Efficiency Analysis of the European Food Banks: Some Managerial Results

Hundreds of thousands of people in Europe are daily receiving food, thanks to local food banks, run basically by volunteers who collect donations and distribute them to organizations. In this paper, data from a sample of food banks working in 13 European countries are analysed using Data Envelopment Analysis (DEA), trying to learn about their profiles and find some clues about the efficiency of their operations, comparing them according to variables such as the number of volunteers and permanent staff, the tonnage of food delivered and the number of people served. Significant inefficiencies were found in the sector as a result of high performance of some food banks, thus setting a high level standard of operational efficiency. Some additional results regarding food bank sizes and performance are presented.     

Mexican Immigrants,Labour Market Assimilation and the Current Population: The Sensitivity of Results Across Seemingly Equivalent Surveys

In this paper we compare estimates of immigrants’ labour supply assimilation profiles using the Current Population Survey Annual Demographic Files (March ADS) and the Current Population Survey Outgoing Rotation Groups (ORGs). We use a measure that is seemingly consistent across both surveys: usual weekly hours of work in the main job. This measure is not only important as it measures the intensive margin of labour supply, but it is also used to estimate hourly earnings in both surveys. Our results indicate that the two surveys produce dramatically different estimates of the change in average hours of work as immigrants’ years in the United States increase: estimates from the March ADS predict much steeper hour's assimilation profiles than do estimates obtained from the ORGs. These differences persist if we include controls for demographic characteristics, and only disappear once we control for occupation heterogeneity. We argue that these differences stem from two separate factors that differentiate the data. First, the ADS and ORG frame the usual “hours worked” question differently. Also, differences in the timing of the surveys may produce seasonality effects that differentially affect the composition of recent and earlier migrants, thereby changing assimilation profiles.     

Application of an Irt Polytomous Model for Measuring Health Related Quality of Life

Background: The Item Response Theory (IRT) has advantages for measuring Health Related Quality of Life (HRQOL) as opposed to the Classical Tests Theory (CTT). Objectives: To present the results of the application of a polytomous model based on IRT, specifically, the Rating Scale Model (RSM), to measure HRQOL with the EORTC QLQ-C30. Methods: 103 terminal cancer patients cared for by the home services of the Servicio Andaluz de Salud (Andalusian Health Service) (Andalusia, Spain) participated. These patients responded to the adapted Spanish version of the EORTC QLQ-C30. The application was carried out individually in the patients’ homes. Results: The results show that there is an adequate global fit between the data and the IRT model applied. The analysis of the items shows that for 31 of the 33 items there is a good fit. The items which measure the general perception of health and the perception of quality of life present a lack of fit. The study of the response categories of the items (by means of Category Probability Curves) indicates that all the alternatives work extremely well. Conclusions:The EORTC QLQ-C30 presents good metric qualities, under the RSM, ratifying the feasibility to measure HRQOL already shown in other studies carried out with CTT.     

Serving the needs of immigrant families of children with autism

The growing influx of immigrant families into the USA necessitates an understanding of how these families manage mental health disorders. Few studies have documented the ways in which autism spectrum disorders (ASD) are understood across different immigrant groups. This lack of knowledge creates barriers for practitioners who are encountering immigrant families in their practice. The present paper provides a conceptual framework of how cultural values and beliefs shape the way diagnosis, etiology and treatment of ASD is perceived by both immigrant families and western practitioners and how differences in perspectives may create obstacles in treatment planning. A review of the literature describing practical and cultural barriers to mental health access and research among immigrant populations is also presented. Finally, recommendations are offered to practitioners, families and individuals with ASD to aid in increasing understanding and collaboration among these populations when designing and implementing treatment interventions.     

Multi-relational learning via hierarchical nonparametric Bayesian collective matrix factorization

Relational learning addresses problems where the data come from multiple sources and are linked together through complex relational networks. Two important goals are pattern discovery (e.g. by (co)-clustering) and predicting unknown values of a relation, given a set of entities and observed relations among entities. In the presence of multiple relations, combining information from different but related relations can lead to better insights and improved prediction. For this purpose, we propose a nonparametric hierarchical Bayesian model that improves on existing collaborative factorization models and frames a large number of relational learning problems. The proposed model naturally incorporates (co)-clustering and prediction analysis in a single unified framework, and allows for the estimation of entire missing row or column vectors. We develop an efficient Gibbs algorithm and a hybrid Gibbs using Newton's method to enable fast computation in high dimensions. We demonstrate the value of our framework on simulated experiments and on two real-world problems: discovering kinship systems and predicting the authors of certain articles based on article–word co-occurrence features.     

ON THE EFFECTIVENESS OF SB1070 IN ARIZONA

We investigate the effectiveness of Arizona's omnibus immigration law SB1070, which made it a misdemeanor crime for an alien to not carry proper documentation and asked police to determine the immigration status of any person suspected of being an illegal alien during a lawful stop. We find that SB1070's enactment coincided with the stalling to slight recovery of the share of non‐citizen Hispanics in Arizona 3 years after the enactment of an employment verification mandate to all employers. Yet, its effectiveness in reducing the share of likely unauthorized immigrants has been minimal and questions the merit of the law. (JEL J61, J1)     

Assessing Climate Change Impacts on Wildfire Exposure in Mediterranean Areas

We used simulation modeling to assess potential climate change impacts on wildfire exposure in Italy and Corsica (France). Weather data were obtained from a regional climate model for the period 1981–2070 using the IPCC A1B emissions scenario. Wildfire simulations were performed with the minimum travel time fire spread algorithm using predicted fuel moisture, wind speed, and wind direction to simulate expected changes in weather for three climatic periods (1981–2010, 2011–2040, and 2041–2070). Overall, the wildfire simulations showed very slight changes in flame length, while other outputs such as burn probability and fire size increased significantly in the second future period (2041–2070), especially in the southern portion of the study area. The projected changes fuel moisture could result in a lengthening of the fire season for the entire study area. This work represents the first application in Europe of a methodology based on high resolution (250 m) landscape wildfire modeling to assess potential impacts of climate changes on wildfire exposure at a national scale. The findings can provide information and support in wildfire management planning and fire risk mitigation activities.     

Centerline-SMED integration for machine changeovers improvement in food industry

This paper demonstrates how it is possible to combine SMED with Centerlining in complex production environments with numerous changes of format, product, raw materials and tools. This research proposes a methodology involving an initial application of Centerlining and, once the machinery and the process are stable, the subsequent implementation of SMED. Furthermore, it aims to show that it is possible to achieve improved output and reduced machinery changeover time while ensuring that the effect achieved by SMED is more stable. This increases the organizational advantages with respect to the implementation of SMED without prior application of Centerlining. The most important overall conclusion is that a successful application of SMED must always be accompanied by another type of tool or technique to maximize the results of its application. And, as presented in this work, one technique that enables significant improvements to SMED is the application of Centerlining.