Models for Extremal Dependence Derived from Skew‐symmetric Families

Skew‐symmetric families of distributions such as the skew‐normal and skew‐t represent supersets of the normal and t distributions, and they exhibit richer classes of extremal behaviour. By defining a non‐stationary skew‐normal process, which allows the easy handling of positive definite, non‐stationary covariance functions, we derive a new family of max‐stable processes – the extremal skew‐t process. This process is a superset of non‐stationary processes that include the stationary extremal‐t processes. We provide the spectral representation and the resulting angular densities of the extremal skew‐t process and illustrate its practical implementation.     

The antecedents of new R&D collaborations with different partner types: On the dynamics of past R&D collaboration and innovative performance

We examine firms' propensity to adapt their R&D collaboration portfolio by establishing new types of R&D collaboration with different kinds of partners (suppliers, customers, competitors and universities & public research institutions). We argue that existing R&D collaboration with one of the two value chain partners (suppliers or customers) is associated with the formation of new R&D collaboration with the other value chain partner to ensure temporal alignment in innovation within the value chain. In contrast, issues related to governance and unintended knowledge spillovers suggest that ‘horizontal’ R&D collaboration with competitors only spurs R&D collaboration with other partner types if such competitor R&D collaboration has been discontinued earlier (‘delayed temporal alignment’). We posit that persistent prior R&D collaboration with institutional partners is an antecedent to the establishment of new R&D collaboration with industrial partners, and that discontinuation of a particular type of R&D collaboration is likely to lead to a restart of such R&D collaborative effort. Strong prior innovative performance is expected to increase the probability that firms establish R&D collaborations with new partner types, except for R&D collaboration with competitors, since the most innovative firms may fear leakage of proprietary knowledge to rivals. We find broad support for these predictions in a large panel of Spanish innovating firms (2004–2011). Our findings highlight that it is not just the configuration of R&D collaborations with existing partner types that predicts tie formation with new partner types, but also the intertemporal pattern of prior R&D collaboration and managerial discretion provided by past innovation success.     

How Selective Are Real Wage Cuts? A Micro‐analysis Using Linked Employer–Employee Data

Using linked employer–employee panel data for Germany, we investigate whether firms implement real wage reductions in a selective manner. In line with insider–outsider and several strands of efficiency wage theory, we find strong evidence for selective wage cuts with high‐productivity workers being spared even when controlling for permanent differences in firms' wage policies. In contrast to some recent contributions stressing fairness considerations, we also find that wage cuts increase wage dispersion among peers rather than narrowing it. Notably, the same selectivity pattern shows up when restricting our analysis to firms covered by collective agreements or having a works council.     

Carrying on Samir Amin’s legacy

ABSTRACT

The academic Marxism of the 20th century has shied away from this responsibility, preferring relatively comfortable staying within the walls of universities. Unlike these academic thinkers Samir Amin was one of the few who did not accept this situation. He never considered himself merely a theorist: connection to praxis was vital for him. From this perspective he advocated a project of Fifth International to address sharp and systemic crisis afflicting leftist movements. Each new stage of the evolution of capitalism requires a corresponding transformation of the anti-capitalist forces. Nevertheless, a new political alternative can’t be constructed artificially. It can only gradually emerge out of collective experience of different struggles.     

A Euclidean Likelihood Estimator for Bivariate Tail Dependence

The spectral measure plays a key role in the statistical modeling of multivariate extremes. Estimation of the spectral measure is a complex issue, given the need to obey a certain moment condition. We propose a Euclidean likelihood-based estimator for the spectral measure which is simple and explicitly defined, with its expression being free of Lagrange multipliers. Our estimator is shown to have the same limit distribution as the maximum empirical likelihood estimator of Einmahl and Segers (2009 Einmahl , J. H. J. , Segers , J. ( 2009 ). Maximum empirical likelihood estimation of the spectral measure of an extreme-value distribution . Ann. Statist. 37 ( 5B ): 2953 – 2989 .[Crossref], [Web of Science ®] , [Google Scholar]). Numerical experiments suggest an overall good performance and identical behavior to the maximum empirical likelihood estimator. We illustrate the method in an extreme temperature data analysis.     

Evidence synthesis through a degradation model applied to myocardial infarction

We propose an evidence synthesis approach through a degradation model to estimate causal influences of physiological factors on myocardial infarction (MI) and coronary heart disease (CHD). For instance several studies give incidences of MI and CHD for different age strata, other studies give relative or absolute risks for strata of main risk factors of MI or CHD. Evidence synthesis of several studies allows incorporating these disparate pieces of information into a single model. For doing this we need to develop a sufficiently general dynamical model; we also need to estimate the distribution of explanatory factors in the population. We develop a degradation model for both MI and CHD using a Brownian motion with drift, and the drift is modeled as a function of indicators of obesity, lipid profile, inflammation and blood pressure. Conditionally on these factors the times to MI or CHD have inverse Gaussian ( ${\mathcal{IG}}$ ) distributions. The results we want to fit are generally not conditional on all the factors and thus we need marginal distributions of the time of occurrence of MI and CHD; this leads us to manipulate the inverse Gaussian normal distribution ( ${\mathcal{IGN}}$ ) (an ${\mathcal{IG}}$ whose drift parameter has a normal distribution). Another possible model arises if a factor modifies the threshold. This led us to define an extension of ${\mathcal{IGN}}$ obtained when both drift and threshold parameters have normal distributions. We applied the model to results published in five important studies of MI and CHD and their risk factors. The fit of the model using the evidence synthesis approach was satisfactory and the effects of the four risk factors were highly significant.     

Impact of Customer‐based Corporate Reputation on Non‐monetary and Monetary Outcomes: The Roles of Commitment and Service Context Risk

A firm's reputation is an important intangible asset, because of its potential for value creation. The authors explore non‐monetary and monetary outcomes of customer‐based corporate reputation (CBR) and hypothesize that commitment serves as a partial mediator, while service context risk is a moderator, of these relationships. Using a large sample of service customers who evaluated the reputation of service firms in four service categories, the results show that (1) commitment partially mediates the relationship between CBR and most of the outcome variables, and (2) service provider selection risk moderates these relationships, such that reputation has a stronger effect on several non‐monetary outcomes for higher‐risk services and commitment has a stronger effect for lower‐risk services, consistent with a dual‐processing framework explanation. The authors discuss the theoretical and managerial implications.     

The financial structure of innovative SMEs in Germany

In politics and business the special role of innovative businesses whose research and development activities expedite technological progress has received steady attention. Especially small and medium sized businesses (SMEs) have initiated promising innovation projects. However, when analysing these projects our research must take into account that SMEs cannot be viewed as a homogeneous business category. Moreover, financing their innovations, SMEs are subject to unique issues. To shed light on these problems, this study will develop an index measuring degrees of innovation. It allows the 171 sample companies to be categorised into three groups: non-innovative, moderately innovative or highly innovative. A multinomial logistic regression is used to examine the quality of this typology. In addition, group-specific differences in the financing mix are demonstrated. Finally, from a theoretical point of view, the implications of the pecking order theory are basically validated. On the other hand, the concept of the financial growth cycle does not deliver satisfactory results.     

Konfliktcoaching in der Gruppe Trainingskonzept und Erfahrungsbericht

Conflict coaching in groups. A training concept and a case study The following article lines out and discusses the main contents of a workshop on conflict coaching in groups: focussing on conflict and conflict related issues, relaxation training, forms of targeting, solving strategies, cognitive restructuring and personal change processes. The experience shows, that conflict coaching can be very well practised in a group setting.