A long run structural macroeconometric model of the UK

A new modelling strategy is introduced which provides a practical approach to incorporating long- run structural relationships, suggested by economic theory, in an otherwise unrestricted VAR model. The strategy is applied in the construction of a small quarterly macroeconometric model of the UK, estimated over the period 1965q1-1995q4 in eight core variables: domestic and foreign outputs, domestic and foreign prices (both measured relative to oil prices), the nominal effective exchange rate, nominal domestic and foreign interest rates and real money balances. The aim is to develop a core model with a transparent and theoretically coherent foundation. Tests of restrictions on the long-run relations of the model are presented and the dynamic properties of the model are discussed.Long-Run Structural VAR, A Core UK Model, Macroeconomic Modelling, Persistence Profiles

Forecast Uncertainties in Macroeconomics Modelling: An Application to the UK Economy

This paper argues that probability forecasts convey information on the uncertainties that surround marco-economic forecasts in a manner which is straightforward and which is preferable to other alternatives, including the use of confidence intervals. Probability forecasts relating to UK output growth and inflation, obtained using a small macro-econometric model, are presented. We discuss in detail the probability that inflation will fall within the Bank of England's target range and that recession will be avoided, both as separate single events and jointly. The probability forecasts are also used to provide insights on the interrelatedness of output growth and inflation outcomes at different horizons.Probability Forecasting, Long Run Structural VARs, Macroeconometric Modelling, Forecast Evaluation, Probability Forecasts of Inflation and Output Growth

Life-span Extension With Reduced Somatotrophic Signaling: Moderation of Aging Effect by Signal Type, Sex, and Experimental Cohort.

Reduced somatotrophic signaling through the growth hormone (GH) and insulin-like growth factor pathways (IGF1) can delay aging, although the degree of life-extension varies markedly across studies. By collating data from previous studies and using meta-analysis, we tested whether factors including sex, hormonal manipulation, body weight change and control baseline mortality quantitatively predict relative lifeextension. Manipulations of GH signaling (including pituitary and direct GH deficiencies) generate significantly greater extension in median life span than IGF1 manipulations (including IGF1 production, reception, and bioactivity), producing a consistent shift in mortality risk of mutant mice. Reduced Insulin receptor substrate (IRS) expression produces more similar life-extension to reduced GH, although effects are more heterogeneous and appear to influence the demography of mortality differently. Life-extension with reduced IGF1 signaling, but neither GH nor IRS signaling, increases life span significantly more in females than males, and in cohorts where control survival is short. Our results thus suggest that reduced GH signaling has physiological benefits to survival outside of its actions on circulating IGF1. In addition to these biological moderators, we found an overrepresentation of small sample sized studies that report large improvements in survival, indicating potential publication bias. We discuss how this could potentially confound current conclusions from published work, and how this warrants further study replication

Comparative idiosyncrasies in life extension by reduced mTOR signalling and its distinctiveness from dietary restriction.

Reduced mechanistic target of rapamycin (mTOR) signalling extends lifespan in yeast, nematodes, fruit flies and mice, highlighting a physiological pathway that could modulate aging in evolutionarily divergent organisms. This signalling system is also hypothesized to play a central role in lifespan extension via dietary restriction. By collating data from 48 available published studies examining lifespan with reduced mTOR signalling, we show that reduced mTOR signalling provides similar increases in median lifespan across species, with genetic mTOR manipulations consistently providing greater life extension than pharmacological treatment with rapamycin. In contrast to the consistency in changes in median lifespan, however, the demographic causes for life extension are highly species specific. Reduced mTOR signalling extends lifespan in nematodes by strongly reducing the degree to which mortality rates increase with age (aging rate). By contrast, life extension in mice and yeast occurs largely by pushing back the onset of aging, but not altering the shape of the mortality curve once aging starts. Importantly, in mice, the altered pattern of mortality induced by reduced mTOR signalling is different to that induced by dietary restriction, which reduces the rate of aging. Effects of mTOR signalling were also sex dependent, but only within mice, and not within flies, thus again species specific. An alleviation of age-associated mortality is not a shared feature of reduced mTOR signalling across model organisms and does not replicate the established age-related survival benefits of dietary restriction

Swarm Robotics: A Survey from a Multi-Tasking Perspective

The behaviour of social insects such as bees and ants has influenced the development of swarm robots. To enable robots to cooperate together, swarm robotics employs principles such as communication, coordination, and collaboration. Collaboration among multiple robots can lead to a faster task completion time compared to the utilisation of a single, complex robot. One of the key aspects of swarm robotics is that control is distributed uniformly across the robots in the swarm, which boosts the system's resilience and fault tolerance. Through the use of the robots' embodied sensors and actuators, this distributed control often facilitates the emergence of collective behaviours through the interaction of the robots with one another and with the environment. The purpose of this survey is to examine the reasons behind the lack of utilisation of swarm robots in multi-tasking applications, which will be accomplished by studying previous research works in the field. We examine the literature from the perspective of multi-tasking: we pay particular attention to concepts that contribute to the progress of swarm robotics for multi-tasking applications. To do this, we first examine the different studies in multi-tasking swarm robotics, covering platforms, multi-tasking scenarios, sub-task allocation methodologies, and performance metrics. We then highlight several swarm robotics related disciplines that have significant effect on the development of swarm robotics for multi-tasking problems. We propose two taxonomies: the first categorises works based on the characteristics of the scenarios being handled, whereas the second taxonomy categorises works based on the swarming strategies utilised to achieve multi-tasking capabilities. We finish with a discussion of swarm robots' existing limitations for real-world multi-tasking applications, as well as recommendations for future research directions

