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040122 SE Topics in Behavioral and Experimental Economics (MA) (2025W)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 08.09.2025 09:00 to We 17.09.2025 12:00
- Registration is open from We 24.09.2025 09:00 to Th 25.09.2025 12:00
- Deregistration possible until Tu 14.10.2025 23:59
Details
max. 18 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 07.10. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 14.10. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 21.10. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 28.10. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 04.11. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 11.11. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 18.11. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 25.11. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 02.12. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 09.12. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 16.12. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 13.01. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 20.01. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 27.01. 16:45 - 18:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Information
Aims, contents and method of the course
The purpose of the seminar is to critically discuss recent developments in Behavioral and Experimental Economics in a small group of advanced students. The course educates students to become critical consumers of current research in behavioral and experimental economics and aims at inspiring students for their own research projects.
Assessment and permitted materials
Method: In the first session, I briefly present the topics and the papers. Each student selects one paper on which s/he is “in charge”, and 3 papers on which s/he submits questions in writing. The discussion in class is organized as follows: The person “in charge” briefly presents the paper (max. 10’). Students who handed in comments / questions briefly explain their contribution as an input to the discussion. The person in charge should be able to summarize each section/paragraph of the paper in his or her own words at any time during the discussion.
All participants are expected to participate in the discussion and contribute their own thoughts and views on the papers.
All participants are expected to participate in the discussion and contribute their own thoughts and views on the papers.
Minimum requirements and assessment criteria
Requirements: Participants are expected to have taken classes providing an introduction into the field, for example “Principles of Behavioral and Experimental Economics” (BA, UK 040110) and ideally also “Behavioral and Experimental Economics” (MA, 040832). Foreign students with similar background are very welcome. In addition, a sound knowledge of microeconomics and game theory is required.
Participation in the first class is compulsory. You cannot participate in this course if you do not attend the first session (7.10.)Grading:
a) Grading for the person "in charge" has two components. 1) Presentation of the paper (20%). Hand in your slides 24h before your seminar presentation through Moodle. 2) Performance in structuring the discussion, in navigating the group through the paper and in answering questions of fellow students (and the instructor) (20% of final grade).
b) Students are requested to read all papers and to actively participate in discussion (20%). As grading is based on active participation in the course, you must not miss more than two sessions.
c) Hand in questions and comments to at least 3 papers (max. 2 questions per paper). Comments should be critical and may, for example, relate to the experimental design, the validity of the analysis, or the interpretation of results. Provide a short explanation for why your question may be relevant or interesting (max. 1 page per question). Best 2 attempts count. Hand in your comments and questions 24h before the seminar through Moodle (40%).
Participation in the first class is compulsory. You cannot participate in this course if you do not attend the first session (7.10.)Grading:
a) Grading for the person "in charge" has two components. 1) Presentation of the paper (20%). Hand in your slides 24h before your seminar presentation through Moodle. 2) Performance in structuring the discussion, in navigating the group through the paper and in answering questions of fellow students (and the instructor) (20% of final grade).
b) Students are requested to read all papers and to actively participate in discussion (20%). As grading is based on active participation in the course, you must not miss more than two sessions.
c) Hand in questions and comments to at least 3 papers (max. 2 questions per paper). Comments should be critical and may, for example, relate to the experimental design, the validity of the analysis, or the interpretation of results. Provide a short explanation for why your question may be relevant or interesting (max. 1 page per question). Best 2 attempts count. Hand in your comments and questions 24h before the seminar through Moodle (40%).
Examination topics
no exam
Reading list
Generative AI and Deep learning as complements to experimental methods
1. Chopra, F. and Haaland, I. (2024): Conducting Qualitative Interviews with AI. Working paper.
2. Dell, M. (2025): Deep Learning for Economists. Journal of Economic Literature 63 (1): 5-58.
3. Korinek, A. (2024): LLMs Learn to Collaborate and Reason: December 2024 Update to “Generative AI for Economic Research: Use Cases and Implications for Economists,” published in the Journal of Economic Literature 61 (4): 1281-1317.
Effectiveness of Nudging
The articles in this section relate to each other and should be presented together in one session.
