The combination of forecasts in the trading of electricity from renewable energy sources

The legal support provided by the ‘Act on Granting Priority to Renewable Energy Sources’ (German Erneuerbare Energien Gesetz, EEG) and its precursor has in the last 20 years led to a marked growth in Germany in the use of renewable energies to generate electricity. As a result of the EEG amendment adopted in the summer of 2011 and in force since 1 January 2012, the market integration of electricity generated from renewable energy sources (RES-E) has become more important. Consequently, the economic importance of trading RES-E has also increased. A major role in determining costs in trading electricity from wind and solar energy on the wholesale markets plays the forecasting method used. If a forecast inaccurately predicts the amount of electricity actually generated, one result could be elevated costs in the trading process. In the beginning of this article we introduce the legal framework governing the trading of RES-E. Subsequently, we present a method for combining several individual forecasting methods. Finally, using empirical data, we show that in comparison to the best available individual forecast, the proposed combined forecast results in a clear improvement of forecasting quality as well as in a reduction in trading costs.     

Further specification of the leader political skill–leadership effectiveness relationships: Transformational and transactional leader behavior as mediators

The present investigation was a three-source test of the intermediate linkages in the leader political skill–leader effectiveness and follower satisfaction relationships, which examined transformational and transactional (i.e., contingent reward behavior) leader behavior as mediators. Data from 408 leaders (headmasters) and 1429 followers (teachers) of state schools in the western part of Germany participated in this research. The results of mediation analyses, based on bias-corrected bootstrapping confidence intervals, provided support for the hypotheses that political skill predicts both transformational and transactional leader behavior, beyond other established predictors, and that transformational and transactional leader behavior mediate the relationships between leader political skill and leadership effectiveness. The contributions to theory and research, strengths and limitations, directions for future research, and practical implications are discussed.     

Nonlinear structural equation modeling: is partial least squares an alternative?

Nonlinear structural equation modeling provides many advantages over analyses based on manifest variables only. Several approaches for the analysis of latent interaction effects have been developed within the last 15 years, including the partial least squares product indicator approach (PLS-PI), the constrained product indicator approach using the LISREL software (LISREL-PI), and the distribution-analytic latent moderated structural equations approach (LMS) using the Mplus program. An assumed advantage of PLS-PI is that it is able to deal with very large numbers of indicators, while LISREL-PI and LMS have not been investigated under such conditions. In a Monte Carlo study, the performance of LISREL-PI and LMS was compared to PLS-PI results previously reported in Chin et al. (2003) and Goodhue et al. (2007) for identical conditions. The latent interaction model included six indicator variables for the measurement of each latent predictor variable and the latent criterion, and sample size was N=100. The results showed that PLS-PI’s linear and interaction parameter estimates were downward biased, while parameter estimates were unbiased for LISREL-PI and LMS. True standard errors were smallest for PLS-PI, while the power to detect the latent interaction effect was higher for LISREL-PI and LMS. Compared to the symmetric distributions of interaction parameter estimates for LISREL-PI and LMS, PLS-PI showed a distribution that was symmetric for positive values, but included outlying negative estimates. Possible explanations for these findings are discussed.     

Higher Education Policy,Enrollment, and Income Inequality*

Objective. The objective of this article is to examine whether public expenditure on higher education has an effect on income inequality by increasing enrollment. Methods. Combining data from the World Bank Development Indicators with data from the World Income Inequality Database version 2, we study the relation between government education expenditure and enrollment rates, as well as the relation between government education expenditure and the change in income inequality during the 1980s and the 1990s. Results. We find that public expenditure on higher education has no positive effect on enrollment. Increased enrollment is mainly explained by higher GDP per capita. Using carefully selected Gini coefficients to ensure comparability over time, we do not find a robust relation between higher education expenditure and lower income inequality, contrary to some previous studies. Conclusions. Government expenditure on higher education has very limited effects on enrollment and inequality. This finding, however, does not imply that there are no social benefits from such subsidies. For example, in countries where high marginal tax rates decrease the economic returns to education, governments may wish to compensate for this through subsidies.     

