A new approach for disclosure control in the IAB establishment panel—multiple imputation for a better data access

For micro-datasets considered for release as scientific or public use files, statistical agencies have to face the dilemma of guaranteeing the confidentiality of survey respondents on the one hand and offering sufficiently detailed data on the other hand. For that reason, a variety of methods to guarantee disclosure control is discussed in the literature. In this paper, we present an application of Rubin’s (J. Off. Stat. 9, 462–468, 1993) idea to generate synthetic datasets from existing confidential survey data for public release.We use a set of variables from the 1997 wave of the German IAB Establishment Panel and evaluate the quality of the approach by comparing results from an analysis by Zwick (Ger. Econ. Rev. 6(2), 155–184, 2005) with the original data with the results we achieve for the same analysis run on the dataset after the imputation procedure. The comparison shows that valid inferences can be obtained using the synthetic datasets in this context, while confidentiality is guaranteed for the survey participants.     

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.     

The multiple faces of tension: dualities in decision-making

Review of Managerial Science - In making decisions about strategic and operational actions, managers commonly need to consider dualities such as long-term versus short-term, innovation versus...     

Moody habitus: Bourdieu with existential feelings

This paper proposes a way of integrating the concepts of habitus and mood. The purpose of this conceptual move is to enrich Pierre Bourdieu's treatment of habitus with a better recognition of its affective aspects. The paper draws on phenomenological studies of psychic disorders and applies the concept of existential feeling to specify what moods are and do. The framing proposed distinguishes between dispositions that function in the foreground and in the background of habitus. Thereby it is possible to regard moods as background dispositions of habitus. This paper also discusses what this idea of moody habitus can do for research in habitus and human practice.     

Testing for autocorrelation among common stock returns

We consider the null distribution of autocorrelation coefficients for stock returns when the variance of the returns is infinite. We show that the empirical autocorrelations then tend to zero faster than in the standard case and that they tend, after suitable normalisation, in distribution to a rather complicated nonnormal law. An empirical application to the 14 most busy German stocks reveals that the significance of observed correlations is thereby in general reduced.     

The demographic effect of mixed marriages

This paper gives a formal expression for the demographic effect of mixed marriages; i.e., the effect on the number of children, and thereafter illustrates the long-term effects of these marriages with a simple simulation model     

He is a Firm,Strong‐Minded and Empowering Leader,but is She? Gendered Positioning of Female and Male CEOs

The article focuses on how management and gender are done in written stories about female and male chief executive officers (CEOs). The stories were written by young Finnish business school students. The logic for studying stories written by students lies in the argument that the new generation will not reproduce common stereotypes about soft, democratic and caring female managers and hard, authoritarian and strong male managers. In the analysis, we rely on positioning theory, which focuses on how the CEOs are discursively positioned, that is, what kinds of roles and duties they are assigned and how their positions shift as the story unfolds. The analysis shows that while there is little difference in the rights and duties assigned to the CEOs, the positioning of female and male CEOs construct a very different picture of their abilities as business managers and leaders of people. The female CEOs are depicted as successful business managers but lacking in interpersonal skills. The male CEOs are also successful business managers but they are constructed as naturally competent leaders of people. This finding is linked to the Finnish management context as well as to the institutionalized leadership and management discourses.     

Mortality inequality in two native population groups

A sample of people aged 40–67 years, taken from a longitudinal register compiled by Statistics Finland, is used to analyse mortality differences between Swedish speakers and Finnish speakers in Finland. Finnish speakers are known to have higher death rates than Swedish speakers. The purpose is to explore whether labour-market experience and partnership status, treated as proxies for measures of variation in health-related characteristics, are related to the mortality differential. Persons who are single, disability pensioners, and those having experienced unemployment are found to have substantially higher death rates than those with a partner and employed persons. Swedish speakers have a more favourable distribution on both variables, which thus notably helps to reduce the Finnish–Swedish mortality gradient. A conclusion from this study is that future analyses on the topic should focus on mechanisms that bring a greater proportion of Finnish speakers into the groups with poor health or supposed unhealthy behaviour.