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.     

Causes of ambiguity aversion: Known versus unknown preferences

Ambiguity aversion appears to have subtle psychological causes. Curley, Yates, and Abrams found that the fear of negative evaluation by others (FNE) increases ambiguity aversion. This paper introduces a design in which preferences can be private information of individuals, so that FNE can be avoided entirely. Thus, we can completely control for FNE and other social factors, and can determine exactly to what extent ambiguity aversion is driven by such social factors. In our experiment ambiguity aversion, while appearing as commonly found in the presence of FNE, disappears entirely if FNE is eliminated. Implications are discussed.      

Non‐linear Effects of Comparison Income in Quit Decisions: Status versus Signal!

This research note utilizes German matched employer–employee data to investigate the relationship between mobility and relative wage positions within establishments for workers without university degrees. The main innovation involves the examination of non‐linear effects, because previous literature mainly analyses mean linear effects. Our random‐effects probit estimates of mobility suggest a non‐linear U‐shaped effect with respect to relative standing. This is plausible because workers in low relative wage positions might quit because of their low status and those in high relative wage positions because of their low career advancement opportunities. Consideration of non‐linearities, thus, is a major improvement for the analysis of the effects of relative wage positions.     

Eigenverantwortung — Berufliche Leistung und Anforderung

Ohne Zusammenfassung     

Asymptotic Representations of the Multivariate Empirical Distribution Function and Applications

Often, many complicated statistics used as estimators or test statistics take the form of the (multivariate) empirical distribution function evaluated at a random vector (V_n). Denote such statistics by S_n. This paper describes methods for the study of various asymptotic properties of S_n. First, under minimal assumptions, a weak asymptotic representation for S_n is derived. This result may be used to show the asymptotic normality of S_n. Second, under slightly more stringent regularity conditions, an almost sure representation of S_n, with suitable order (as.) of the remainder term is studied and then a law of the iterated logarithm for S_n, is derived. In this context, strong convergence results from a sequential point of view are also studied. Finally, weak convergence to a Brownian motion process is established. As an application, we show the limiting normality of S_n, for a random number of summands.     

Die Supervision auf dem Weg zur Profession? Professionalisierung im Spannungsfeld zwischen Expansionsbestrebung und Selbstbescheidung

In contrast to the general trend of deprofessionalization, supervision has established some criteria for professions during the last twenty years: wide ranges of quality standards, standardized educational programs, professional ethics etc. This development toward this trend needs explanation. It is argued, that the approach of the development of profession could be successful, because supervision became a successful “parasite” of its “host” social work. The introduction of supervision in social work, however, was responsible for the introduction of coaching as a new profession in the area of organizational consulting. The question is which effects the expansion of supervision towards team and organizational development will have on the establishing of its further professionalization. There appears to be some tendencies toward the idea that supervision will become a part of the development of professionalization as the “perfect nanny of organizations”.     

A tractable model of process fairness under risk

This paper proposes a social utility model of individual preferences for process fairness that complements the Fehr–Schmidt model for outcome fairness. The model assumes that the outcome generating process rather than the actual outcomes influences fairness perceptions, and that process fairness is evaluated through comparison of expected payoffs. The process model successfully predicts data from bargaining games involving risky payoffs that neither outcome-based nor reciprocity models can explain. In a theoretical application, Machina’s parental example for non-expected utility in a distributional problem (Machina’s Mom) is analyzed by incorporating individual level process fairness preferences under expected utility.