Coordination Tasks and Negotiation Modes of Linked Lives in Entrepreneurial Families

The overlap of business and family roles, and how they are linked in entrepreneurial families, requires intergenerational negotiation. Biographical case reconstruction analysis of 32 narrative interviews of 12 German entrepreneurial families explores what coordination tasks need to be resolved and how family members negotiate their interlocking lives. The article finds that entrepreneurial families actively coordinate positions, life phases, and material transfers by means of a pedagogy of succession, life course evidence analysis, and entrepreneurial narratives. The article presents two innovations. First, it demonstrates how these families experience and cope with their linked lives under flexible working conditions and in multigenerational families. Second, it argues that research on linked lives should shift from focusing on outcomes to understanding emergence and operations, and it advances the use of the biographical case reconstruction method for this endeavor.     

Tests on asymmetry for ordered categorical variables

Skewness is a well-established statistical concept for continuous and, to a lesser extent, for discrete quantitative statistical variables. However, for ordered categorical variables, limited literature concerning skewness exists, although this type of variables is common for behavioral, educational, and social sciences. Suitable measures of skewness for ordered categorical variables have to be invariant with respect to the group of strictly increasing, continuous transformations. Therefore, they have to depend on the corresponding maximal-invariants. Based on these maximal-invariants, we propose a new class of skewness functionals, show that members of this class preserve a suitable ordering of skewness and derive the asymptotic distribution of the corresponding skewness statistic. Finally, we show the good power behavior of the corresponding skewness tests and illustrate these tests by applying real data examples.     

Effect of Berkson measurement error on parameter estimates in Cox regression models

We study the effect of additive and multiplicative Berkson measurement error in Cox proportional hazard model. By plotting the true and the observed survivor function and the true and the observed hazard function dependent on the exposure one can get ideas about the effect of this type of error on the estimation of the slope parameter corresponding to the variable measured with error. As an example, we analyze the measurement error in the situation of the German Uranium Miners Cohort Study both with graphical methods and with a simulation study. We do not see a substantial bias in the presence of small measurement error and in the rare disease case. Even the effect of a Berkson measurement error with high variance, which is not unrealistic in our example, is a negligible attenuation of the observed effect. However, this effect is more pronounced for multiplicative measurement error.     

Keep it simple: estimation strategies for ordered response models with fixed effects

By running Monte Carlo simulations, we compare different estimation strategies of ordered response models in the presence of non-random unobserved heterogeneity. We find that very simple binary recoding schemes deliver parameter estimates with very low bias and high efficiency. Furthermore, if the researcher is interested in the relative size of parameters the simple linear fixed effects model is the method of choice.     

Power kurtosis transformations: Definition, properties and ordering

Summary Heavy tail distributions can be generated by applying specific non-linear transformations to a Gaussian random variable. Within this work we introduce power kurtosis transformations which are essentially determined by their generator function. Examples are theH-transformation of Tukey (1960), theK-transformation of MacGillivray and Cannon (1997) and theJ-transformation of Fischer and Klein (2004).Furthermore, we derive a general condition on the generator function which guarantees that the corresponding transformation is actually tail-increasing. In this case the exponent of the power kurtosis transformation can be interpreted as a kurtosis parameter. We also prove that the transformed distributions can be ordered with respect to the partial ordering of van Zwet (1964) for symmetric distributions.     

Gamblers’ Habits: Empirical Evidence on the Behavior of Regulars, Newcomers and Dropouts

Electronic gambling offers the opportunity to analyze huge and unbiased data sets of automatically recorded actual gambling behavior. This study refers to data on 2,127,887 poker playing identities from the Online Poker Database of the University of Hamburg (OPD-UHH) to analyze three subgroups of gamblers: regulars, newcomers, and dropouts. Their gambling habits over 6 months are analyzed in total, as well as over time. Regulars show a much higher involvement than non-regulars and increase their playing volume slightly over the observation period. Newcomers have a lower involvement than non-newcomers and most of them decrease their playing volume over time. Still, there is a small group of newcomers which increases their playing volume sharply and is, hence, very interesting for the industry as well as for the early prevention of pathological gambling. Dropouts have a higher gambling involvement than newcomers but play less than players who have not stopped stop gambling. Most dropouts also show a decreasing playing volume before dropping out. An analysis of the correlations between different variables of gambling habits shows that most of them reinforce each other, for example: gamblers with a higher total playing time tend to play at more tables simultaneously. Only playing frequency is a moderating variable of gambling involvement.