Ein neues Angebot speziell für Ärztinnen und Ärzte: Im November 2017 startet des CAS in Medical Leadership, mit dem Ziel, Personen mit Führungs- und Managementaufgaben in Kliniken und Spitälern Grundkenntnisse in den Bereichen Governance, Management, Finanzielle Führung, Leadership sowie Kommunikation zu vermitteln. Am 7. Juni 2017 findet um 18.30 Uhr ein Informationsanlass statt.
Recent experiments suggest that dishonesty can escalate from small levels to ever-larger ones along a 'slippery slope'. Activity in bilateral amygdala tracks this gradual adaptation to repeated acts of self-serving dishonesty.
How are optimal taxes affected by superstar phenomena? To answer this question, we extend the Mirrlees model to incorporate an assignment problem in the labor market that generates superstar effects. Perhaps surprisingly, rather than providing a rationale for higher taxes, we show that superstar effects provide a force for lower marginal taxes conditional on the observed distribution of earnings. Superstar effects make the earnings schedule convex, which increases the responsiveness of individual earnings to tax changes. We show that various common elasticity measures must be adjusted upward in optimal tax formulas. Finally, we study a comparative static that does not keep the observed earnings distribution fixed: when superstar technologies are introduced, inequality increases but we obtain a neutrality result, finding optimal taxes unaltered
This paper defines and studies a variable selection procedure called Testing-Based Forward Model Selection. The procedure inductively selects covariates which increase predictive accuracy into a working statistical regression model until a stopping criterion is met. The stopping criteria and selection criteria are defined using statistical hypothesis tests. The paper explicitly describes a testing procedure in the context of high-dimensional linear regression with heteroskedastic disturbances. Finally, a simulation study examines finite sample performance of the proposed procedure and shows that it behaves favorably in high-dimensional sparse settings in terms of prediction error and size of selected model.
What determines risk-bearing capacity and the amount of leverage in financial markets? Using unique archival data on collateralized lending, we show that personal experience can affect individual risk-taking and aggregate leverage. When an investor syndicate speculating in Amsterdam in 1772 went bankrupt, many lenders were exposed. In the end, none of them actually lost money. Nonetheless, only those at risk of losing money changed their behavior markedly; they lent with much higher haircuts. The rest continued largely as before. The differential change is remarkable since the distress was public knowledge. Overall leverage in the Amsterdam stock market declined as a result.
We propose a valuation method for financial assets subject to default risk, where investors cannot observe the state variable triggering the default but observe a correlated price process. The model is sufficiently general to encompass a large class of structural models and can be seen as a generalization of the model of Duffie and Lando (Econometrica 69:633–664, [2001]). In this setting we prove that the default time is totally inaccessible in the market’s filtration and derive the conditional default probabilities and the intensity process. Finally, we provide pricing formulas for default-sensitive claims and illustrate in particular examples the shapes of the credit spreads.
To reduce poverty and food insecurity in Africa requires raising productivity in agriculture. Systematic use of fertilizer and hybrid seed is a pathway to increased productivity, but adoption of these technologies remains low. We investigate whether the quality of agricultural inputs can help explain low take-up. Testing modern products purchased in local markets, we find that 30% of nutrient is missing in fertilizer, and hybrid maize seed is estimated to contain less than 50% authentic seeds. We document that such low quality results in low average returns. If authentic technologies replaced these low-quality products, however, average returns are high. To rationalize the findings, we calibrate a learning model using data from our agricultural trials. Because agricultural yields are noisy, farmers’ ability to learn about quality is limited and this can help explain the low quality equilibrium we observe, but also why the market has not fully collapsed.
Most models of ambiguity aversion satisfy Anscombe-Aumann’s Monotonicity axiom. Monotonicity imposes separability of preferences across events that occur with unknown probability. We construct a test of Monotonicity by modifying the Allais paradox to a setting with both subjective and objective uncertainty. Two experimental studies are conducted: while study 1 uses U.S. online workers and a natural source of ambiguity, study 2 employs European students and an Ellsberg urn. In both studies, modal behavior violates Monotonicity in a specific, intuitive way. Overall, our data suggest that violations of Monotonicity are as prevalent as violations of von Neumann-Morgenstern’s Independence axiom.
The occurrence of some events can impact asset prices and produce losses. The amplitude of these losses are partly determined by the degree of predictability of those events by the market investors, as risk premiums build up in an asset price as a compensation of the anticipated losses. The aim of this paper is to propose a general framework where these phenomena can be properly defined and quantified.
Our focus are the default events and the defaultable assets, but the framework could apply to any event whose occurrence impacts some asset prices.
We provide the general construction of a default time under the so called (H) hypothesis, which reveals a useful way in which default models can be built, using both market factors and idiosyncratic factors. All the relevant characteristics of a default time (i.e. the Azema supermartingale and its Doob-Meyer decomposition) are explicitly computed given the information about these factors.
We then define the default event risk premiums and the default adjusted probability measure. These concepts are useful for pricing defaultable claims in a framework that includes possible economic shocks, such as jumps of the recovery process or of some default-free assets at the default time. These formulas are not classic and we point out that the knowledge of the default compensator (or the intensity process when the default time is totally inaccessible) is not a sufficient quantity for finding explicit prices; the Azema supermartingale and its Doob-Meyer decomposition are needed. The progressive enlargement of a filtration framework is the right tool for pricing defaultable claims in non standard frameworks where non defaultable assets or recovery processes may react at the default event.
