Migration Policy and Industrial Structure: The Case of Switzerland

Structural change in OECD countries, emphasizing knowledge‐based sectors, has led to an increasing demand for highly skilled labour. One means of meeting this demand has been to implement a selective immigration policy. Such policies, however, have been criticized for channelling labour into low‐producing sectors and occupations, hampering structural change. Proponents of such criticism point to Switzerland's former policy of channelling immigrants into so‐called seasonal sectors, a practice abandoned in the early 1990s, as having contributed to Switzerland's low growth rates. To assess this, we here analyse the amended migration policy's effects on skill structure and sectoral distribution of immigration flows using data from the Swiss Census of 1990 and 2000 to determine whether the new policy has led to an immigrant inflow more adapted to the processes of structural change. We find that the share of highly skilled immigrants has increased notably under the new migration policy. Our analysis also shows an important change in the sectoral focus of the new arrival inflow. Not only have fewer immigrants been entering declining sectors, but the majority of migrants arriving under the new policy regime have been absorbed into growing and knowledge‐based sectors, meaning they are employed primarily in service and knowledge‐intensive sectors. Overall, the analysis provides ample evidence that the current admission policy as ositively contributed to tructural change in Switzerland.     

Child Mortality and Socioeconomic Status: An Examination of Differentials by Migration Status in South Africa1

This study examines child mortality and socioeconomic status among migrants and nonmigrants. It also examines child mortality by migration status in all quintiles of socioeconomic status, comparing immigrants to the native‐born and internal migrants to nonmigrants. The results show that among migrants, child mortality decreased faster as socioeconomic status increased than among nonmigrants. The results also show a cross‐over in the likelihood of child mortality by immigration status as socioeconomic status increased. In the poorest socioeconomic quintiles immigrants had a greater likelihood of child mortality than the native‐born while in the wealthiest quintiles child mortality was greater among the native‐born.     

Culture, Context, and Homicide of the Elderly

In recent years, there has been a renewed interest in the criminal victimization of elderly persons. Given that homicides of the elderly are thought to occur primarily in the context of robbery/burglary situations, this study seeks to identify situational as well as structural and cultural factors that influence the murder of older persons. In particular, it has been noted that Southern culture promotes a notion that one should 'respect their elders.' Using conservative Protestant affiliation as a proxy for Southern culture, this study also examines the relationship between Southern culture and homicide of the elderly. Findings show that Southern culture as reflected in conservative Protestant affiliation does not insulate the elderly from victimization.     

Resilience and Survival: Black Teenage Mothers ‘Looked After’ by the State Tell their Stories About their Experience of Care

‘Looked after’ young people are among the most disadvantaged members of our society. While their disadvantaged status should not be ignored, poor outcomes are often emphasised at the expense of good ones. This article reports a study that adopts the concept of resilience to understand the narratives of the participants’ experience of care and foster care. A total of 15 young mothers, aged 16–19 and mainly from black African backgrounds, were interviewed. Despite lacking a ‘secure base’, informants invested in a sense of moral identity and a source of self‐directedness, which enabled them to move from victim of circumstances to individuals who overcome their circumstances.     

PROFIT‐MAXIMIZING GATE REVENUE SHARING IN SPORTS LEAGUES

In this article, I examine how sports leagues can use gate revenue sharing to coordinate talent investments and maximize club profits. Gate revenue sharing reduces incentives to invest in talent. Initially lower investments boost profits, because total costs go down, but investing less also shrinks revenues, which harms profits at higher levels of sharing. The league maximizes profits by setting a sharing rule, which balances these two effects. Gate revenue sharing decreases talent investments more strongly in leagues with heterogeneous rather than homogeneous local market sizes. As a result, the profit‐maximizing level of sharing is higher for relatively homogeneous leagues. This implies that more balanced leagues are expected to share more gate revenues than less balanced leagues. It also explains why gate revenue sharing is widely used in the U.S. major leagues, while it is largely absent in European soccer. (JEL L41, L83)     

A survey on multivariate chi-square distributions and their applications in testing multiple hypotheses

