Versicherungsvertragliche Anzeigepflicht und Garantiehaftung für culpa in contrahendo

To sanction the insurant’s obligation to disclose the risk-relevant circumstances by the insurer’s exemption from performance does not comply with the ordinary pattern of pre-contractual liability. Instead of making the insurant responsible for the consequences of his breach of duty, the German Insurance Act subjects him to a guarantee which is comparable to the one imposed by the German Civil Code in the case of initial impossibility. The insurant has to guarantee that the facts which he did not, or at least not entirely, disclose do not cause any obligation of the insurer. The structure of this sanction is equivalent to the insurer’s so-called liability of performance. But contrary to the latter it can be justified by the specific importance of the insurant’s pre-contractual obligation of disclosure.     

Network Structure and Airline Scheduling

This paper provides a simple analysis of the effects of network structure on the scheduling, traffic, and aircraft size choices of a monopoly airline. The analysis shows that switching to a hub-and-spoke network leads to increases in both flight frequency and aircraft size, while stimulating local traffic in and out of the hub. In addition, HS networks are shown to be preferred by the airline when travel demand is low, when flights are expensive to operate, and when passengers place a high value on flight frequency but are not excessively inconvenienced by the extra travel time required for a connecting trip. The welfare analysis shows that the flight frequency, traffic volumes, and aircraft size chosen by the monopolist are all inefficiently low under both network types. Moreover, in the most plausible case, the monopolist's network choice exhibits an inefficient bias toward the HS network, apparently reflecting an excessive desire to economize on the number of flights.     

Management earnings forecasts and other forward-looking statements

We identify forward-looking statements (FLS) in firms’ disclosures to distinguish between “forecast-like” (quantitative statements about earnings) and “other”, or non-forecast-like, FLS.  We show that, like earnings forecasts, other FLS generate significant investor and analyst responses. Unlike earnings forecasts, other FLS are issued more frequently when uncertainty is higher. We then show that earnings-related FLS are more sensitive to uncertainty than quantitative statements, suggesting that managers are more likely to alter the content than the form of FLS when uncertainty is higher.  Our study indicates that incorporating other FLS into empirical measures provides a more comprehensive proxy for firms’ voluntary disclosures.     

The rise of defensive engineering: how personal liability considerations impact decision-making

Abstract

Based on a survey of Australian engineers (n = 275) this paper examines the impact of personal liability considerations on engineering decision-making. Almost all respondents who make high-stakes decisions saw questions of liability as having both positive (90%) and negative (87%) impacts. Our analysis shows that awareness of personal liability acts to focus the attention of many engineers on the moral dimension of their work. However, it also encourages more expensive decision-making, inhibition of innovation and professional paralysis. We argue that while personal legal liability is a legitimate way to focus engineers’ attention on the potential impact of their work, a problem arises when decision-makers are held responsible for disasters over which they had little control. The focus then shifts to ‘defensive engineering’ practices that are aimed at limiting individual liability rather than disaster prevention. Legal processes that are seen to unfairly allocate blame do not encourage practices that support future disaster prevention.     

Mean–variance and mean–semivariance portfolio selection: a multivariate nonparametric approach

While univariate nonparametric estimation methods have been developed for estimating returns in mean-downside risk portfolio optimization, the problem of handling possible cross-correlations in a vector of asset returns has not been addressed in portfolio selection. We present a novel multivariate nonparametric portfolio optimization procedure using kernel-based estimators of the conditional mean and the conditional median. The method accounts for the covariance structure information from the full set of returns. We also provide two computational algorithms to implement the estimators. Via the analysis of 24 French stock market returns, we evaluate the in-sample and out-of-sample performance of both portfolio selection algorithms against optimal portfolios selected by classical and univariate nonparametric methods for three highly different time periods and different levels of expected return. By allowing for cross-correlations among returns, our results suggest that the proposed multivariate nonparametric method is a useful extension of standard univariate nonparametric portfolio selection approaches.     

