The savings behavior of temporary and permanent migrants in Germany

This paper examines the relative savings position of migrant households in West Germany paying particular attention to differences between temporary and permanent migrants. Our findings reveal significant differences in the savings rates between German natives and immigrants. If remittances are treated as savings, however, migrants who intend to return to their home country save significantly more than comparable natives. The results of a decomposition analysis indicate that slightly more than half of the differences in the savings rate between Germans and permanent migrants and almost 70% between temporary and permanent migrants can be attributed to differences in observable characteristics.     

Generic Identifiability of Linear Structural Equation Models by Ancestor Decomposition

Linear structural equation models, which relate random variables via linear interdependencies and Gaussian noise, are a popular tool for modelling multivariate joint distributions. The models correspond to mixed graphs that include both directed and bidirected edges representing the linear relationships and correlations between noise terms, respectively. A question of interest for these models is that of parameter identifiability, whether or not it is possible to recover edge coefficients from the joint covariance matrix of the random variables. For the problem of determining generic parameter identifiability, we present an algorithm building upon the half‐trek criterion. Underlying our new algorithm is the idea that ancestral subsets of vertices in the graph can be used to extend the applicability of a decomposition technique.     

Ein metrikbasierter Ansatz zur Messung der Aktualit?t von Daten in Informationssystemen

Due to the importance of using up-to-date data in information systems, this paper analyzes how the data quality dimension currency can be measured. Therefore, we design a probability based metric that allows for an objective and to a great extent automated assessment of data’s currency. In contrast to existing approaches, the resulting values of the new metric meet important requirements such as ratio scale and can be interpreted as probabilities. Hence, they can also be applied to calculate expected values for decision making in a methodically well-founded manner. Moreover, the metric can be adapted to the context of a particular application considering both, the specific characteristics of attribute values and supplemental data stored in the information system. The evaluation of the approach is based on six requirements for data quality metrics. Furthermore, the case of a mobile services provider illustrates the metric’s applicability and its practical benefit.     

A SINful approach to Gaussian graphical model selection

Multivariate Gaussian graphical models are defined in terms of Markov properties, i.e., conditional independences, corresponding to missing edges in the graph. Thus model selection can be accomplished by testing these independences, which are equivalent to zero values of corresponding partial correlation coefficients. For concentration graphs, acyclic directed graphs, and chain graphs (both LWF and AMP classes), we apply Fisher's z-transform, Šidák's correlation inequality, and Holm's step-down procedure to simultaneously test the multiple hypotheses specified by these zero values. This simple method for model selection controls the overall error rate for incorrect edge inclusion. Prior information about the presence and/or absence of particular edges can be readily incorporated.     

An extension of the Blinder–Oaxaca decomposition to nonlinear models

This paper develops a general Blinder–Oaxaca decomposition that allows the differences in an outcome variable between two groups to be decomposed into (i) a part that is explained by differences in observed characteristics and (ii) a part attributable to differences in the estimated coefficients also for nonlinear regression models. Based on this general model, we show how it can be applied to different models with discrete and limited dependent variables.     

International Migration and City Growth in the Global South: An Analysis of IPUMS Data for Seven Countries, 1992–2013

Evidence on the demographic components of city growth in the global South is scarce, and the role played by international migration is neglected. We analyze the importance of recent international migration in cities, compare it with that of internal movements, and evaluate the growth contribution across national contexts and the urban hierarchy. Combining individual-level census data and geographic master files of metropolitan areas with indirect demographic estimation techniques, we cover 377 cities in seven countries. It is found that, in almost one third of cities, population change and replacement has been mainly determined by migration. The international component was larger than the internal one in more than half of cities. Whereas internal migration tends to decrease with rising city size, international movements tend to increase. Positive net international migration substitutes for the net losses from domestic movements in large cities, but complements the gains in intermediate-sized cities.     

Multiscale change point detection for dependent data

In this article we study the theoretical properties of the simultaneous multiscale change point estimator (SMUCE) in piecewise-constant signal models with dependent error processes. Empirical studies suggest that in this case the change point estimate is inconsistent, but it is not known if alternatives suggested in the literature for correlated data are consistent. We propose a modification of SMUCE scaling the basic statistic by the long run variance of the error process, which is estimated by a difference-type variance estimator calculated from local means from different blocks. For this modification we prove model consistency for physical-dependent error processes and illustrate the finite sample performance by means of a simulation study.     

All risk-taking is not the same: examining the competing effects of firm risk-taking with meta-analysis

Although researchers have vigorously studied organizational risk-taking for over 35 years, relatively little emphasis has been placed on theoretically differentiating the unique relationships between the many risk-taking choices organizations make and firm risk or firm performance. In this research, we propose a new framework that builds from March’s exploration–exploitation model to argue that different risk-taking choices can have substantially different influences on firm outcomes. We use meta-analysis to examine the unique and at times competing effects of four of the most commonly studied risk-taking choices on firm risk and firm performance. Results from a meta-analysis of 257 unique studies (N = 499,808) demonstrate support for our proposed framework and cast significant doubt on the idea that commonly studied firm risk-taking choices theoretically aggregate into one overarching risk-taking construct.     

Containment im Coaching

The psychodynamic concept of containment in coaching describes a process where the coach takes on, digests and returns emotional tension, unresolved conflicts und unconscious acting out of the coachee. Using two case studies the article develops the basic elements of containment in coaching. In addition to this interpersonal dimension of containment the article also highlights the structural dimension of containment — to provide sufficient space and conditions for thinking and processing emotional turmoil.     

Welfare, labor supply and heterogeneous preferences: evidence for Europe and the US

Following the report of the Stiglitz Commission, measuring and comparing well-being across countries has gained renewed interest. Yet, analyses that go beyond income and incorporate non-market dimensions of welfare most often rely on the assumption of identical preferences to avoid the difficulties related to interpersonal comparisons. In this paper, we suggest an international comparison based on individual welfare rankings that fully retain preference heterogeneity. Focusing on the consumption-leisure trade-off, we estimate discrete choice labor supply models using harmonized microdata for 11 European countries and the US. We retrieve preference heterogeneity within and across countries and analyze several welfare criteria which take into account that differences in income are partly due to differences in tastes. The resulting welfare rankings clearly depend on the normative treatment of preference heterogeneity with alternative metrics. We show that these differences can indeed be explained by estimated preference heterogeneity across countries—rather than demographic composition.