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Andreas Hackethal: Better than a pension guarantee would be to allow citizens finally more insights.
Discriminating inflation
(2018)
Alexander Ludwig: An expert commission makes sense – but why expert opinion only after 2025 and clientele policy before?
Diskriminierende Inflation
(2018)
Augmented reality (AR) gained much public attention since the success of Pok´emon Go in 2016. Technology companies like Apple or Google are currently focusing primarily on mobile AR (MAR) technologies, i.e. applications on mobile devices, like smartphones or tablets. Associated privacy issues have to be investigated early to foster market adoption. This is especially relevant since past research found several threats associated with the use of smartphone applications. Thus, we investigate two of the main privacy risks for MAR application users based on a sample of 19 of the most downloaded MAR applications for Android. First, we assess threats arising from bad privacy policies based on a machine-learning approach. Second, we investigate which smartphone data resources are accessed by the MAR applications. Third, we combine both approaches to evaluate whether privacy policies cover certain data accesses or not. We provide theoretical and practical implications and recommendations based on our results.
Advanced machine learning has achieved extraordinary success in recent years. “Active” operational risk beyond ex post analysis of measured-data machine learning could provide help beyond the regime of traditional statistical analysis when it comes to the “known unknown” or even the “unknown unknown.” While machine learning has been tested successfully in the regime of the “known,” heuristics typically provide better results for an active operational risk management (in the sense of forecasting). However, precursors in existing data can open a chance for machine learning to provide early warnings even for the regime of the “unknown unknown.”
A commentary on Commentary: Aesthetic Pleasure versus Aesthetic Interest: The Two Routes to Aesthetic Liking by Consoli, G. (2017). Front. Psychol. 8:1197. doi: 10.3389/fpsyg.2017.01197
In his commentary on the paper “Aesthetic Pleasure versus Aesthetic Interest: The Two Routes to Aesthetic Liking,” authored by Jan R. Landwehr and myself (Graf and Landwehr, 2017), Consoli (2017) deplores two aspects of our paper. First, an inadequate definition and operationalization of the key constructs aesthetic pleasure, aesthetic interest, and aesthetic liking, respectively aesthetic attractiveness. Second, the conclusions drawn from our empirical studies. While I acknowledge that one may have a different theoretical perspective on aesthetic perception and evaluation, it appears that Consoli's (2017) commentary does not even address the empirical data of our studies but only our theoretical assumptions and definitions. In the following, I will address Consoli's (2016, 2017) arguments in more detail, and I will corroborate our theoretical reasoning with the empirical data of our studies (Graf and Landwehr, 2017).....
Inhibitory interneurons govern virtually all computations in neocortical circuits and are in turn controlled by neuromodulation. While a detailed understanding of the distinct marker expression, physiology, and neuromodulator responses of different interneuron types exists for rodents and recent studies have highlighted the role of specific interneurons in converting rapid neuromodulatory signals into altered sensory processing during locomotion, attention, and associative learning, it remains little understood whether similar mechanisms exist in human neocortex. Here, we use whole-cell recordings combined with agonist application, transgenic mouse lines, in situ hybridization, and unbiased clustering to directly determine these features in human layer 1 interneurons (L1-INs). Our results indicate pronounced nicotinic recruitment of all L1-INs, whereas only a small subset co-expresses the ionotropic HTR3 receptor. In addition to human specializations, we observe two comparable physiologically and genetically distinct L1-IN types in both species, together indicating conserved rapid neuromodulation of human neocortical circuits through layer 1.
Exploiting the natural experiment of the German reunification, we examine how consumers adapt to a new environment in their macroeconomic forecasting. We document that East Germans expect higher in inflation and make larger forecast errors than West
Germans even decades after reunification. Differences in consumption baskets, financial literacy, risk aversion or trust in the central bank cannot fully account for these patterns. We find most support for the explanation that East Germans, who were used to a strong norm of zero inflation, persistently overadjusted the level of their expectations in the face of the initial inflation shock in reunified Germany. Our findings suggest that large changes in the economic environment can permanently impede people's ability to form accurate macroeconomic expectations, with an important role for the interaction of old norms and new experiences around the event.
Policymakers attach an important role to the macroeconomic outlook of households. Using a representative online panel form the U.S., the authors examine how individuals' macroeconomic expectations causally affect their personal economic prospects and their behavior and provide them with different professional forecasts about the likelihood of a recession. The authors find that groups with the largest exposure to aggregate risk, such as individuals working in cyclical industries, are most likely to respond to an improved macroeconomic outlook, while a large fraction of the population is unlikely to react.