Modified efficient importance sampling for partially non‐Gaussian state space models

The construction of an importance density for partially non‐Gaussian state space models is crucial when simulation methods are used for likelihood evaluation, signal extraction, and forecasting. The method of efficient importance sampling is successful in this respect, but we show that it can be implemented in a computationally more efficient manner using standard Kalman filter and smoothing methods. Efficient importance sampling is generally applicable for a wide range of models, but it is typically a custom‐built procedure. For the class of partially non‐Gaussian state space models, we present a general method for efficient importance sampling. Our novel method makes the efficient importance sampling methodology more accessible because it does not require the computation of a (possibly) complicated density kernel that needs to be tracked for each time period. The new method is illustrated for a stochastic volatility model with a Student's t distribution.     

Exploring business process modelling paradigms and design-time to run-time transitions

The business process management literature describes a multitude of approaches (e.g. imperative, declarative or event-driven) that each result in a different mix of process flexibility, compliance, effectiveness and efficiency. Although the use of a single approach over the process lifecycle is often assumed, transitions between approaches at different phases in the process lifecycle may also be considered. This article explores several business process strategies by analysing the approaches at different phases in the process lifecycle as well as the various transitions.     

Effectiveness of independent boards of UCITS funds

In order to protect fund investors against conflicts of interest with fund management companies, US funds have mandatory independent directors, but this obligation is not required under the European Union Undertakings for Collective Investment in Transferable Securities (UCITS) Directive. Nevertheless, a considerable number of UCITS funds do have independent directors. Whether independent directors should also be mandatory in Europe has been a topic of ongoing debate. Using a sample of Luxembourg UCITS, we test the hypothesis that more independent boards add value for investors through lower costs and/or better investment performance, but we fail to find supporting evidence, even for funds with a higher risk of conflicts of interest. Oversight by independent depositaries and institutional shareholders does not seem to be effective either. It appears that board attitude and the sponsor distribution model are more important since we find evidence that boards that prioritise cost monitoring have lower costs and that independent sponsor funds have better performance. These results question the effectiveness of self-regulation or formal regulation requiring independent board members.     

POSTERIOR‐PREDICTIVE EVIDENCE ON US INFLATION USING EXTENDED NEW KEYNESIAN PHILLIPS CURVE MODELS WITH NON‐FILTERED DATA

Changing time series properties of US inflation and economic activity, measured as marginal costs, are modeled within a set of extended New Keynesian Phillips curve (NKPC) models. It is shown that mechanical removal or modeling of simple low‐frequency movements in the data may yield poor predictive results which depend on the model specification used. Basic NKPC models are extended to include structural time series models that describe typical time‐varying patterns in levels and volatilities. Forward‐ and backward‐looking expectation components for inflation are incorporated and their relative importance is evaluated. Survey data on expected inflation are introduced to strengthen the information in the likelihood. Use is made of simulation‐based Bayesian techniques for the empirical analysis. No credible evidence is found on endogeneity and long‐run stability between inflation and marginal costs. Backward‐looking inflation appears stronger than forward‐looking inflation. Levels and volatilities of inflation are estimated more precisely using rich NKPC models. The extended NKPC structures compare favorably with existing basic Bayesian vector autoregressive and stochastic volatility models in terms of fit and prediction. Tails of the complete predictive distributions indicate an increase in the probability of deflation in recent years. Copyright © 2014 John Wiley & Sons, Ltd.     

Timing the Start of Material Substitution Projects: Creating Switching Options under Volatile Material Prices

Firms developing new products often face the challenge of making investment decisions under uncertain input–cost conditions due to the price volatilities of the materials they use. These decisions need to be made long before the final products are launched on the market. Therefore, firms that invest in the opportunity to switch materials in a timely manner will have the flexibility to react to material price changes and realize competitive advantages. However, volatile material prices may also cause a firm to delay investment. Using real‐options reasoning, this paper studies the influence of input‐cost fluctuations on the timing decision to start new product development (NPD) and thus create the follow‐on opportunity to later replace an existing product. A model that combines waiting and switching options to derive influencing factors of the flexibility value that triggers the investment is developed and tested on a sample of material substitution projects from manufacturing firms. The results show how price uncertainty of the new and the old material, their joint price development, the expected project duration, and competitive preemption are related to the propensity to delay the start of NPD. The findings provide new insights on how timing in adopting materials can be used to hedge exposure to volatile material prices. The insights are relevant for adopters and producers of new materials, as well as for policy makers who strive for supporting the diffusion of new materials.