Mental accounting, access motives, and overinsurance

People exercising mental accounting have an additional motive for buying insurance. They perceive a risk of having insufficient funds available to self-insure. In this way insurance protects the consumption value of the insured asset beyond the expenditure to acquire/replace it. This complements previous approaches based on probability weighting and loss aversion to explain the high profitability of warranties and an aversion toward deductibles. It helps to account for why the value of a warranty is found to be positively related to the value of the product and why there is seemingly contradictory empirical evidence on how household income affects demand for warranties. The adapted model rationalizes a strong aversion to deductibles, and explains the observed sensitivity of this aversion to the insurance context. Finally, it predicts a strong impact of how an insurer pays out benefits on the value and cost of insurance. This can explain both the evidence on strong deductible aversion for flood insurance and the lack of such evidence for long-term care insurance

ACTH-Bestimmungen im Plasma aus dem Bulbus cranialis venae jugularis

Der Anstieg der Corticosteroninkretion in das Nebennierenvenenblut frisch hypophysektomierter Ratten diente zur Bestimmung von ACTH-Spiegeln in 1 ml nativen, menschlichen Plasma. Normale ACTH-Plasmaspiegel sind sowohl bei Punktion der Vena cubitalis als auch des Bulbus cranialis venae jugularis durch diese Methode nicht oder nur ungenau zu erfassen. Bei Patienten mit pathologisch erhöhten ACTH-Spiegeln in der Vena cubitalis sind die ACTH-Spiegel im Bulbus cranialis venae jugularis signifikant höher. Es ließ sich eine Beziehung zwischen ACTH-Spiegel in der Peripherie (Vena cubitalis), Differenz der ACTH-Spiegel zwischen Bulbus cranialis venae jugularis und Vena cubitalis und biologischer Halbwertszeit von endogenem ACTH aufstellen. Nach den Ergebnissen der Bestimmung von ACTH-Spiegeln bei Nebennierengesunden läßt sich folgern, daß die biologische Halbwertszeit von endogenem ACTH größer als 4 min sein muß. Bei Patienten mit erhöhten ACTH-Spiegeln ließ sich die biologische Halbwertszeit von endogenem ACTH größenordnungsmäßig mit ca. 40 min berechnen. Bei diesen Patienten betrug die mittlere tägliche ACTH-Inkretion ca. 100 E.ACTH-contents of 1 ml specimens of human plasma were assayed by measurement of increases of corticosterone output in the adrenal vein of acutely hypophysectomized rats. This procedure is not sensitive enough to measure normal ACTH-levels acurately, neither when blood was drawn from the bulbus cranialis venae jugularis, nor from the vena cubitalis. In patients having pathologically elevated ACTH-levels, the ACTH-content of plasma is significantly higher in the bulbus cranialis venae jugularis than in peripheral venous blood. An equation is presented formulating the relation of peripheral ACTH-levels, differences of ACTH-levels between bulbus cranialis venae jugularis and vena cubitalis, and of the biological halflife of endogenous ACTH. On the basis of the results of the determinations of socalled normal ACTH-levels it can be concluded, that the biological halflife of endogenous ACTH is longer than 4 min. From the data of patients with elevated ACTH-levels a halflife of approximately 40 min and a mean ACTH-secretion of approx. 100 units per day could be calculated

Prospect theory, mitigation and adaptation to climate change

Climate change is one of the most pressing challenges in current environmental policy. Appropriate policies intended to stimulate efficient adaptation and mitigation should not exclusively rely on the assumption of the homo oeconomicus, but take advantage of well-researched alternative behavioural patterns. Prospect theory provides a number of climate-relevant insights, such as the notion that evaluations of outcomes are reference dependent, and the relevance of perceived certainty of outcomes. This paper systematically reviews what prospect theory can offer to analyse mitigation and adaptation. It is shown that accounting for reference dependence and certainty effects contributes to a better understanding of some well-known puzzles in the climate debate, including (but not limited to) the different uptake of mitigation and adaptation amongst individuals and nations, the role of technical vs. financial adaptation, and the apparent preference for hard protection measures in coastal adaptation. Finally, concrete possibilities for empirical research on these effects are proposed

An analysis-ready and quality controlled resource for pediatric brain white-matter research

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets

An analysis-ready and quality controlled resource for pediatric brain white-matter research

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets. BárbaraAvelar-Pereira 9 , EthanRoy2 , Valerie J.Sydnor3,4,5, JasonD.Yeatman1,2, The Fibr Community Science Consortium*, TheodoreD.Satterthwaite3,4,5,88 & Ariel Roke