Online distributed learning in wind power forecasting

Forecasting wind power generation up to a few hours ahead is of the utmost importance for the efficient operation of power systems and for participation in electricity markets. Recent statistical learning approaches exploit spatiotemporal dependence patterns among neighbouring sites, but their requirement of sharing confidential data with third parties may limit their use in practice. This explains the recent interest in distributed, privacy preserving algorithms for high-dimensional statistical learning, e.g. with auto-regressive models. The few approaches that have been proposed are based on batch learning. However, these approaches are potentially computationally expensive and do not allow for the accommodation of nonstationary characteristics of stochastic processes like wind power generation. This paper closes the gap between online and distributed optimisation by presenting two novel approaches that recursively update model parameters while limiting information exchange between wind farm operators and other potential data providers. A simulation study compared the convergence and tracking ability of both approaches. In addition, a case study using a large dataset from 311 wind farms in Denmark confirmed that online distributed approaches generally outperform existing batch approaches while preserving privacy such that agents do not have to actively share their private data.     

Using Panel Data on Income Satisfaction to Estimate Equivalence Scale Elasticity

In this paper, the equivalence scale elasticity will be estimated by using individual panel data on income satisfaction from the German Socio-Economic Panel Study (GSOEP). Satisfaction or happiness data have been more frequently used by economists in recent years to analyze individual well-being. The approach differs from other subjective approaches as respondents are requested to evaluate current income rather than income in hypothetical situations. The estimated scale elasticity is higher compared to those from other subjective approaches based on German data. In addition, panel data enable different scale use by the respondents to be controlled. It can be shown that elasticity decreases when unobserved fixed-effects are controlled for.     

A review of integrated QCA and statistical analyses

Systematically combining quantitative and qualitative research approaches offers the potential for a more comprehensive and nuanced understanding of social scientific phenomena. With their strong opportunities for building, qualifying, and testing social scientific theories, methodological integrations thus enable researchers to make substantive contributions that would not have been possible with one method alone. In this article we demonstrate how the integration of Qualitative Comparative Analysis (QCA) and conventional statistical analysis offers researchers new opportunities for contributing to the social sciences. Whereas statistical analysis is variable-oriented and relies on correlational analysis to make comparisons across cases, QCA is based on set theory, is case oriented, and relies on Boolean algebra to make comparisons between cases. Drawing on the literature on the interdependency between theoretical contribution and methodology, we review studies that integrate QCA and statistical analysis to explain how the specific combination of these two approaches allows researchers to strengthen the theoretical contribution of their research. From our review we identify common challenges and provide solutions for integrating QCA and statistical analysis.     

Antitrust Compliance: Managerial Incentives and Collusive Behavior

This article analyzes a manager's incentives to establish and sustain an illegal collusive agreement if her firm is subject to profit shocks, if her utility function is concave in profits (e.g., because of risk aversion), and if she incurs opportunity costs (e.g., by violating a social norm). The model supports the empirical observation that if collusion is to be established and sustained in a state with low profits, then this state must be quite persistent. It also indicates that compliance with antitrust laws can be ensured best by combining a zero tolerance policy with a strategy of forgiveness. Copyright © 2017 John Wiley & Sons, Ltd.     

The Value‐relevance of Equity Accounted Carrying Amounts and Disclosed Fair Values of Listed Associates

Equity accounting is a controversial accounting treatment. Although fair value measurement represents a potential alternative measurement base, information content may be lost under a pure fair value measurement approach. This study investigates the value‐relevance of equity accounted carrying amounts and disclosed fair values of listed associates, using a sample of the largest firms listed in South Africa, Australia and the UK. The main finding is that the alternative measurement bases are incrementally value‐relevant during the sample period of 31 December 2005 to 31 December 2011, implying that equity investors do not blindly accept either measurement base. Rather, investors include their own assessment of the intrinsic value of an entity's listed associates in their valuations.     

Regelgebundene Fiskalpolitik und Schuldenkommissionen

Die Staatsschuldenkrise im Euroraum kann kurzfristig nicht gel?st werden: Die finanzielle Unterstützung für die Schuldnerstaaten reicht nicht aus, deren Austerit?tsprogramme wirken zu restriktiv und die Mitgliedsl?nder sind nicht bereit, auf Fiskalkompetenz zu verzichten. Die Autoren stellen hier ein Konzept vor, das zu h?heren sWachstumsraten und niedrigeren Schuldenquoten in den betroffenen L?ndern führt.     

Within-person variation in affective commitment to teams: Where it comes from and why it matters

Teamwork is crucial to organizational success and commitment to teams is an important predictor of team-related behaviors. However, theorists and researchers have typically assumed that commitment levels are generally stable within-persons, increasing or decreasing as a result of substantial organizational changes. This position is at odds with the evidence of systematic and regular intraindividual fluctuations in personal attributes and workplace behaviors. We draw upon affective events theory to present a model explaining how certain events and dispositions produce vacillations in affective reactions which, in turn, are likely to create within-person variation in affective commitment to teams (WPVC_teams). We further propose that WPVC_teams enhances prediction and explanation of intraindividual fluctuations in work behavior and, interindividually, moderates the relationship between level of commitment and behavior.