Updating the UK's code for fiscal stability

The 1998 Code for Fiscal Stability sets out the framework within which UK fiscal policy is now set. While having such a code does not make it easier for a Government to meet its fiscal objectives, it may improve the economic credibility of the policy process. To date the Code has generally worked well, and in any case many of the Treasury's practices exceed the minimum requirements of the Code. However, improvements could be made in the light of recent experiences. In particular it would be preferable for less emphasis to be placed on the precise forecasts for fiscal aggregates and greater emphasis to be placed on the magnitude of the risks to those forecasts. Using the projections contained in the March 2004 Budget, and information on the size of errors made in the past, we estimate that there is now a 60% chance that the Chancellor's "golden rule" will be met without further tax increases or spending cuts. This compares to 74% for the forecast made by the Treasury 12 months earlier. As well as clarifying how cautious forecasts are, the uncertainty surrounding projections for fiscal aggregates also has implications for the way in which progress towards any fiscal rules should be interpreted.

Education subsidies and school drop-out rates

This paper evaluates whether means-tested grants paid to secondary students are an effective way of reducing the proportion of school dropouts. We look at this problem using matching techniques on a pilot study carried out in England during 1999 and 2000 using a specially designed dataset that ensures that valid comparisons between our pilot and control areas are made. The impact of the subsidy is quite substantial with initial participation rates (at age 16/17) being around 4.5 percentage points higher. Full-time participation rates one year later are found to have increased by around 6.4 percentage points which is largely due to the EMA having a significant effect on retention in post compulsory education. These effects vary by eligibility group with those receiving the full payment having the largest initial increase in participation, whilst the effects for those who are partially eligible are only significantly different from the control group in the second year of the program. There is some evidence that the participation rate effect is stronger for boys, especially in the second year, and that the policy goes some way to reducing the gap in dropout rates between boys and girls. It is also clear that the policy has the largest impact on children from the poorest socio-economic background.

A Survey of Housing Equity Withdrawal and Injection in Australia

Over the past decade or so, aggregate data suggest a trend increase in housing equity withdrawal in Australia, potentially stimulating household spending. However, there has been little disaggregated information on how equity is being withdrawn and injected, the characteristics of households altering housing equity, and how funds from withdrawn equity are being used. This paper uses a survey of 4 500 households commissioned by the Reserve Bank of Australia (RBA) to address these questions. The results suggest that, during 2004, the most common method of withdrawing equity was for a household to increase the level of debt secured against a property they already owned. In contrast, most of the value of equity withdrawn was associated with property transactions, with the typical property transaction resulting in a net equity withdrawal. Turnover in the property market is therefore likely to be an important driver of cycles in aggregate housing equity withdrawal. Bivariate and logit analysis suggests a significant life-cycle influence, with the bulk of equity withdrawal being undertaken by older households, while younger households typically inject, primarily through mortgage repayments or deposits for property purchase. Finally, the results suggest that the bulk of the value of withdrawn equity was used to increase non-housing assets, although a significant proportion of households used the funds for consumption expenditure.housing equity withdrawal; housing turnover; household debt

Education Subsidies and School Drop-Out Rates

Education, School

Dopamine regulation of contextual fear and associated neural circuit function

© 2020 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd Learning to associate certain contexts with threat and adapting to changing environmental contingencies by learning that such contexts are no longer associated with threat are both crucial for survival. Research over the last few decades has made considerable progress in determining the brain areas involved in the encoding, retrieval and extinction of contextual fear. These studies have identified the hippocampus and amygdala, along with the prefrontal cortex and other inter-connected brain areas, as key players in contextual fear processing. In contrast to the neural circuit basis of contextual fear, the neurochemical mechanisms involved in its regulation remain poorly understood. Dopamine is well known for its role in appetitive learning but this neurotransmitter is also important for other types of learning, including spatial and aversive memory processing. Dopamine is ideally positioned to regulate contextual fear given that the areas involved receive dopamine input and express dopamine receptors. Moreover, neuronal activity, functional connectivity and synaptic plasticity in this neural circuitry are modulated by dopamine receptor signalling. Here, we review the evidence indicating that dopamine regulates various contextual fear processes, along with the more recent studies that have begun to elucidate the brain areas and neurophysiological mechanisms involved. From a fundamental research perspective, understanding how dopamine regulates contextual fear will lead to novel insights on the neurochemical modulation of neural circuit function underlying memory processing. This research may also have translational relevance given that contextual fear conditioning and extinction also provide useful preclinical models of certain aspects of anxiety-related disorders and their treatment

