Filtern
Erscheinungsjahr
- 2014 (1)
- (1)
Sprache
- Englisch (2) (entfernen)
Volltext vorhanden
- ja (2) (entfernen)
Schlagworte
- Unsicherheit (2) (entfernen)
Institut
- Fachbereich 4 (1)
- Psychologie (1)
The distractor-response binding effect (Frings & Rothermund, 2011; Frings, Rothermund, & Wentura, 2007; Rothermund, Wentura, & De Houwer, 2005) is based on the idea that irrelevant information will be integrated with the response to the relevant stimuli in an episodic memory trace. The immediate re-encounter of any aspect of this saved episode " be it relevant or irrelevant " can lead to retrieval of the whole episode. As a consequence, the previously executed and now retrieved response may influencing the response to the current relevant stimulus. That is, the current response may either be facilitated or be impaired by the retrieved response, depending on whether it is compatible or incompatible to the currently demanded response. Previous research on this kind of episodic retrieval focused on the influence on action control. I examined if distractor response binding also plays a role in decision making in addition to action control. To this end I adapted the distractor-to-distractor priming paradigm (Frings et al., 2007) and conducted nine experiments in which participants had to decide as fast as possible which disease a fictional patient suffered from. To infer the correct diagnosis, two cues were presented; one did not give any hint for a disease (the irrelevant cue), whereas the other did (the relevant cue). Experiments 1a to 1c showed that the distractor-response binding effect is present in deterministic decision situations. Further, experiments 2a and 2b indicate that distractor-response binding also influences decisions under uncertainty. Finally, experiments 3a to 3d were conducted to test some constraints and underlying mechanisms of the distractor-response binding effect in decision making under uncertainty. In sum, these nine experiments provide strong evidence that distractor-response binding influences decision making.
In the modeling context, non-linearities and uncertainty go hand in hand. In fact, the utility function's curvature determines the degree of risk-aversion. This concept is exploited in the first article of this thesis, which incorporates uncertainty into a small-scale DSGE model. More specifically, this is done by a second-order approximation, while carrying out the derivation in great detail and carefully discussing the more formal aspects. Moreover, the consequences of this method are discussed when calibrating the equilibrium condition. The second article of the thesis considers the essential model part of the first paper and focuses on the (forward-looking) data needed to meet the model's requirements. A large number of uncertainty measures are utilized to explain a possible approximation bias. The last article keeps to the same topic but uses statistical distributions instead of actual data. In addition, theoretical (model) and calibrated (data) parameters are used to produce more general statements. In this way, several relationships are revealed with regard to a biased interpretation of this class of models. In this dissertation, the respective approaches are explained in full detail and also how they build on each other.
In summary, the question remains whether the exact interpretation of model equations should play a role in macroeconomics. If we answer this positively, this work shows to what extent the practical use can lead to biased results.