Fears and realisations of employment insecurity

We investigate the validity of subjective data expectations of job loss and on the probability of re-employment consequent on job loss, by examining associations between expectations and realisations. We find that subjective expectations data reveal private information about subsequent job loss, the expectations data perform better with numerical descriptors than with ordinal verbal descriptors. On average, employees overestimate the chance of losing their job; while they underestimate the difficulty of finding another job as good as the currently-held one. We recommend that survey items on employment insecurity should be explicit about each risk investigation, and utilise a cardinal probability scale with discrete numerical descriptors

Part time employment and happiness: A cross-country analysis

The relationship between part time employment and job satisfaction is analysed for mothers in Germany, Denmark, the Netherlands, Finland, France, Spain and the UK. The impact of working part time on subjective life satisfaction and mental well-being is additionally analysed for British mothers. Cultural traditions concerning women´s role in society, and institutional differences between the countries are exploited. Results indicate that poor quality jobs can diminish any positive well-being repercussions of part time employment. The results additionally suggest that part time mothers in the UK experience higher levels of job satisfaction but not of overall life satisfaction as compared to their full time counterparts

Reducing streak film data via electronic cross correlator

Continuous /nonframing/ motion picture projector, two photocells, a cross-correlator, and a ground glass screen where the photocells intercept the stream image determine the time delay between successive streak images. Velocities corresponding to the streaks are determined from the delay together with the distance separating the photocells

The incidence and intensity of employer-provided training

This paper examines the provision of training by employers and the participation in training by employees, conditional on employers´ training provision. Together these two dimensions of training determine its overall distribution in the workforce. The factors which affect employer training provision and employee training participation are considered simultaneously within an empirical model using data drawn primarily from the 2001 Employers Skill Survey. The results are consistent with high fixed costs but constant marginal costs of training provision, while also supporting many of the predictions regarding the relationship between training and workforce skills, skill-shortages, workplace and local labour market characteristics

The impact of distance to nearest education institution on the post-compulsory education participation decision

This paper uses data sources with the unique capacity to measure distances between home addresses and education institutions, to investigate, for the first time, the effect that such distance has on an individual´s post–compulsory education participation decision. The results show that there is no overall net effect. However, when attention is focussed on young people who are on the margin of participating in post–compulsory education (according to their prior attainment and family background) and when post–compulsory education is distinguished by whether it leads to academic or vocational qualifications, then greater distance to nearest education institution is seen to have a significant impact on the decision to continue in full–time post–compulsory education. This finding has relevance for education participation in rural areas relative to urban areas

Ignorance is Almost Bliss: Near-Optimal Stochastic Matching With Few Queries

The stochastic matching problem deals with finding a maximum matching in a graph whose edges are unknown but can be accessed via queries. This is a special case of stochastic $k$-set packing, where the problem is to find a maximum packing of sets, each of which exists with some probability. In this paper, we provide edge and set query algorithms for these two problems, respectively, that provably achieve some fraction of the omniscient optimal solution. Our main theoretical result for the stochastic matching (i.e., $2$-set packing) problem is the design of an \emph{adaptive} algorithm that queries only a constant number of edges per vertex and achieves a $(1-\epsilon)$ fraction of the omniscient optimal solution, for an arbitrarily small $\epsilon>0$. Moreover, this adaptive algorithm performs the queries in only a constant number of rounds. We complement this result with a \emph{non-adaptive} (i.e., one round of queries) algorithm that achieves a $(0.5 - \epsilon)$ fraction of the omniscient optimum. We also extend both our results to stochastic $k$-set packing by designing an adaptive algorithm that achieves a $(\frac{2}{k} - \epsilon)$ fraction of the omniscient optimal solution, again with only $O(1)$ queries per element. This guarantee is close to the best known polynomial-time approximation ratio of $\frac{3}{k+1} -\epsilon$ for the \emph{deterministic} $k$-set packing problem [Furer and Yu, 2013] We empirically explore the application of (adaptations of) these algorithms to the kidney exchange problem, where patients with end-stage renal failure swap willing but incompatible donors. We show on both generated data and on real data from the first 169 match runs of the UNOS nationwide kidney exchange that even a very small number of non-adaptive edge queries per vertex results in large gains in expected successful matches

Caught in the Trap: Pricing Racial Housing Preferences

In The Two-Income Trap, Harvard Law School Professor Elizabeth Warren and business consultant Amelia Warren Tyagi reach a startling conclusion: a two-income middle-class family faces greater financial risks today than a one-income family faced three decades ago. Middle-class families are caught in an income trap because they budget based on two incomes and face financial ruin if they lose an income or incur unexpected expenses. The authors suggest that most middle-class families cannot quickly adjust their budgets because their largest monthly expense is the fixed mortgage payment. The parents maintained that they had to allocate a significant portion of their income to housing expenses to ensure they could buy a home in a good neighborhood with good, safe schools (pp. 22-23, 29, 32). Moreover, because good schools are located in expensive neighborhoods, parents contend that they must participate in a high priced bidding war for those homes. If their income declines or expenses increase, however, they are trapped: unable to pay the mortgage and unable to quickly reduce their living expenses (pp. 7-8). The book never explains how parents determine what is a good, safe neighborhood or school. Housing and school segregation patterns suggest, however, that some middle-class parents consciously or unconsciously use good and safe as a proxy for predominately or exclusively nonminority. This Review suggests that middle-income parents can no longer afford these racial housing preferences. The Review summarizes the problems middle-class families face then argues that what is viewed as good and safe may be based more on racially biased perceptions than on reality. The Review concludes by arguing that the best way to help middle-class families avoid the income trap is to make school assignments without regard to the student\u27s street address and to allow parents who live in integrated neighborhoods to participate in an auction to buy a slot in their first choice school