4. Mertens, S., Herberz, M., Hahnel, U.J., and Brosch, T. (2022): The Effectiveness of Nudging: A Meta-analysis of Choice Architecture Interventions across Behavioral Domains. Proceedings of the National Academy of Science PNAS 119(1): e2107346118. (correction in: PNAS 2022, 119(19) e2204059119)
5. Szaszi et al. (2022): No Reason to Expect Large and Consistent Effects of Nudge Interventions. PNAS 119(3): e2200732119
6. Maier, M. et al. (2022): No Evidence for Nudging after Adjusting for Publication Bias. PNAS 119(31): e2200300119.Loss aversion
7. Fryer, R.G., Levitt, S.D., List, J. and Sadoff, S. (2022): Enhancing the Efficacy of Teacher Incentives through Loss Aversion: A Field Experiment. American Economic Journal: Policy 14(4): 269-99.
8. Iqbal, K., Islam, A., List, J.A. and Nguyen, V. (2021): Myopic Loss Aversion and Investment Decisions: From the Laboratory to the Field. NBER WP 28730.
9. Larson, F., List, J., Metcalfe, R. (2016): Can Myopic Loss Aversion Explain the Equity Premium Puzzle? Evidence from a Natural Field Experiment with Professional Traders. NBER Working Paper No. 22605. Reject and Resubmit, Econometrica.Experimental Approaches to Vote Buying
10. Apffelstaedt, A. and Freundt, J. (2024): Corrupted Votes and Rule Compliance. American Economic Journal: Microeconomics 16(4): 440-474.
11. Blattman, C., Larreguy, H., Marx, B. and Reid, O. (2024): Eat Widely, Vote Wisely? Lessons from a Campaign Against Vote Buying in Uganda.
12. Schechter, L. and Vasudevan, S. (2023): Persuading voters to Punish Corrupt Vote-buying Candidates: Experimental Evidence from a Large-scale Radio Campaign in India. Journal of Development Economics 160: 102976.Discrimination
13. Angerer, S., Brosch, H., Glätzle-Rützler, D., Lergetporer, P. and Rittmannsberger, T. (2024): Discrimination in the General Population. IZA DP No. 16984
14. Barron, K., Ditlmann, R., Gehrig, S. and Schweighofer-Kodritsch, S. (2024): Explicit and Implicit Belief-Based Gender Discrimination: A Hiring Experiment. WP Berlin School of Economics #35
15. Eyting, M. (2025): Why Do We Discriminate? The Role of Motivated Reasoning. WP Feb 2025
16. Gagnon, N., Bosmans, K. and Rield, A. (2025): The Effect of Gender Discrimination on Labor Supply. Journal of Political Economy 133(3): 1047–1081Moral behavior, Social Preferences
17. Cappelen, A.W., Enke, B. and Tungodden, B. (2025): Universalism: Global Evidence. American Economic Review 115(1): 43-76.
18. Fehr, E. and Charness, G. (2025): Social Preferences: Fundamental Characteristics and Economic Consequences. Journal of Economic Literature 63(2): 440-514.
19. Huber, C. et al. (93 authors in total), (2023): Competition and Moral Behavior: A Meta-Analysis of forty-five Crowd-sourced Experimental Designs. Proceedings of the National Academy of Science PNAS 120 (23) e2215572120.Methodological and measurement issues
20. Oprea, R. (2024): Complexity and its Measurement. Working paper
21. Janas, M., Lozano, L., Nikiforakis, N., Reuben, E., and Stüber, R. (2025): Bringing it All Back Home: Incentives in the Age of General Population Sampling. Working paper NYUAD, Feb. 2025
22. Enke, B., Gneezy, U., Hall, B., Martin, D., Nelidov, V., Offerman, T. and van de Ven, J. (2023): Cognitive Biases: Mistakes or Missing Stakes? Review of Economics and Statistics 105(4): 818-32.
1. Chopra, F. and Haaland, I. (2024): Conducting Qualitative Interviews with AI. Working paper.
2. Dell, M. (2025): Deep Learning for Economists. Journal of Economic Literature 63 (1): 5-58.
3. Korinek, A. (2024): LLMs Learn to Collaborate and Reason: December 2024 Update to “Generative AI for Economic Research: Use Cases and Implications for Economists,” published in the Journal of Economic Literature 61 (4): 1281-1317.
