The demand for job protection: Some clues from behavioural economics

Radical differences in labour market regulations among countries that in other institutional respects are quite similar are still surprisingly frequent. Nonetheless, traditional theoretical analysis meets enormous difficulties in explaining these differences. The scope of our paper is to show that some clues from behavioural economics could be used to better theoretically treat this problem. Our argument is that workers are different, due to the effects of both culture and education. In particular, building on empirical evidence, we argue that loss aversion and hedonic adaptation are culturally-determined and country-specific aptitudes and that they may help explaining why workers, either employed or unemployed, ask for job protection and are willing to pay the cost of it. The main conclusion of our analysis is that, for poorly educated workers sharing a fatalist view of life, job protection can be more effective than public social expenditure. As a consequence, we suggest that countries with a poorly educated and fatalist workforce will be more prone to offer protection through job protection rather than public social expenditure, which is exactly what the empirical evidence shows.     

Reactions of students to different settings of field experience

The study assessed Israeli students’ emotional–experiential reaction and attitude to different client populations, following a week-long experience in one of five social services settings. The study provides preliminary findings regarding the implications of first year students’ experience on their emphatic skills, a subject that generally has not received adequate scholarly attention. Using a purpose-built, self-administered questionnaire, we found students’ emotional–experiential response to their experience differed by the setting in which they were placed, being lowest in the Bedouin oriented services, intermediate among those placed in juvenile correction services, and highest in mental health, adult and child disability services. Responses were independent of all other explanatory variables, including sex, cognitive ability, previous training experience and perceptual shifts concerning the population served. We discuss possible reasons for these differences.

     

Comparing the U.S. Decennial Census Coverage Estimates for Children from Demographic Analysis and Coverage Measurement Surveys

Following every U.S. decennial census since 1960, the U.S. Census Bureau has evaluated the completeness of coverage using two different methods. Demographic analysis (DA) compares the census counts to a set of independent population estimates to infer coverage differences by age, sex, and race. The survey-based approach (also called dual system estimation or DSE) provides coverage estimates based on matching data from a post-enumeration survey to census records. This paper reviews the fundamentals of the two methodological approaches and then initially examines the results of these two methods for the 2010 decennial census in terms of consistency and inconsistency for age groups. The authors find that the two methods produce relatively consistent results for all age groups, except for young children. Consequently, the paper focuses on the results for children. Results of the 1990, 2000, and 2010 decennial censuses are shown for the overall population in this age group and by demographic detail (age, race, and Hispanic origin). Among children, the DA and DSE results are most inconsistent for the population aged 0–4 and most consistent for ages 10–17. Results also show that DA and DSE are more consistent for Black than non-Black populations. The authors discuss possible explanations for the differences in the two methods for young children and conclude that the DSE approach may underestimate the net undercount of young children due to correlation bias.     

Measuring disparities in access to water based on the normative content of the human right

Measuring access to water in the Sustainable Development Goals era involves taking into account the human rights framework. Therefore, its content should be considered to conceptualize the level of service through adequate indicators and to follow-up inequities reduction at global, national and local level. This research develops and tests a methodology to measure intra-community disparities based on human right to water normative criteria through a stratified sampling, splitting households served by community based organizations and those self-provided. This approach implies considering much reduced populations, thus special care needs to be taken with sample sizes and uncertainty of estimators. The proposed methodology is practical to locate and accurately characterize minority sectors within rural communities and allows moving beyond central-tendency estimators. It implies higher costs for field data collection than traditional approaches, but this can be assumed given the relevance of the approach from a human rights perspective, which calls for adequate tools for equity-oriented policy making at local level. The research point out how results might be used to shape decision-making processes.     

SCHEDULING PARALLEL PROCESSORS WITH SETUP COSTS AND RESOURCE LIMITATIONS

An integer linear programming model is presented for the scheduling of n products on m identical machines. The particular problem studied is one that occurs frequently in the fiberglass and textile industries. The model incorporates setup costs, lost production costs, and overtime costs. Due to the structure of the model, integer solutions can be obtained by explicitly restricting only a small number of the integer variables. This allows those responsible for scheduling to solve realistically sized problems in an efficient manner. Computational results are provided for a set of generated test problems.     

Poverty and educational achievement in the US: A less-biased estimate using PISA 2012 data

In the current paper, we employ the most recent Programme for International Student Assessment (PISA) data to calculate a less-biased estimate of poverty on US achievement. The PISA was specifically chosen as it is an assessment removed from a specific curriculum and instead focuses on concepts that students should know in order to participate in a global economy. Using a propensity score matching approach, our findings suggest that US students in poverty have notable educational attainment deficiencies compared to a matched group of students who are not in poverty. In other words, when we select two students who have a great deal in common but for the fact that one comes from a poverty background, the student in poverty is expected to perform nearly 28 points, or about a quarter of a standard deviation lower, on the PISA assessment. In real terms, this puts math achievement for children not in poverty on-par with the Organisation for Economic Co-operation and Development (OECD) average, while children in poverty are well below the OECD average.