Employers' perspectives on benefit conditionality in the UK and Denmark

This article examines the under-explored demand-side of active labour market policies (ALMPs). Based on interview data from a comparative study of the UK and Denmark, the paper analyses employers' perspectives and experiences of ALMPs. In both countries, employers were favourably disposed towards employing unemployed jobseekers but held negative views on conditionality. First, benefit conditionality led to employers receiving large numbers of unsuitable and unfiltered job applications, with associated negative resource impacts. Second, employers perceived this as a product of ‘box ticking' and compliance targets. Finally, employers criticised policy and media rhetoric for focusing solely on the supply-side and for problematizing unemployed candidates. The paper argues that these crucial, but neglected, employer perspectives demonstrate that the current benefit conditionality regime in the UK risks irrevocably ‘tarnishing' candidates, which undermines, rather than enhances, their chances of securing employment through ALMPs. This unique dataset provides further evidence that the current direction of policy requires urgent and radical re-thinking.     

Rurality and Income Inequality in the United States, 1975–2015

Recent events have focused attention on the perceived widening of the economic divide between urban and rural areas, and on the continued rise of national income inequality. We demonstrate that, in fact, the average income gap between urban (metropolitan) and rural (nonmetropolitan) households has not risen over the past 40 years, and makes virtually no contribution to national income inequality. Rising national inequality is driven by rising inequality within both urban and rural America, not by an urban/rural divergence. As is well known, the growing dispersion of household money income is partly driven by rising wage inequality, particularly in urban areas. Less well recognized is the role played by other income sources. We show that a decline in the progressivity of the distribution of social security payments and cash transfers, and an increase in the regressivity of the distribution of retirement incomes, have jointly made a comparably large contribution to rising income inequality. At the same time, the share of income from self-employment has declined, particularly in rural America, and because self-employment income is very unequally distributed, its diminution has retarded the growth of rural inequality. In 2014–15, however, rural inequality increased, cutting the urban/rural inequality gap in half.     

Engaging Children in Meaningful Charity: Opening-up the Spaces within Which Children Learn to Give

This paper presents qualitative evidence from an in-depth, participative action research project with 150 children aged 4–8 years old, exploring their experiences, perceptions and preferences regarding charitable giving. Most children positively engage in charitable giving through home, school and their community; however, less than 20% are aware of the cause area they are being asked to support, and most have little decision-making in their giving. Children’s willingness to engage increases when they critically examine the cause area and are facilitated to lead on giving decisions, often resulting in increased and sustained efforts to support cause areas that matter to them.     

Ageing Population: Identifying the Determinants of Ageing in the Least Developed Countries

Population Research and Policy Review - The issue of population ageing is no longer exclusively centred on developed countries. Empirical studies have proven that the rise in the proportion of the...     

Regression models to dependence for exceedance

Extreme Value Theory (EVT) aims to study the tails of probability distributions in order to measure and quantify extreme events of maximum and minimum. In river flow data, an extreme level of a river may be related to the level of a neighboring river that flows into it. In this type of data, it is very common for flooding of a location to have been caused by a very large flow from an affluent river that is tens or hundreds of kilometers from this location. In this sense, an interesting approach is to consider a conditional model for the estimation of a multivariate model. Inspired by this idea, we propose a Bayesian model to describe the dependence of exceedance between rivers, where we considered a conditionally independent structure. In this model, the dependence between rivers is captured by modeling the excess marginally of one river as a consequence of linear functions of the other rivers. The results showed that there is a strong and positive connection between excesses in one river caused by the excesses of the other rivers.