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on Neuroeconomics |
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Issue of 2018‒02‒12
three papers chosen by |
| By: | Dmitry Lyusin (National Research University Higher School of Economics); Abdul-Raheem Mohammed (National Research University Higher School of Economics) |
| Abstract: | The temporal dynamic characteristics of mood play an important role in various aspects of our lives including our psychological health and well-being. It is assumed that the individuals with high emotional intelligence (EI) are characterized by more positive and stable moods. However, most studies analyze how EI is related to emotional traits or momentary assessments of mood; there are almost no findings on EI relationships with mood dynamics. The present study fills this gap. Two research questions were asked. How mood dynamics characteristics are related to each other and to what extent are they independent? Which aspects of EI are related to particular characteristics of mood dynamics? Method. To collect data on mood dynamics, an experience sampling procedure was implemented. Twenty-six female participants reported their mood for two weeks, three times a day, using the EmoS-18 questionnaire. Their emotional intelligence was measured with the EmIn questionnaire. Mean mood scores calculated across all measurement points were regarded as static characteristics showing a mood background typical for the participant. Also, three dynamic characteristics of mood were calculated, namely variability, instability, and inertia. Results. Mood variability and instability were found to be very closely related to each other, measuring essentially the same construct. Inertia is relatively independent. EI was not related to mean mood scores which contradicts the results of other studies and can be explained by the use of the experience sampling procedure. EI was positively related to the inertia of a positive mood with high arousal and a negative mood with low arousal. In addition, a negative relationship between EI and the instability of tension was found. Most of the correlations were low. Further studies with higher statistical power are needed for more decisive conclusions. However, the results show that experience sampling provides new important insights on the role of EI in mood |
| Keywords: | emotional intelligence, mood dynamics, mood variability, mood instability, mood inertia |
| JEL: | Z |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:hig:wpaper:88psy2018&r=neu |
| By: | Gema Zamarro (University of Arkansas & University of Southern California) |
| Abstract: | Social science, more than ever, is drawing upon the insights of personality psychology. Though researchers now know that noncognitive skills and personality traits, such as conscientiousness, grit, self-control, or a growth mindset could be important for life outcomes, they struggle to find reliable measures of these skills. Self-reports are often used for analysis, but these measures have been found to be affected by important biases. We study the validity of innovative, more robust measures of noncognitive skills based on performance tasks. Our first proposed measure is an adaptation, for the adult population, of the Academic Diligence Task (ADT) developed and validated among students by Galla et al. (2014). For our second type of performance task measures of noncognitive skills, we argue that questionnaires themselves can be seen as performance tasks, such that measures of survey effort, e.g. item non-response rates and degree of carelessness in answering, could lead to meaningful measures of noncognitive skills. New measures along with self-reports are then used to study the role of noncognitive skills and personality traits on an individual’s preparation for retirement and financial capability. In a world where individuals are increasingly asked to take responsibility for retirement preparations and when available financial products to do so are growing in sophistication, a better understanding of how noncognitive skills influence retirement preparation could help effective policy design. |
| Date: | 2017–09 |
| URL: | http://d.repec.org/n?u=RePEc:mrr:papers:wp365&r=neu |
| By: | Jehiel, Philippe; Steiner, Jakub |
| Abstract: | A proposed model of information processing generates a prediction about the constrained-optimal stochastic choice that is robust to details of the feasible information structures. A decision-maker processes payoff-relevant information until she reaches her cognitive constraint, at which point she either terminates the decision-making and chooses an action, or restarts the process. By conditioning the probability of termination on the information collected, she controls the correlation between the payoff state and her terminal action. The constrained-optimal choice rule exhibits (i) confirmation bias, (ii) speed-accuracy complementarity, (iii) overweighting of rare events, and (iv) salience effect. |
| Date: | 2017–12 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:12546&r=neu |