Development and validation of the e-Work Self-Efficacy Scale to assess digital competencies in remote working

The COVID-19 pandemic accelerated the adoption of remote working practices worldwide. This has focussed attention on the need to identify the competencies employers and employees should train and develop to build digital resilience, enabling the benefits of remote working to be realised while mitigating potential risks. This contribution presents a multifaceted e-Work Self-Efficacy Scale, which supports a recently developed Digital Resilience Competency Framework (DRCF), assessing e-skills, trust building, self-care, remote social skills, and remote emotional self-efficacy beliefs. Data from 670 non-managerial employees (54.0% males) from a telecommunications company based in the Czech Republic were analysed, providing support for a bi-factor model. Latent Profile Analysis identified three clusters, characterised by different profiles: the Well-adjusted (with a reasonably good balance in engagement, satisfaction, and productivity), the Unhealthily dedicated (suffering some difficulties in setting boundaries), and the Distrustful self-shielding (the most compromised) remote workers. The results reinforce the importance of focusing on digital resilience competencies to promote sustainable, productive, engaging and healthy remote working. The e-Work Self-Efficacy Scale is a practical and effective organisational tool for managers and employees to use to assess and build digital resilience and sits alongside the Digital Resilience Competency Framework

Clustering proteins from interaction networks for the prediction of cellular functions

BACKGROUND: Developing reliable and efficient strategies allowing to infer a function to yet uncharacterized proteins based on interaction networks is of crucial interest in the current context of high-throughput data generation. In this paper, we develop a new algorithm for clustering vertices of a protein-protein interaction network using a density function, providing disjoint classes. RESULTS: Applied to the yeast interaction network, the classes obtained appear to be biological significant. The partitions are then used to make functional predictions for uncharacterized yeast proteins, using an annotation procedure that takes into account the binary interactions between proteins inside the classes. We show that this procedure is able to enhance the performances with respect to previous approaches. Finally, we propose a new annotation for 37 previously uncharacterized yeast proteins. CONCLUSION: We believe that our results represent a significant improvement for the inference of cellular functions, that can be applied to other organism as well as to other type of interaction graph, such as genetic interactions

Jugend in sozialistischen Arbeitskollektiven: Zusatzbericht: Zusammenhang zwischen Kollektivgröße, -zusammensetzung, -zugehörigkeit und dem Ausprägungsgrad einiger sozialistischer Kollektiv- und Persönlichkeitsmerkmale

In der Studie werden die Zusammenhänge von Kollektivgröße, Kollektivzusammensetzung bezüglich der Geschlechter, Dauer der Kollektivzugehörigkeit und Schichtsystem mit den untersuchten Kollektivmerkmalen und Persönlichkeitsmerkmalen von jungen Werktätigen in sozialistischen Arbeitskollektiven analysiert. Im einzelnen werden betrachtet: (1) Kollektivbedingungen; (2) Integration in das Arbeitskollektiv; (3) Leistungsmerkmale des Kollektivs; (4) Einstellung zur Arbeit und zum sozialistischen Wettbewerb; (5) Teilnahme an volkswirtschaftlichen Initiativen; (6) Leitung und Leiter; (7) Erwartungen an das Arbeitskollektiv; (8) die Tätigkeit der FDJ im Kollektiv. Die Auswertung des Datenmaterials ergibt, daß sich junge Werktätige, die in unterschiedlichen Schichtsystemen arbeiten, bezüglich der befragten Kollektivmerkmale und Persönlichkeitsmerkmale nicht unterscheiden. (ICA