Ethnic Prejudice and Discrimination in Europe

This article provides an introduction to research on European prejudice and discrimination. First, we list the distinctive characteristics of a European perspective and provide a short sketch of European immigration and ethnic groups. Europe has become a multicultural community. Nevertheless, public opinion and the continent's politics often do not reflect this empirical fact. Prejudice and discrimination directed at immigrants are a widespread phenomena across Europe. Several cross-European surveys support this conclusion, although theoretically driven surveys on prejudice and discrimination in Europe remain rare. Cross-European research studies classical and modern theories of prejudice and discrimination and attempts to uncover the psychological mechanisms that explain individual readiness to exclude ethnic groups. A brief sketch of recent European research is presented. This issue offers both important cross-national perspectives as well as needed comparisons with the more studied case of racial prejudice and discrimination in the United States.     

Global Environmental Change and Historical Transitions

What do transition processes in rural areas in Thailand, biomass consumption in nineteenth-century Austria and the ecology of hunter-gatherers have to do with the appropriation of plant production and global environmental change? More than one might think of in the first place. They are part of a scholarly discourse on our changing relations with the environment. We argue that global change can be analysed in terms of transitions between major modes of subsistence and try to document this with several case studies.     

On predictive distributions and Bayesian networks

In this paper we are interested in discrete prediction problems for a decision-theoretic setting, where the task is to compute the predictive distribution for a finite set of possible alternatives. This question is first addressed in a general Bayesian framework, where we consider a set of probability distributions defined by some parametric model class. Given a prior distribution on the model parameters and a set of sample data, one possible approach for determining a predictive distribution is to fix the parameters to the instantiation with the maximum a posteriori probability. A more accurate predictive distribution can be obtained by computing the evidence (marginal likelihood), i.e., the integral over all the individual parameter instantiations. As an alternative to these two approaches, we demonstrate how to use Rissanen's new definition of stochastic complexity for determining predictive distributions, and show how the evidence predictive distribution with Jeffrey's prior approaches the new stochastic complexity predictive distribution in the limit with increasing amount of sample data. To compare the alternative approaches in practice, each of the predictive distributions discussed is instantiated in the Bayesian network model family case. In particular, to determine Jeffrey's prior for this model family, we show how to compute the (expected) Fisher information matrix for a fixed but arbitrary Bayesian network structure. In the empirical part of the paper the predictive distributions are compared by using the simple tree-structured Naive Bayes model, which is used in the experiments for computational reasons. The experimentation with several public domain classification datasets suggest that the evidence approach produces the most accurate predictions in the log-score sense. The evidence-based methods are also quite robust in the sense that they predict surprisingly well even when only a small fraction of the full training set is used.     

Intensity, timeliness, and success of incumbent response to technological discontinuities: a synthesis and empirical investigation

The extant literature highlights numerous different factors influencing the timeliness and intensity of incumbent response to discontinuous technological change. However, this literature has so far not been synthesized and is therefore limited in its analytical, predictive, and normative power. We develop a comprehensive model of incumbent response that organizes different explanatory factors into the three distinct dimensions of (1) identification and interpretation, (2) decision making, and (3) organizational implementation. We also conceptualize how response intensity and timeliness affect business performance in new technological domains. We test the model against data from 320 firms from the German dental lab industry, finding substantial support for the majority of our hypotheses. This study offers unique empirical insight in observing that cognitive constructs such as framing and management flexibility have the strongest impact on both intensity and timeliness of incumbent response to technological, and thus, strategic discontinuities. Together, our findings have important implications for both theory and practice.     

How to ask sensitive multiple-choice questions

Motivated by recent failures of polling to estimate populist party support, we propose and analyze two methods for asking sensitive multiple-choice questions where the respondent retains some privacy and therefore might answer more truthfully. The first method consists of asking for the true choice along with a choice picked at random. The other method presents a list of choices and asks whether the preferred one is on the list or not. Different respondents are shown different lists. The methods are easy to explain, which makes it likely that the respondent understands how her privacy is protected and may thus entice her to participate in the survey and answer truthfully. The methods are also easy to implement and scale up.     

Modelling columnarity of pyramidal cells in the human cerebral cortex

For modelling the location of pyramidal cells in the human cerebral cortex, we suggest a hierarchical point process in that exhibits anisotropy in the form of cylinders extending along the z-axis. The model consists first of a generalised shot noise Cox process for the xy-coordinates, providing cylindrical clusters, and next of a Markov random field model for the z-coordinates conditioned on the xy-coordinates, providing either repulsion, aggregation or both within specified areas of interaction. Several cases of these hierarchical point processes are fitted to two pyramidal cell data sets, and of these a final model allowing for both repulsion and attraction between the points seem adequate. We discuss how the final model relates to the so-called minicolumn hypothesis in neuroscience.