Effectiveness of Nudging
The articles in this section relate to each other and should be presented together in one session.
4. Mertens, S., Herberz, M., Hahnel, U.J., and Brosch, T. (2022): The Effectiveness of Nudging: A Meta-analysis of Choice Architecture Interventions across Behavioral Domains. Proceedings of the National Academy of Science PNAS 119(1): e2107346118. (correction in: PNAS 2022, 119(19) e2204059119)
5. Szaszi et al. (2022): No Reason to Expect Large and Consistent Effects of Nudge Interventions. PNAS 119(3): e2200732119
6. Maier, M. et al. (2022): No Evidence for Nudging after Adjusting for Publication Bias. PNAS 119(31): e2200300119.Loss aversion
7. Fryer, R.G., Levitt, S.D., List, J. and Sadoff, S. (2022): Enhancing the Efficacy of Teacher Incentives through Loss Aversion: A Field Experiment. American Economic Journal: Policy 14(4): 269-99.
8. Iqbal, K., Islam, A., List, J.A. and Nguyen, V. (2021): Myopic Loss Aversion and Investment Decisions: From the Laboratory to the Field. NBER WP 28730.
9. Larson, F., List, J., Metcalfe, R. (2016): Can Myopic Loss Aversion Explain the Equity Premium Puzzle? Evidence from a Natural Field Experiment with Professional Traders. NBER Working Paper No. 22605. Reject and Resubmit, Econometrica.Experimental Approaches to Vote Buying
10. Apffelstaedt, A. and Freundt, J. (2024): Corrupted Votes and Rule Compliance. American Economic Journal: Microeconomics 16(4): 440-474.
11. Blattman, C., Larreguy, H., Marx, B. and Reid, O. (2024): Eat Widely, Vote Wisely? Lessons from a Campaign Against Vote Buying in Uganda.
12. Schechter, L. and Vasudevan, S. (2023): Persuading voters to Punish Corrupt Vote-buying Candidates: Experimental Evidence from a Large-scale Radio Campaign in India. Journal of Development Economics 160: 102976.Discrimination
13. Angerer, S., Brosch, H., Glätzle-Rützler, D., Lergetporer, P. and Rittmannsberger, T. (2024): Discrimination in the General Population. IZA DP No. 16984
14. Barron, K., Ditlmann, R., Gehrig, S. and Schweighofer-Kodritsch, S. (2024): Explicit and Implicit Belief-Based Gender Discrimination: A Hiring Experiment. WP Berlin School of Economics #35
15. Eyting, M. (2025): Why Do We Discriminate? The Role of Motivated Reasoning. WP Feb 2025
16. Gagnon, N., Bosmans, K. and Rield, A. (2025): The Effect of Gender Discrimination on Labor Supply. Journal of Political Economy 133(3): 1047–1081Moral behavior, Social Preferences
17. Cappelen, A.W., Enke, B. and Tungodden, B. (2025): Universalism: Global Evidence. American Economic Review 115(1): 43-76.
18. Fehr, E. and Charness, G. (2025): Social Preferences: Fundamental Characteristics and Economic Consequences. Journal of Economic Literature 63(2): 440-514.
19. Huber, C. et al. (93 authors in total), (2023): Competition and Moral Behavior: A Meta-Analysis of forty-five Crowd-sourced Experimental Designs. Proceedings of the National Academy of Science PNAS 120 (23) e2215572120.Methodological and measurement issues
20. Oprea, R. (2024): Complexity and its Measurement. Working paper
21. Janas, M., Lozano, L., Nikiforakis, N., Reuben, E., and Stüber, R. (2025): Bringing it All Back Home: Incentives in the Age of General Population Sampling. Working paper NYUAD, Feb. 2025
22. Enke, B., Gneezy, U., Hall, B., Martin, D., Nelidov, V., Offerman, T. and van de Ven, J. (2023): Cognitive Biases: Mistakes or Missing Stakes? Review of Economics and Statistics 105(4): 818-32.
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Last modified: Th 05.03.2026 13:46