibens in den Naturwissenschaften. Sie setzen das Gelernte beim Schreiben eines kritischen Literaturberichtes zu einem agrarwissenschaftlichen Thema ihrer Wahl um. Die Lehrveranstaltung bereitet die Studierenden auf weitere schriftliche Arbeiten im Studium der Agrarwissenschaften vor, beispielsweise auf die Bachelor-Arbeit. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Es wird ein Skript abgegeben. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Die Note für die LV Wissenschaftliches Arbeiten (Teil I: Grundlagen (WiA) und Teil II: Wissenschaftliches Schreiben (WiSch)) setzt sich aus den Leistungen der Lehrveranstaltungen im 4. und 5. Semester zusammen. Die Note für WiSch (5. Sem.) zählt zu 80% zur Gesamtnote. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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