Xenophobic attacks, migration intentions, and networks: evidence from the South of Africa

We investigate how emigration from a developing region is affected by xenophobic violence at destination. Based on a unique household survey collected in Mozambique in summer 2008, a few months after a series of xenophobic attacks in South Africa that killed dozens and displaced thousands of immigrants from neighboring countries, we estimate migration intentions of Mozambicans before and after the attacks, controlling for a placebo period. We focus on the role of family and social networks in the sending community in shaping changes in the expressed intentions to migrate. We find that the migration intention of household heads decreases after the violence, especially for those household heads with many children whose families have no access to social networks. The results illustrate that networks at origin insure risks related to migration and that, when deciding to migrate, workers tend to care more about the future of their offspring than their own health.     

A psychometric evaluation of a Dutch version of the Job Content Questionnaire and of a short direct questioning procedure

Using the demand-control-support perspective on job stress, a Dutch translation of an adapted version of the Job Content Questionnaire (AJCQ) was administered to a large population ( N = 3638) of Flemish workers in a variety of jobs, together with the General Health Questionnaire, and a negative affectivity scale. Overall, the AJCQ was shown to be a solid measurement instrument as indicated by several estimated reliability indices and validity of the subscales. A factor analysis largely reproduced the a priori structure of the AJCQ. A short 10-item direct questioning procedure was constructed to measure the 10 subscales of the AJCQ and the results of this procedure were compared with the AJCQ in a subsample ( N = 660). The correlations with six criterion variables showed that single questions were equally predictive than the much longer version of the AJCQ.     

The Impact of Information Sharing on Supply Chain Performance under Asymmetric Information

The use of screening contracts is a common approach to solve supply chain coordination problems under asymmetric information. One main assumption in this context is that managers without specific incentives would rather use their private information strategically than reveal it truthfully. This harms supply chain performance. This study investigates the impact of information sharing in a principal‐agent setting that is typical for many supply chain transactions. We conduct a laboratory experiment to test whether information sharing has an influence on supply chain coordination. We find that information sharing within the supply chain has two positive effects. First, information sharing reduces the inefficiencies resulting from information deficits if there is a certain amount of trust in the supply chain. Second, communication can limit out‐of‐equilibrium behavior with a small impact on the firm's own payoff, but a large impact on the supply chain partner. Furthermore, we find that both effects are amplified when communication takes place in an environment that allows the less informed supply chain party to punish or to reward the better informed party. Although our extended mechanisms substantially enhance the poor performance of the theoretically optimal coordination contract menu, we find no mechanism that implements supply chain performance superior to the theoretically predicted second‐best level.     

Unbiased Bayesian inference for population Markov jump processes via random truncations

We consider continuous time Markovian processes where populations of individual agents interact stochastically according to kinetic rules. Despite the increasing prominence of such models in fields ranging from biology to smart cities, Bayesian inference for such systems remains challenging, as these are continuous time, discrete state systems with potentially infinite state-space. Here we propose a novel efficient algorithm for joint state/parameter posterior sampling in population Markov Jump processes. We introduce a class of pseudo-marginal sampling algorithms based on a random truncation method which enables a principled treatment of infinite state spaces. Extensive evaluation on a number of benchmark models shows that this approach achieves considerable savings compared to state of the art methods, retaining accuracy and fast convergence. We also present results on a synthetic biology data set showing the potential for practical usefulness of our work.     

The downside of organizational identification: Relations between identification,workaholism and well-being

Abstract

Employee organizational identification has been proposed and found to be positively related to employee health and well-being. The empirical evidence, however, is not unequivocal, and some authors have suggested possible downsides of identification with the organization as a whole or with a group within it. The potential negative effect of over-identification was tested empirically for the first time in the present paper. Two studies were conducted; Study 1 was cross-sectional and used a sample of Italian law court clerks (N=195) and Study 2 was longitudinal and employed a sample of Italian teachers (N=140 at T2). We proposed a curvilinear mediation model with identification curvilinearly predicting workaholism, and workaholism, in turn, negatively affecting employee well-being. This curvilinear link between organizational identification and workaholism means that workaholism at first decreases with growing identification, but when identification becomes too strong, workaholism increases. The results confirmed our hypotheses, and we discuss theoretical and practical implications.     

Matching on the Estimated Propensity Score

Propensity score matching estimators (Rosenbaum and Rubin (1983)) are widely used in evaluation research to estimate average treatment effects. In this article, we derive the large sample distribution of propensity score matching estimators. Our derivations take into account that the propensity score is itself estimated in a first step, prior to matching. We prove that first step estimation of the propensity score affects the large sample distribution of propensity score matching estimators, and derive adjustments to the large sample variances of propensity score matching estimators of the average treatment effect (ATE) and the average treatment effect on the treated (ATET). The adjustment for the ATE estimator is negative (or zero in some special cases), implying that matching on the estimated propensity score is more efficient than matching on the true propensity score in large samples. However, for the ATET estimator, the sign of the adjustment term depends on the data generating process, and ignoring the estimation error in the propensity score may lead to confidence intervals that are either too large or too small.     

Robust, accurate confidence intervals with a weak instrument: quarter of birth and education

Summary.  An instrument or instrumental variable manipulates a treatment and affects the outcome only indirectly through its manipulation of the treatment. For instance, encouragement to exercise might increase cardiovascular fitness, but only indirectly to the extent that it increases exercise. If instrument levels are randomly assigned to individuals, then the instrument may permit consistent estimation of the effects caused by the treatment, even though the treatment assignment itself is far from random. For instance, one can conduct a randomized experiment assigning some subjects to 'encouragement to exercise' and others to 'no encouragement' but, for reasons of habit or taste, some subjects will not exercise when encouraged and others will exercise without encouragement; none-the-less, such an instrument aids in estimating the effect of exercise. Instruments that are weak, i.e. instruments that have only a slight effect on the treatment, present inferential problems. We evaluate a recent proposal for permutation inference with an instrumental variable in four ways: using Angrist and Krueger's data on the effects of education on earnings using quarter of birth as an instrument, following Bound, Jaeger and Baker in using simulated independent observations in place of the instrument in Angrist and Krueger's data, using entirely simulated data in which correct answers are known and finally using statistical theory to show that only permutation inferences maintain correct coverage rates. The permutation inferences perform well in both easy and hard cases, with weak instruments, as well as with long-tailed responses.     

Understanding the concept of food sovereignty using the Ghana School Feeding Programme (GSFP)

This article deepens the understanding of the emerging food sovereignty concept using a case study of a home-grown school feeding programme that promotes local food demand – supply linkages. A school feeding programme in four selected districts in Ghana is analysed with respect to community involvement in programme implementation and management as well as its socio-economic impacts. A combination of quantitative and qualitative methodological approaches was used in data collection and analysis. Results showed a significant improvement in household food access and months of adequate household food provisioning, which were used as measurement proxies for food sovereignty, as a result of access to local market created by the Ghana School Feeding Programme. However, the study recommends more empirical evidence from research to support the claim that using locally produced food for school feeding actually reduces poverty and malnutrition in rural farming communities.