Der Hawthorne-Effekt – ein Effekt für viele Gelegenheiten?

It is shown that the concept of ?Hawthorne effect‘ was created many years after the Hawthorne studies in Western Electric Company. Presently, the ?Hawthorne effect‘ concept is increasingly used in social sciences and many other sciences. The concept is however used in different and occasionally digressive meanings. The question arises whether such a concept is useful at all. In addition, it is discussed why the rather imprecise reports of single Hawthorne field experiments have been spread as academic folklore, and why rather undefined concepts like the ?Hawthorne effect‘ are used so widely in psychology and social sciences.     

A Comparative Study of Segregation Patterns in Belgium,Denmark, the Netherlands and Sweden: Neighbourhood Concentration and Representation of Non-European Migrants

In this paper, we use geo-coded, individual-level register data on four European countries to compute comparative measures of segregation that are independent of existing geographical sub-divisions. The focus is on non-European migrants, for whom aggregates of egocentric neighbourhoods (with different population counts) are used to assess small-scale, medium-scale, and large-scale segregation patterns. At the smallest scale level, corresponding to neighbourhoods with 200 persons, patterns of over- and under-representation are strikingly similar. At larger-scale levels, Belgium stands out as having relatively strong over- and under-representation. More than 55% of the Belgian population lives in large-scale neighbourhoods with moderate under- or over-representation of non-European migrants. In the other countries, the corresponding figures are between 30 and 40%. Possible explanations for the variation across countries are differences in housing policies and refugee placement policies. Sweden has the largest and Denmark the smallest non-European migrant population, in relative terms. Thus, in both migrant-dense and native-born-dense areas, Swedish neighbourhoods have a higher concentration and Denmark a lower concentration of non-European migrants than the other countries. For large-scale, migrant-dense neighbourhoods, however, levels of concentration are similar in Belgium, the Netherlands, and Sweden. Thus, to the extent that such concentrations contribute to spatial inequalities, these countries are facing similar policy challenges.     

“Know What to Do If You Encounter a Flash Flood”: Mental Models Analysis for Improving Flash Flood Risk Communication and Public Decision Making

Understanding how people view flash flood risks can help improve risk communication, ultimately improving outcomes. This article analyzes data from 26 mental models interviews about flash floods with members of the public in Boulder, Colorado, to understand their perspectives on flash flood risks and mitigation. The analysis includes a comparison between public and professional perspectives by referencing a companion mental models study of Boulder‐area professionals. A mental models approach can help to diagnose what people already know about flash flood risks and responses, as well as any critical gaps in their knowledge that might be addressed through improved risk communication. A few public interviewees mentioned most of the key concepts discussed by professionals as important for flash flood warning decision making. However, most interviewees exhibited some incomplete understandings and misconceptions about aspects of flash flood development and exposure, effects, or mitigation that may lead to ineffective warning decisions when a flash flood threatens. These include important misunderstandings about the rapid evolution of flash floods, the speed of water in flash floods, the locations and times that pose the greatest flash flood risk in Boulder, the value of situational awareness and environmental cues, and the most appropriate responses when a flash flood threatens. The findings point to recommendations for ways to improve risk communication, over the long term and when an event threatens, to help people quickly recognize and understand threats, obtain needed information, and make informed decisions in complex, rapidly evolving extreme weather events such as flash floods.     

Robust bootstrap forecast densities for GARCH returns and volatilities

Bootstrap procedures are useful to obtain forecast densities for both returns and volatilities in the context of generalized autoregressive conditional heteroscedasticity models. In this paper, we analyse the effect of additive outliers on the finite sample properties of these bootstrap densities and show that, when obtained using maximum likelihood estimates of the parameters and standard filters for the volatilities, they are badly affected with dramatic consequences on the estimation of Value-at-Risk. We propose constructing bootstrap densities for returns and volatilities using a robust parameter estimator based on variance targeting implemented together with an adequate modification of the volatility filter. We show that the performance of the proposed procedure is adequate when compared with available robust alternatives. The results are illustrated with both simulated and real data.     

Urban and agricultural soils: conflicts and trade-offs in the optimization of ecosystem services

On-going human population growth and changing patterns of resource consumption are increasing global demand for ecosystem services, many of which are provided by soils. Some of these ecosystem services are linearly related to the surface area of pervious soil, whereas others show non-linear relationships, making ecosystem service optimization a complex task. As limited land availability creates conflicting demands among various types of land use, a central challenge is how to weigh these conflicting interests and how to achieve the best solutions possible from a perspective of sustainable societal development. These conflicting interests become most apparent in soils that are the most heavily used by humans for specific purposes: urban soils used for green spaces, housing, and other infrastructure and agricultural soils for producing food, fibres and biofuels. We argue that, despite their seemingly divergent uses of land, agricultural and urban soils share common features with regards to interactions between ecosystem services, and that the trade-offs associated with decision-making, while scale- and context-dependent, can be surprisingly similar between the two systems. We propose that the trade-offs within land use types and their soil-related ecosystems services are often disproportional, and quantifying these will enable ecologists and soil scientists to help policy makers optimizing management decisions when confronted with demands for multiple services under limited land availability.     

Bayesian unit-root tests for Stochastic Volatility models

In this article, we consider Bayesian inference procedures to test for a unit root in Stochastic Volatility (SV) models. Unit-root tests for the persistence parameter of the SV models, based on the Bayes Factor (BF), have been recently introduced in the literature. In contrast, we propose a flexible class of priors that is non-informative over the entire support of the persistence parameter (including the non-stationarity region). In addition, we show that our model fitting procedure is computationally efficient (using the software WinBUGS). Finally, we show that our proposed test procedures have good frequentist properties in terms of achieving high statistical power, while maintaining low total error rates. We illustrate the above features of our method by extensive simulation studies, followed by an application to a real data set on exchange rates.     

Tests of fit for normal inverse Gaussian distributions

Goodness-of-fit tests for the family of symmetric normal inverse Gaussian distributions are constructed. The tests are based on a weighted integral incorporating the empirical characteristic function of suitably standardized data. An EM-type algorithm is employed for the estimation of the parameters involved in the test statistic. Monte Carlo results show that the new procedure is competitive with classical goodness-of-fit methods. An application with financial data is also included.