Rényi entropy of m-generalized order statistics

Abstract

Characterizing relations via Rényi entropy of m-generalized order statistics are considered along with examples and related stochastic orderings. Previous results for common order statistics are included.     

The neglected mediating role of self-efficacy in the goal setting process in local public administrations

To analyse the role of self-efficacy in goal setting in public administrations, this study combines goal-setting theory, public service motivation literature and cognitive theory. Using partial least squares structural equation modelling (PLS-SEM), survey data from 105 German civil servants are analysed. The results underline the role of goal setting (represented by goal difficulty and specificity) in determining the self-efficacy of public servants. Public service motivation and goal specificity both increase public servants’ work performance; however, the effects of goal difficulty are negatively mediated by the employee’s self-efficacy. That finding reflects the central role of self-efficacy, which should not be ignored in the goal-setting processes of public administrations.     

A Probabilistic Framework for Risk Analysis of Widespread Flood Events: A Proof‐of‐Concept Study

This article presents a flood risk analysis model that considers the spatially heterogeneous nature of flood events. The basic concept of this approach is to generate a large sample of flood events that can be regarded as temporal extrapolation of flood events. These are combined with cumulative flood impact indicators, such as building damages, to finally derive time series of damages for risk estimation. Therefore, a multivariate modeling procedure that is able to take into account the spatial characteristics of flooding, the regionalization method top‐kriging, and three different impact indicators are combined in a model chain. Eventually, the expected annual flood impact (e.g., expected annual damages) and the flood impact associated with a low probability of occurrence are determined for a study area. The risk model has the potential to augment the understanding of flood risk in a region and thereby contribute to enhanced risk management of, for example, risk analysts and policymakers or insurance companies. The modeling framework was successfully applied in a proof‐of‐concept exercise in Vorarlberg (Austria). The results of the case study show that risk analysis has to be based on spatially heterogeneous flood events in order to estimate flood risk adequately.     

Beyond tail median and conditional tail expectation: Extreme risk estimation using tail Lp-optimization

The conditional tail expectation (CTE) is an indicator of tail behavior that takes into account both the frequency and magnitude of a tail event. However, the asymptotic normality of its empirical estimator requires that the underlying distribution possess a finite variance; this can be a strong restriction in actuarial and financial applications. A valuable alternative is the median shortfall (MS), although it only gives information about the frequency of a tail event. We construct a class of tail L^p-medians encompassing the MS and CTE. For p in (1,2), a tail L^p-median depends on both the frequency and magnitude of tail events, and its empirical estimator is, within the range of the data, asymptotically normal under a condition weaker than a finite variance. We extrapolate this estimator and another technique to extreme levels using the heavy-tailed framework. The estimators are showcased on a simulation study and on real fire insurance data.     

The identification of logistic regression models with errors in the variables

The simple logistic regression model with normal measurement error and normal regressor is shown to be identifiable without any extra information about the measurement error. The multiple logistic regression model with more than one regressor variable measured with error is not identifiable. If the covariance matrix of the measurement error is known up to a scalar factor, the model is identified. Further we discuss why in spite of the identifiability the models cannot be estimated in a reasonable way without extra information about the measurement error.     

Einstellungen zur sozialen Mindestsicherung

Within the debate about the future of the welfare state a guaranteed social minimum income is often discussed as an alternative to the current social security system. One objection to such a proposal argues that a social minimum income lacks social acceptance and normative recognition. Starting from the thesis that the standard instruments of survey research have little to offer for giving a detailed account of the attitudes towards a social minimum, we deploy the more complex method of Factorial Survey Design. The study sample consists of 121 employed persons. Within the study, the focus is on the criteria used and the differentiations made when people are asked to evaluate a just minimum income. It can be shown that a uniform and flat-rate social minimum possesses less legitimacy than a transfer system that differentiates entitlements according to the beneficiaries relation to the employment sphere and certain need criteria. In addition, we find support for the idea of low income subsidies as suggested by the negative income concept. Though the results give evidence of the normative attraction of a social minimum, it is also apparent that the social judgments of the respondents are influenced by in the normative principles of the existing social security arrangements.     

On social work and what gender has got to do with it

Living in gendered societies makes it necessary to take into account the specific ways in which social problems and social issues affect the lives of women and men, girls and boys. Not only are social problems and social issues very often gender biased; this is also true for the professions dealing with these problems and issues, and for the training programmes for professions like social work. Sociological analysis of society and philosophical understanding of a good life are permeated by gender-specific perceptions -- often without those involved being aware of them. Furthermore, social policies reinforce gender-specific biases because they are based on gender-specific (i.e. male) standards. Gender as an analytical category has been brought into scientific and public discourse by feminist theoreticians and activists making women -- and thus also men -- visible with regard to structure and subject issues. The development of gender theory and research highlights the significance of gender arrangements to understand social phenomena and to support gender-equality ways of thinking and policies. At the same time, men and women are not only confronted with gendered structures, but via socialization processes and personal development they also reproduce these gender differences in their daily lives by 'doing gender'.