The Role of Migration in the Urban Transition: A Demonstration From Albania

Although natural increase has been recognized as the main driver of postwar urban growth in developing countries, urban transition theory predicts a dominant role for population mobility in the early and late phases of the process. To account for this discrepancy between theory and empirical evidence, I demonstrate the complex role played by internal and international migration in the pattern of urban growth. Using a combination of indirect demographic estimations for postwar Albania, I show that the dominant contribution of natural increase from the 1960s to the 1990s was induced by a limited urban in-migration; this was due to the restrictions on leaving the countryside imposed under communist rule and, thereafter, to the redirection abroad of rural out-migrants. Although young adults in cities also engaged in international movements and significantly reduced their fertility, the indirect effects of rural-to-urban migration attenuated the fall in urban birth rates and postponed demographic aging. In-migrants swelled urban cohorts of reproductive age and delayed the urban fertility transition. Despite a high level of urban natural increase in Albania, I thus conclude that the role of population mobility dominated in the early and most recent phases of urban growth. The results also have implications for our understanding of demographic processes during the second urban transition in developing countries.     

Determinants of savings and remittances: empirical evidence from immigrants to Germany

This paper investigates the determinants of migrants’ financial transfers to their home country using German data. A double-hurdle model is applied to analyze the determinants of the propensity to send transfers to the country of origin and the amount of transfers. The findings reveal that return intentions positively affect financial transfers of immigrants to their home country. The results of a decomposition analysis suggest that only a small part of the gap in financial transfers 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.     

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.     

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.     

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.     

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.     

The Effectiveness of Immigration Policies

This article elaborates a conceptual framework for assessing the character and effectiveness of immigration policies. It argues that, to a considerable extent, the public and academic controversy concerning this issue is spurious because of fuzzy definitions of policy effectiveness, stemming from confusion between (1) policy discourses, (2) policies on paper, (3) policy implementation, and (4) policy impacts. The article distinguishes three policy gaps: the discrepancy between public discourses and policies on paper (discursive gap); the disparity between policies on paper and implemented policies (implementation gap); and the extent to which implemented policies affect migration (efficacy gap). Although implemented policies seem to be the correct yardstick to assess policy effectiveness, in practice the (generally more pronounced) discourses are often used as a benchmark. This can lead to an overestimation of policy failure. Existing empirical studies suggest that policies significantly affect the targeted migration flows, but they crucially fail to assess the relative importance of policies in comparison to other migration determinants, including non‐migration policies, as well as the hypothetical occurrence of unintended categorical, spatial, inter‐temporal, and reverse flow “substitution” effects. Evidence on such effects is still scarce, showing the need for more empirically informed insights about the short‐ and long‐term effects of migration policies.     

Ein Optimierungsansatz für ein fortlaufendes Datenqualitätsmanagement und seine praktische Anwendung bei Kundenkampagnen

Zusammenfassung  Die Verbesserung der Datenqualit?t (DQ) wird in Wissenschaft und Praxis intensiv diskutiert. Ob die ergriffenen DQ-Ma?nahmen jedoch ?konomisch überhaupt gerechtfertigt sind und wann und in welchem optimalen Umfang investiert werden soll, wird oftmals nicht analysiert. Zur Untersuchung dieser Fragestellungen entwickeln die Autoren ein Optimierungsmodell, mit dem die Umf?nge und Zeitpunkte für Investitionen in ein fortlaufendes DQ-Management ermittelt werden k?nnen. Hierdurch lassen sich vier Investitionsszenarien mit allgemeinen Handlungsempfehlungen identifizieren. So ist bspw. bei ehemalig intensiven Kundenbeziehungen, die sich inzwischen verschlechtert haben (nur wenige Gesch?ftstransaktionen), zwar über mehrere Perioden zu investieren, jedoch bei einem sich nicht ver?ndernden, geringen Transaktionsanteil, in abnehmender H?he. Daneben l?sst sich u. a. zeigen, dass der Umfang der existierenden Kundendatenmenge und nicht, wie oftmals angeführt, ein schlechtes existierendes DQ-Niveau ma?geblich für die Entscheidung ist, ob überhaupt in DQ investiert werden soll. Anhand einer Fallstudie wird abschlie?end nicht nur die praktische Anwendbarkeit des Optimierungsmodells verdeutlicht, sondern es soll zudem aufgezeigt werden, wie sich für einen konkreten Sachverhalt detaillierte Empfehlungen hinsichtlich des DQM-Einsatzes ermitteln lassen.

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A model based approach for continuous data quality management and its implementation to improve customer campaigns

Summary  The improvement of data quality (DQ) currently finds a great deal of attention in science as well as in practice. Nevertheless there are two fundamental questions that are often ignored in the analysis: i) Are the DQ measures already implemented economically reasonable? ii) When and to what extent is investing into the improvement of DQ justifiable? For an in-depth understanding considering the design of DQ management the authors develop an optimization model which determines the optimal amount and point of time for consecutive DQ investments. Hence they distinguish between four scenarios and propose corresponding action recommendations. For example, a customer relationship with declining intensity up to the present (i. e. diminishing volume of business transactions) requires DQ investments over several future business periods- and at a decreasing investment rate in cases where the transaction volume continues to go down. Additionally it can be shown that in general the amount of available client data is a crucial factor for the decision whether it is reasonable to invest into DQ at all as opposed to a low quality level — which is often claimed. A concluding case study determines the practical applicability of the proposed optimization model.