We are concerned with three different types of multivariate chi-square distributions. Their members play important roles as limiting distributions of vectors of test statistics in several applications of multiple hypotheses testing. We explain these applications and consider the computation of multiplicity-adjusted p-values under the respective global hypothesis. By means of numerical examples, we demonstrate how much gain in level exhaustion or, equivalently, power can be achieved with corresponding multivariate multiple tests compared with approaches which are only based on univariate marginal distributions and do not take the dependence structure among the test statistics into account. As a further contribution of independent value, we provide an overview of essentially all analytic formulas for computing multivariate chi-square probabilities of the considered types which are available up to present. These formulas were scattered in the previous literature and are presented here in a unified manner.     

Bayesian adaptive dose‐escalation procedures for binary and continuous responses utilizing a gain function

One of the main aims of early phase clinical trials is to identify a safe dose with an indication of therapeutic benefit to administer to subjects in further studies. Ideally therefore, dose‐limiting events (DLEs) and responses indicative of efficacy should be considered in the dose‐escalation procedure. Several methods have been suggested for incorporating both DLEs and efficacy responses in early phase dose‐escalation trials. In this paper, we describe and evaluate a Bayesian adaptive approach based on one binary response (occurrence of a DLE) and one continuous response (a measure of potential efficacy) per subject. A logistic regression and a linear log‐log relationship are used respectively to model the binary DLEs and the continuous efficacy responses. A gain function concerning both the DLEs and efficacy responses is used to determine the dose to administer to the next cohort of subjects. Stopping rules are proposed to enable efficient decision making. Simulation results shows that our approach performs better than taking account of DLE responses alone. To assess the robustness of the approach, scenarios where the efficacy responses of subjects are generated from an E _max model, but modelled by the linear log–log model are also considered. This evaluation shows that the simpler log–log model leads to robust recommendations even under this model showing that it is a useful approximation to the difficulty in estimating E _max model. Additionally, we find comparable performance to alternative approaches using efficacy and safety for dose‐finding. Copyright © 2015 John Wiley & Sons, Ltd.     

Understanding preferences for tree attributes: the relative effects of socio-economic and local environmental factors

Urban plant biodiversity is influenced by both the physical environment and attitudes and preferences of urban residents for specific plant types. Urban residents are assumed to be disconnected from their immediate environment, and cultural and societal factors have been emphasized over environmental factors in studies of landscaping choices. However, we postulate that local climatic and environmental factors can also affect preferences for plant attributes. Therefore, spatial and temporal patterns in urban tree biodiversity may be driven not only by the direct effect of environmental variables on plant function, but also by the effect of environmental variables on attitudes toward trees and associated choices about which types of trees to plant. Here, we tested the relative effects of socio-economic and local environmental factors on preferences toward tree attributes in five counties in southern California in and surrounding Los Angeles, based on 1,029 household surveys. We found that local environmental factors have as strong an effect on preferences for tree attributes as socio-economic factors. Specifically, people located in hotter climates (average maximum temperature 25.1 °C) were more likely to value shade trees than those located in cooler regions (23.1 °C). Additionally, people located in desert areas were less likely to consider trees to be important in their city compared with people located in naturally forested areas. Overall, our research demonstrates the inherent connections between local environmental factors and perceptions of nature, even in large modern cities. Accounting for these factors can contribute to the growing interest in understanding patterns of urban biodiversity.     

Time to Diagnosis: Accounting for Differential Endpoint Follow-up in Multi-Cohort Studies

Cox regression is widely used to analyze discrete survival time data. Differential endpoint follow-up across sub-cohorts where distribution of a covariate varies may cause typical estimators to be biased or inefficient. We demonstrate that with Cardiovascular Health Study data for incident type 2 diabetes. Two cohorts with extremely different race distribution have differential follow-up for fasting glucose levels. We study various scenarios of Cox regression. We suggest an alternative approach, Poisson generalized estimating equations with an offset to accommodate the differential follow-up. We use simulations to contrast the methods.