Economic Rationality and Competing Behavioral Rules
Final Report Abstract
Economics and Psychology can both be called „Decision Sciences “. Models of decision making in economics lack a proper, systematic psychological foundation, while experimental psychology can greatly benefit from the formal approaches that characterizes modern economics. This individual project, as part of the research unit, developed an integrative and data-driven research plan to understand how interacting motives and strategies determine actual human behavior. The objectives of the research plan included a unification of very different research conventions and methodologies in economics and psychology. For instance, various different methods from psychology (response times, electrophysiological measurements, eye, tracking, use of cognitive load and similar manipulations) have been introduced to economic experiments while at the same time, behavioral models have been expanded to accommodate predictions for this kind of process data in economics. First, theoretical advances have led to multiple publications with new models incorporating response time predictions for economic decisions based on dual-process theories. Second, the predictions borne from the models developed have been readily observed in many experiments throughout the project. This shows that the two disciplines can accommodate a unified approach to understanding decisions. One major result of the models (and experiments) is the idea of multiple behavioral rules and biases might be in conflict or in alignment with respect to their prescriptions. When trying to understand those biases, it is important to make the distinction of these different kind of situations. Third, process data in economics yield valuable information which is greatly underused. It starts from simple response times which are readily available in the majority of experiments and reveals insights about the underlying decision processes as was shown in multiple articles from this project. Tracking the gaze and pupil size yields more complex process data, however, is still applicable to many economic paradigms and has become more popular among some economists recently. This kind of data reveals what kind of information has been seen (and possible processed) by the agent and pupil size can be used as a proxy for arousal or effort, which is usually unobservable by focusing only on choice outcomes. EEG measurements reveal direct links to brain activity and helps to understand the basic underlying processes. All different kind of process data that has been used in the project proved to reveal invaluable in investigating human decision making. One surprising result in the project concerns cognitive load in economic decision making. Cognitive load is a well-established manipulation to causally induce more automatic behavior in typical psychological experiments. However, typical economic experiments, specifically the behavioral rules and strategies usually considered in those experiments, are more complex than paradigms tested in cognitive psychology. A dual-process model, incorporating cognitive load, reveals that strong assumptions need to be satisfied to shift the behavior to more intuitive decisions by implementing cognitive load. The model also provides a simple manipulation check whether or not the cognitive load was successfully implemented, i.e., (counter-intuitively) faster response times under cognitive load which has been presented in a large series of studies (N=628). In summary, the individual project has succeeded in advancing behavioral economics by expanding economic models incorporating process data. The predictions of the theoretical models have been shown empirically in a battery of experiments in various settings.
Publications
- (2014). Fast or Rational? A Response-Times Study of Bayesian Updating. Management Science, 60(4):923–938
Achtziger, A. and Alós-Ferrer, C.
(See online at https://doi.org/10.1287/mnsc.2013.1793) - (2014). From Dual Processes to Multiple Selves: Implications for Economic Behavior. Journal of Economic Psychology, 41:1–11
Alós-Ferrer, C. and Strack, F.
(See online at https://doi.org/10.1016/j.joep.2013.12.005) - (2015). Self-Control Depletion and Decision Making. Journal of Neuroscience, Psychology, and Economics, 8(4):203–216
Alós-Ferrer, C., Hügelschäfer, S., and Li, J.
(See online at https://doi.org/10.1037/npe0000047) - (2016). Cognitive Reflection, Decision Biases, and Response Times. Frontiers in Psychology, 7 (1402):1–21
Alós-Ferrer, C., Garagnani, M., and Hügelschäfer, S.
(See online at https://doi.org/10.3389/fpsyg.2016.01402) - (2016). Inertia and Decision Making. Frontiers in Psychology, 7 (169):1–9
Alós-Ferrer, C., Hügelschäfer, S., and Li, J.
(See online at https://doi.org/10.3389/fpsyg.2016.00169) - (2017). Framing Effects and the Reinforcement Heuristic. Economics Letters, 156:32–35
Alós-Ferrer, C., Hügelschäfer, S., and Li, J.
(See online at https://doi.org/10.1016/j.econlet.2017.03.038) - (2018). A Dual-Process Diffusion Model. Journal of Behavioral Decision Making, 31(2):203–218
Alós-Ferrer, C.
(See online at https://doi.org/10.1002/bdm.1960) - (2018). A Review Essay on Social Neuroscience: Can Research on the Social Brain and Economics Inform Each Other?. Journal of Economic Literature, 56 (1), March 2018, pp. 234-264
Alós-Ferrer, C.
(See online at https://doi.org/10.1257/jel.20171370) - (2018). The Reinforcement Heuristic in Normal Form Games. Journal of Economic Behavior and Organization, 152:224–234
Alós-Ferrer, C. and Ritschel, A.
(See online at https://doi.org/10.1016/j.jebo.2018.06.014)
