Complexity
The TI-Complexity research field focuses on the analysis and empirical validation of behavioral micro, macro and finance models under “bounded” rationality, where agents are not fully rational, but behave in accordance with experimental and empirical evidence. A central question is: which emerging aggregate macro behavior arises through the interactions of individual micro decisions of boundedly rational heterogeneous agents? Focus topics are: Complex systems & nonlinear dynamics; Bounded rationality, learning & heterogeneous expectations; Behavioral & experimental macro-finance; Complex networks; Dynamic games in complex systems; Strategic interaction and (non-)cooperative games.
Complexity
The TI-Complexity research field focuses on the analysis and empirical validation of behavioral micro, macro and finance models under “bounded” rationality, where agents are not fully rational, but behave in accordance with experimental and empirical evidence. A central question is: which emerging aggregate macro behavior arises through the interactions of individual micro decisions of boundedly rational heterogeneous agents? Focus topics are: Complex systems & nonlinear dynamics; Bounded rationality, learning & heterogeneous expectations; Behavioral & experimental macro-finance; Complex networks; Dynamic games in complex systems; Strategic interaction and (non-)cooperative games.
Researchers in this field
Fellows
Fellows
PhD Students
PhD Students
Key Publications
Kopányi-Peuker, A., Offerman, T., and Sloof, R. (2018). Team production benefits from a permanent fear of exclusion. European Economic Review, 103:125-149. With supplementary materials (research data).
Cornea-Madeira, A., Hommes, C., and Massaro, D. (2017). Behavioral heterogeneity in U.S. inflation dynamics. Journal of Business & Economic Statistics. With supplemental material.
Bao, T., Hommes, C., and Makarewicz, T. (2017). Bubble formation and (in)efficient markets in learning-to-forecast and optimise experiments. Economic Journal, 127(605):F581-F609. With supplementary file - In feature issue.
Diks, C. and Wolski, M. (2016). Nonlinear granger causality: Guidelines for multivariate analysis. Journal of Applied Econometrics, 31(7):1333-1351. With supporting information.
Wagener, F. (2014). Expectations in experiments. Annual Review of Economics, 6:421-443.
Discussion Papers
19-028/II - The effect of futures markets on the stability of commodity prices
Date: April 12, 2019
19-026/II - The Degree Ratio Ranking Method for Directed Networks
Date: April 06, 2019
19-022/II - The alpha-constant-sum games
Date: March 15, 2019
19-016/II - Bubbles, crashes and information contagion in large-group asset market experiments
Date: February 20, 2019
18-092/II - Experience Does not Eliminate Bubbles: Experimental Evidence
Date: November 20, 2018
Upcoming events
PhD Defense
| 10:00 - 11:30
Expectations and Bubbles in Asset Market Experiments
Myrna Hennequin (University of Amsterdam)
- PhD Defense
Seminar
| 16:00 - 17:15
Title to be announced
Ilse Lindenlaub (Yale University, United States)
- Complexity-Macro Seminars
Seminar
| 16:00 - 17:15
Title to be announced
Paola Giuliano (UCLA, United States)
- TI Complexity in Economics Seminars
Seminar
| 16:00 - 17:15
Title to be announced
Luba Petersen (Simon Fraser University, Canada)
- TI Complexity in Economics Seminars
Seminar
| 16:00 - 17:15
Title to be announced
Robert MacKay (Warwick, The United Kingdom)
- TI Complexity in Economics Seminars