Dynamics of Fluctuating Bose-Einstein Condensates

We present a generalized Gross-Pitaevskii equation that describes also the dissipative dynamics of a trapped partially Bose condensed gas. It takes the form of a complex nonlinear Schr\"odinger equation with noise. We consider an approximation to this Langevin field equation that preserves the correct equilibrium for both the condensed and the noncondensed parts of the gas. We then use this formalism to describe the reversible formation of a one-dimensional Bose condensate, and compare with recent experiments. In addition, we determine the frequencies and the damping of collective modes in this case.Comment: 4 pages of REVTeX, including 4 figure

Competition Leverage: How the Demand Side Affects Optimal Risk Adjustment

We study optimal risk adjustment in imperfectly competitive health insurance markets when high-risk consumers are less likely to switch insurer than low-risk consumers. First, we find that insurers still have an incentive to select even if risk adjustment perfectly corrects for cost differences among consumers. Consequently, the outcome is not efficient even if cost differences are fully compensated. To achieve first best, risk adjustment should overcompensate for serving high-risk agents to take into account the difference in mark- ups among the two types. Second, the difference in switching behavior creates a trade off between efficiency and consumer welfare. Reducing the difference in risk adjustment subsidies to high and low types increases consumer welfare by leveraging competition from the elastic low-risk market to the less elastic high-risk market. Finally, mandatory pooling can increase consumer surplus even further, at the cost of efficiency.health insurance;risk adjustment;imperfect competition;leverage

Competition for Traders and Risk

Abstract: The financial crisis has been attributed partly to perverse incentives for traders at banks and has led policy makers to propose regulation of banks’ remuneration packages. We explain why poor incentives for traders cannot be fully resolved by only regulating the bank’s top executives, and why direct intervention in trader compensation is called for. We present a model with both trader moral hazard and adverse selection on trader abilities. We demonstrate that as competition on the labour market for traders intensifies, banks optimally offer top traders contracts inducing them to take more risk, even if banks fully internalize the costs of negative outcomes. In this way, banks can reduce the surplus they have to offer to lower ability traders. In addition, we find that increasing banks’ capital requirements does not unambiguously lead to reduced risk-taking by their top traders.optimal contracts;remuneration policy;imperfect competition;financial institutions;risk

Selective Contracting and Foreclosure in Health Care Markets

We analyze exclusive contracts between health care providers and insurers in a model where some consumers choose to stay uninsured. In case of a monopoly insurer, exclusion of a provider changes the distribution of consumers who choose not to insure. Although the foreclosed care provider remains active in the market for the non-insured, we show that exclusion leads to anti-competitive effects on this non-insured market. As a consequence exclusion can raise industry profits, and then occurs in equilibrium. Under competitive insurance markets, the anticompetitive exclusive equilibrium survives. Uninsured consumers, however, are now not better off without exclusion. Competition among insurers raises prices in equilibria without exclusion, as a result of a horizontal analogue to the double marginalization effect. Instead, under competitive insurance markets exclusion is desirable as long as no provider is excluded by all insurers.health insurance;uninsured;selective contracting;exclusion;foreclosure;anti-competitive effects

The effect of adherence to statin therapy on cardiovascular mortality : quantification of unmeasured bias using falsification end-points

Background: To determine the clinical effectiveness of statins on cardiovascular mortality in practice, observational studies are needed. Control for confounding is essential in any observational study. Falsification end-points may be useful to determine if bias is present after adjustment has taken place. Methods: We followed starters on statin therapy in the Netherlands aged 46 to 100 years over the period 1996 to 2012, from initiation of statin therapy until cardiovascular mortality or censoring. Within this group (n = 49,688, up to 16 years of follow-up), we estimated the effect of adherence to statin therapy (0 = completely non-adherent, 1 = fully adherent) on ischemic heart diseases and cerebrovascular disease (ICD10-codes I20-I25 and I60-I69) as well as respiratory and endocrine disease mortality (ICD10-codes J00-J99 and E00-E90) as falsification end points, controlling for demographic factors, socio-economic factors, birth cohort, adherence to other cardiovascular medications, and diabetes using time-varying Cox regression models. Results: Falsification end-points indicated that a simpler model was less biased than a model with more controls. Adherence to statins appeared to be protective against cardiovascular mortality (HR: 0.70, 95 % CI 0.61 to 0.81). Conclusions: Falsification end-points helped detect overadjustment bias or bias due to competing risks, and thereby proved to be a useful technique in such a complex setting

Neuroprediction and A.I. in Forensic Psychiatry and Criminal Justice: A Neurolaw Perspective

Advances in the use of neuroimaging in combination with A.I., and specifically the use of machine learning techniques, have led to the development of brain-reading technologies which, in the nearby future, could have many applications, such as lie detection, neuromarketing or brain-computer interfaces. Some of these could, in principle, also be used in forensic psychiatry. The application of these methods in forensic psychiatry could, for instance, be helpful to increase the accuracy of risk assessment and to identify possible interventions. This technique could be referred to as ‘A.I. neuroprediction,’ and involves identifying potential neurocognitive markers for the prediction of recidivism. However, the future implications of this technique and the role of neuroscience and A.I. in violence risk assessment remain to be established. In this paper, we review and analyze the literature concerning the use of brain-reading A.I. for neuroprediction of violence and rearrest to identify possibilities and challenges in the future use of these techniques in the fields of forensic psychiatry and criminal justice, considering legal implications and ethical issues. The analysis suggests that additional research is required on A.I. neuroprediction techniques, and there is still a great need to understand how they can be implemented in risk assessment in the field of forensic psychiatry. Besides the alluring potential of A.I. neuroprediction, we argue that its use in criminal justice and forensic psychiatry should be subjected to thorough harms/benefits analyses not only when these technologies will be fully available, but also while they are being researched and developed