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2024/2025 KAN-CPSYO2001U Behavioral Economics II
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| Behavioral Economics II |
Course information |
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| Language | English |
| Course ECTS | 7.5 ECTS |
| Type | Mandatory |
| Level | Full Degree Master |
| Duration | One Semester |
| Start time of the course | Autumn |
| Timetable | Course schedule will be posted at calendar.cbs.dk |
| Study board |
Study Board for BSc/MSc in Business Administration and
Psychology, MSc
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| Last updated on 24-06-2024 | |
Relevant links |
| Learning objectives | ||||||||||||||||||||||
The overall purpose of the course is to provide
students with insights on and understanding of key elements in
behavioral economics, including how psychology is explicitly
involved in economic and business-economic models to establish more
robust explanations, predictions, and tools. At the end of the
course, students should be able to:
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The course aims to provide students with a broad insight into the many areas where psychology is explicitly involved in economic theory. The course is primarily based on behavioral economics research, which in the wake of the collaboration between Daniel Kahneman and Amos Tversky has taken an increasingly central position in economic theory and practice. Behavioral economics research covers, among other things, decision rationality and heuristics, prospect theory, intertemporal choices, dual process theory, etc. The course will introduce these areas and review how behavioral economics theory has been and can be applied in a number of key areas such as business, organization, sustainability, user experience and policy. Further applications of the behavioral and experimental toolkit to social issues will be presented.
The first block of lectures will introduce the field of behavioral economics and will examine its roots in applied economics, rationality, and behavioral theory. The second block will focus more on practical issues within the curriculum of behavioral economics. The purpose there is to provide space for analyzing behavioral methods and approaches to tackle social and business issues, to explore the material from various angles and to challenge key hypotheses based on the syllabus.
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| Description of the teaching methods | ||||||||||||||||||||||
| The course consists of 12 on campus lectures with 1-2 lectures delivered per week. The first block of lectures will introduce the field of behavioral economics and will examine its roots in applied economics, rationality, and behavioral theory. The second block will focus more on practical issues within the curriculum of behavioral economics. The purpose there is to provide space for analysing behavioral methods and approaches to tackle social and business issues, to explore the material from diverse angles and to challenge key hypotheses based on the syllabus. A variety of methods will be used, covering group discussions, mini-cases and group class exercises to traditional scientific paper analyses. | ||||||||||||||||||||||
| Feedback during the teaching period | ||||||||||||||||||||||
| The course will provide space for feedback and
dialogue throughout, ie. for discussions in plenary for lectures or
for personal inquiries during breaks, after the end of the lecture,
or for inquiries per mail. In addition, the course includes both
exercises and active student participation in several lectures,
where there will be ample opportunity to ask questions, discuss
relevant topics, etc.
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Contact information and details
For any issue/question about a specific lecture you can reach out to the class lecturer. For any other inquiry do reach out to the course coordinator.
Lecturer Alice Pizzo: api.msc@cbs.dk Lecturer Jan M. Bauer: jmb.msc@cbs.dk Course coordinator Efthymios Altsitsiadis: ea.msc@cbs.dk |
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| Expected literature | ||||||||||||||||||||||
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Lecture 1: Introduction to Behavioral Economics
Becker, GS (1993). The Economic Way of Looking at Behavior. Journal of Political Economy: 385-409.
Chapter I - Book: Charles A. Holt, Markets, Games, & Strategic Behavior. Pearson Higher Education, 2007.
Lecture 2: Decision making in Behavioral Economics
Kahneman, D., & Frederick, S. (2005). A model of heuristic judgment. Cambridge University Press.
Kahneman, D. (2003). Maps of bounded rationality: Psychology for behavioral economics. American economic review, 93(5), 1449-1475.
LeBoeuf, RA, & Shafir, EB (2005). Decision Making. Cambridge University Press.
Harrison, GW, & List, JA (2004). Field experiments. Journal of economic literature, 42(4), 1009-1055.
Lecture 3: Nudging in Choice Architecture
Sunstein, CR, & Thaler, RH (2003). Libertarian paternalism is not an oxymoron. The University of Chicago Law Review, 1159-1202.
Sunstein, C. (2017). Nudges that fail. Behavioral Public Policy, 1(1), 4-25.
Carlsson, F., Gravert, C., Johansson-Stenman, O., & Kurz, V. (2021). The use of green nudges as an environmental policy instrument. Review of Environmental Economics and Policy, 15(2), 216-237.
Lecture 4: Behavioral Economics Applications & Environmental Sciences
Carlsson, F., & Johansson-Stenman, O. (2012). Behavioral economics and environmental policy. Annu. Rev. Resour. Econ., 4(1), 75-99.
Alpizar, F., Carlsson, F., & Johansson-Stenman, O. (2008). Anonymity, reciprocity, and conformity: Evidence from voluntary contributions to a national park in Costa Rica. Journal of Public Economics, 92(5-6), 1047-1060.
Schubert, C. (2017). Green nudges: Do they work? Are they ethical? Ecological economics, 132, 329-342.
Lecture 5: Critical reflections and alternative perspectives
Berg, N., & Gigerenzer, G. (2010). AS-IF BEHAVIORAL ECONOMICS: NEOCLASSICAL ECONOMICS IN DISGUISE? History of Economic Ideas, 18(1), 133–165. http://www.jstor.org/stable/23723790
Lecture 6: Behavioral welfare economics
Sunstein, C. (2020). Behavioral Welfare Economics. Journal of Benefit-Cost Analysis, 11(2), 196-220. doi:10.1017/bca.2020.14
Lecture 7: Digital Behavioral Economics and UX design
Caraban, A., Karapanos, E., Gonçalves, D., & Campos, P. (2019). 23 Ways to Nudge: A Review of Technology-Mediated Nudging in Human-Computer Interaction. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1–15. https://doi.org/10.1145/3290605.3300733
Gray, CM, Kou, Y., Battles, B., Hoggatt, J., & Toombs, AL (2018). The Dark (Patterns) Side of UX Design. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 1–14. https://doi.org/10.1145/3173574.3174108
Lecture 8: Behavioral Economics in the metaverse era
Rahwan, I., et al (2019). Machine behavior. Nature, 568 (7753), 477 486 .
Yee, N., & Bailenson, J. (2007). The Proteus Effect: The Effect of Transformed Self-Representation on Behavior. Human Communication Research, 33(3), 271–290. https://doi.org/10.1111/j.1468-2958.2007.00299.x
Lecture 9: Behavioral economic policy and implications
Cass R. Sunstein (2016), "Fifty Shades of Manipulation", Journal of Marketing Behavior: Vol. 1: No. 3-4, pp 213-244. http://dx.doi.org/10.1561/107.00000014
Bhanot, SP, & Linos, E. (2020). Behavioral Public Administration: Past, Present, and Future. Public Administration Review, 80(1), 168–171. https://doi.org/10.1111/puar.13129
AL-UBAYDLI, O., LEE, M., LIST, J., MACKEVICIUS, C., & SUSKIND, D. (2021). How can experiments play a greater role in public policy? Twelve proposals from an economic model of scaling. Behavioral Public Policy, 5(1), 2-49. doi:10.1017/bpp.2020.17
DellaVigna, S., & Linos, E. (2020). RCTs to Scale: Comprehensive Evidence from Two Nudge Units (Working Paper No. 27594; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27594 |
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