A macroeconomic potential describing structural change of the economy

For the purpose of describing change in an economy's structure, and addressing issues of transformation, the notion of a time-dependent macroeconomic potential function is introduced. It penalizes deviations from equilibrium (entrepreneurial error) and induces moves toward equilibrium. Thus, from the concept of a potential function is derived the concept of short-term and long-term change forces. We focus here on the long-term structural changes of an economy as distinct from short-term cyclical variations, and we represent economic transformations as phase-transitions between monostable and ambiguous bistable states of the economy. One important feature of the potential function approach is that the parameter of the potential can be determined from empirical data. In particular, the parameters can be regressed for input variables. Hence, a relationship has been established between the structural change force and a set of input variables, some of which are controlled in part by either public or private sector agents. The method has been applied to West German and United States industry data for 1950–1980.     

‘You Are Germany’– ‘I Am Australian’: The construction of national unity through diversity in select examples from Australia and Germany

This article explores the construction of national unity through diversity by analysing two case studies from Germany and Australia: the television campaign ‘You Are Germany’ and the song ‘I Am Australian’. It places both examples in a broader context of forging national unity through diversity and argues that diversity has occasionally been hijacked as a nationalist argument to advance national identity and unity. This study explores the different aspects of diversity appearing in both cases under study, identifies those parts of diversity being excluded and asks how national unity is being forged through recourse to diversity.     

Stochastic orders and non-Gaussian risk factor models

The main results of this paper are monotonicity statements about the risk measures value-at-risk (VaR) and tail value-at-risk (TVaR) with respect to the parameters of single and multi risk factor models, which are standard models for the quantification of credit and insurance risk. In the context of single risk factor models, non-Gaussian distributed latent risk factors are allowed. It is shown that the TVaR increases with increasing claim amounts, probabilities of claims and correlations, whereas the VaR is in general not monotone in the correlation parameters. To compare the aggregated risks arising from single and multi risk factor models, the usual stochastic order and the increasing convex order are used in this paper, since these stochastic orders can be interpreted as being induced by the VaR-concept and the TVaR-concept, respectively. To derive monotonicity statements about these risk measures, properties of several further stochastic orders are used and their relation to the usual stochastic order and to the increasing convex order are applied.     

Modelling method effects as individual causal effects

Summary.  Method effects often occur when different methods are used for measuring the same construct. We present a new approach for modelling this kind of phenomenon, consisting of a definition of method effects and a first model, the method effect model , that can be used for data analysis. This model may be applied to multitrait–multimethod data or to longitudinal data where the same construct is measured with at least two methods at all occasions. In this new approach, the definition of the method effects is based on the theory of individual causal effects by Neyman and Rubin. Method effects are accordingly conceptualized as the individual effects of applying measurement method j instead of k . They are modelled as latent difference scores in structural equation models. A reference method needs to be chosen against which all other methods are compared. The model fit is invariant to the choice of the reference method. The model allows the estimation of the average of the individual method effects, their variance, their correlation with the traits (and other latent variables) and the correlation of different method effects among each other. Furthermore, since the definition of the method effects is in line with the theory of causality, the method effects may (under certain conditions) be interpreted as causal effects of the method. The method effect model is compared with traditional multitrait–multimethod models. An example illustrates the application of the model to longitudinal data analysing the effect of negatively (such as 'feel bad') as compared with positively formulated items (such as 'feel good') measuring mood states.     

Beliefs About Affirmative Action and Diversity and Their Relationship to Support for Hiring Policies

Two hundred seventy-three White undergraduates participated in an investigation of how beliefs relate to support for affirmative action (AA) policies. Beliefs included belief in the fairness of AA, belief in merit, and belief in the value of diversity. Analyses predicted support for a general affirmative action policy, a tiebreak policy, and a policy using banding from beliefs and individual-level variables such as future benefit from AA and demographics. For the general policy, each belief predicted support for AA. Fairness and value of diversity predicted support for a tiebreak policy. Value of diversity predicted support for aptitude testing. Individual characteristics improved prediction for AA in general but not for tiebreak policy or aptitude testing. We discuss predictions and results in terms of procedural and distributive justice, fairness heuristic theory, and models of support for AA.     

Statusgefälle und Intragruppenprozesse in Schülerarbeitsgruppen

The study investigates group status and group processes between students working in small groups in the classroom. 40 lessons of ten teachers were observed and videotaped. It can be shown that there is a different status and leadership behaviour between the members of the groups but very interesting, there is no ?free rider“ effect. Status differences are not a constant phenomenon on over different lessons and they are not important for good results at the end of group work but sensitive for the leadership practiced in group work. Between the group processes and the results there are specific relationships. Implications for managing group work are discussed.