Hélène Schernberg: Catalogue data in Autumn Semester 2023 |
| Name | Dr. Hélène Schernberg |
| Address | Lehre Management, Technol. u. Ök. ETH Zürich, SEC D 8 Scheuchzerstrasse 7 8092 Zürich SWITZERLAND |
| Telephone | +41 44 632 82 49 |
| hschernberg@ethz.ch | |
| URL | https://sites.google.com/view/helene-schernberg/home |
| Department | Management, Technology, and Economics |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 363-1017-00L | Risk and Insurance Economics | 3 credits | 2G | H. Schernberg | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The course covers the economics of risk and insurance, in particular the following topics will be discussed: 2) individual decision making under risk 3) models of insurance demand, risk sharing, insurance supply 4) information issues in insurance markets 5) advanced topics in microeconomics and behavioral economics 5) the macroeconomic role of insurers and insurance regulation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The course introduces students to basic microeconomic models of risk attitudes and highlight the role insurance can – or cannot – play for individuals facing risks. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Everyday, we take decisions involving risks. These decisions are driven by our perception of and our appetite for risk. Insurance plays a significant role in people's risk-management strategies. In the first part of this lecture, we discuss a normative decision concept, Expected Utility theory, and compare it with empirically observed behaviour. Students then learn about the rationale for individuals to purchase insurance, and for companies to offer it. We derive the optimal level of insurance demand and discuss how it depends on our model's underlying assumptions. We then discuss the consequences of information asymmetries in insurance markets and the consequences for insurance supply. Finally, we discuss refinements in decision theory that help account for observed behaviours that don't fit with the basic models of microeconomic theory. For example, we'll explore how behavioural economics can be leveraged by the insurance industry. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Main literature: - Zweifel, P., & Eisen, R. (2012). Insurance Economics. Springer. - Handbook of the Economics of Risk and Uncertainty, Volume1; Further readings: - Dionne, G. (Ed.). (2013). Handbook of Insurance (2nd ed.). Springer. References will be given on a topic-by-topic basis during the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competencies |
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| 363-1162-00L | Resilience in the New Age of Risk | 3 credits | 2V | H. Schernberg, C. Hölscher, J. Jörin, G. Sansavini | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | With the global increase in interconnectivity, the potential for disruption is everywhere. Modern organisations who build resilience in all systems will respond intelligently to emergent disruptions. This course explores the concept of resilience and its application to socio-technical systems: The resilience of infrastructure systems and how individuals and social groups interact in and with them. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | After taking this course, you will be able to: - Discuss the concept of resilience and related frameworks and concepts, and explain their relevance in different contexts (organizations, infrastructure, social groups…). - Use and discuss key resilience metrics and use them to analyze infrastructure systems. - Discuss the role of organizational resilience and describe methods to improve it. - Describe how resilience is applied in practice. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Our increasingly complex and connected systems face continuously emerging disruptions. Resilience constitutes a fundamental departure from the philosophy of risk-management. With resilience, stakeholders adopt risk mitigation strategies aligned to the theories of complex systems. It is, however, difficult to learn about resilience, since it applies to an extremely large array of systems and contexts. Moreover, the topic of resilience is surprisingly absent from most university curricula. This course fills a gap and walks you through a mode of thinking that is bound to shape the way risks and disasters are dealt with in our increasingly connected society. Hence, tomorrow's risk managers will and shall also be "resilience managers". This course breaks down the concept of complex systems and their resilience. It introduces some of the different flavors of resilience and provides tools for building it in various socially relevant areas (social resilience, engineered systems resilience, organizational resilience...). The course is divided in 4 parts. - Part 1: Foundations of Resilience (2 hours) - Part 2: Resilience Analysis: Infrastructure Systems (12 hours) - Part 3: Organizational resilience and sensemaking (6 hours) - Part 4: Resilience in Practice (4 hours) Part 1 introduces the concept of resilience, and the framework in which it is applied. The distinction between resilience and risk management is highlighted, as well as how these approaches complement each other. The founding concepts of resilience are explained and illustrated: vulnerability, disruption, absorption, recovery, adaptation, etc. Part 2 walks you through the analysis of the resilience of infrastructure systems. It introduces the useful metrics of resilience. It provides examples of building resilience into complex systems, by increasing the robustness and recoverability of systems, and reducing vulnerabilities. Finally, students will explore the optimization of infrastructure systems. Part 3. Every system subject to potential disruptions is managed by a human organization. Sensemaking describes how humans frame the problem. It is a process whereby organizational actors attach meaning to external events to resolve the uncertainty surrounding them. Investing in mindfulness improves personal and organizational resilience and success. Finally, the management of organizational resilience is discussed. Part 4 will provide examples of the use of resilience by practitioners, with guest speakers from the public and private sector. This course is aimed at MSc and MAS students, from MTEC and other departments. Ideally, students have a quantitative background and some knowledge of risk management. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | The Science and Practice of Resilience, Book by Benjamin D. Trump and Igor Linkov | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This course is in-person and will be recorded. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 364-1058-00L | Risk Center Seminar Series | 0 credits | 2S | H. Schernberg, D. Basin, A. Bommier, D. N. Bresch, S. Brusoni, L.‑E. Cederman, P. Cheridito, F. Corman, H. Gersbach, C. Hölscher, K. Paterson, G. Sansavini, B. Stojadinovic, B. Sudret, J. Teichmann, R. Wattenhofer, S. Wiemer, R. Zenklusen | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course is a mixture between a seminar primarily for PhD and postdoc students and a colloquium involving invited speakers. It consists of presentations and subsequent discussions in the area of modeling complex socio-economic systems and crises. Students and other guests are welcome. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Participants should learn to get an overview of the state of the art in the field, to present it in a well understandable way to an interdisciplinary scientific audience, to develop novel mathematical models for open problems, to analyze them with computers, and to defend their results in response to critical questions. In essence, participants should improve their scientific skills and learn to work scientifically on an internationally competitive level. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | This course is a mixture between a seminar primarily for PhD and postdoc students and a colloquium involving invited speakers. It consists of presentations and subsequent discussions in the area of modeling complex socio-economic systems and crises. For details of the program see the webpage of the colloquium. Students and other guests are welcome. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | There is no script, but a short protocol of the sessions will be sent to all participants who have participated in a particular session. Transparencies of the presentations may be put on the course webpage. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Literature will be provided by the speakers in their respective presentations. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Participants should have relatively good mathematical skills and some experience of how scientific work is performed. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||