Automatic Multi-Class Collective Motion Recognition Using a Decision Forest Extracted from Neural Networks

This paper presents an approach to machine recognition of multiple classes of collective motion behaviours. Previous work has demonstrated that it is possible to distinguish structured collective motion from random, unstructured motion. However, it has proved difficult to use such techniques for automatically recognising specific collective motion variants such as moving in a line versus moving in a group. To enable a knowledge base to recognise multiple classes of collective motion, this paper proposes a decision forest approach. The proposed approach extracts machine-understandable knowledge from a neural network trained to automatically recognise collective motions. The main advantage of this approach is that besides being automatic, it is fast, accurate and easy to use. We show that our deep neural network achieves 90.30% accuracy for multi-class labelling of collective motion behaviours, which is more accurate than shallow neural networks for this problem. Furthermore, a knowledge base extracted using the decision forest on the deep neural network can recognise the class of random behaviour and the eight classes of collective motion behaviours with 88.81% accuracy in just 0.03 seconds, which is only 1.49% less accurate than the original deep neural network, but over 100 times faster

Dangerous liaisons: youth sport, citizenship and intergenerational mistrust

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Sport Policy and Politics on 24/3/2014, available online: DOI 10.1080/19406940.2014.896390This paper reflects on and offers a critical analysis of the relationship between youth sport and citizenship development, in practice and in the UK policy context of sports coaching and physical education. While deploying data and insights from a recently completed research project in England, which identified substantial tensions in intergenerational relationships in sport and coaching, the argument and analysis also invokes wider international concerns and more generally applicable implications for policy and practice. Drawing heuristically upon the philosophy of Dewey (2007 [1916]), it is recognised that the concept of citizenship as a form of social practice should seek to encourage the development of complementary traits and dispositions in young people. To develop socially and educationally thus entails engagement in meaningful social and cultural activity, of which one potentially significant component is participation in youth sport, both within and outside formal education. However, it is argued that any confident assumption that sporting and coaching contexts will necessarily foster positive traits and dispositions in young people should be considered dubious and misplaced. Deploying a Lacanian (1981) perspective to interpret our data, we contend that ‘liaisons’ and interactions between coaches and young people are often treated suspiciously, and regarded as potentially ‘dangerous’

Macroeconometric Modelling with a Global Perspective

This paper provides a synthesis and further development of a global modelling approach introduced in Pesaran, Schuermann and Weiner (2004), where country specific models in the form of VARX* structures are estimated relating a vector of domestic variables to their foreign counterparts and then consistently combined to form a Global VAR (GVAR). It is shown that VARX* models can be derived as the solution to a dynamic stochastic general equilibrium (DSGE) model where over-identifying long-run theoretical relations can be tested and imposed if acceptable. Similarly, short-run over-identifying theoretical restrictions can be tested and imposed if accepted. The assumption of the weak exogeneity of the foreign variables for the long-run parameters can be tested, where foreign variables can be interpreted as proxies for global factors. Rather than using deviations from ad hoc statistical trends, the equilibrium values of the variables reflecting the long-run theory embodied in the model can be calculated

Trading places : worklessness dynamics in Greater Manchester

As part of the Local Economic Assessment process, a number of additional research projects were proposed by Greater Manchester (GM) local authorities into areas where data gaps exist or a greater understanding and analysis of a particular issue is required. One such area was the dynamics of the workless population in deprived neighbourhoods. There are neighbourhoods across GM where worklessness rates are persistently high. It has been suggested that in some areas this is partly the result of individuals moving out of deprived neighbourhoods to ‘better’ areas having found employment and then being replaced by workless individuals moving into the neighbourhood. Thus, people experience positive individual level employment outcomes whilst living in a neighbourhood, but the area may change little over time and may appear unresponsive to initiatives aimed at reducing worklessness. The analysis in this report breaks new ground in using individual level data on employment transitions and geographical movements taken from Department for Work and Pensions (DWP) and Her Majesty’s Revenue and Customs (HMRC) records to shed light on neighbourhood level population dynamics

Understanding the worklessness dynamics and characteristics of deprived areas

Research was commissioned to use individual level data from the Work and Pensions Longitudinal Study (WPLS) to try to shed light on some unanswered questions about the dynamics of worklessness in deprived areas. It has been suggested that in certain deprived neighbourhoods individuals make the transition from worklessness into employment and move away to less deprived areas. As these people move away they are replaced by inflows of other workless people who may themselves find employment and move on in a similar way. Therefore, although people experience positive individual level employment outcomes whilst living in a neighbourhood, the area may change little over time and may appear unresponsive to initiatives aimed at reducing worklessness. This research examines this issue and the associated policy implications. The research classifies deprived areas according to whether they were an ‘improver’ or ‘non-improver’ area, over the period 2004 to 2007, as well as identifying ‘transition’ areas (a subset of ‘non-improver’ areas characterised by high population churn). We have published a full list of these classifications for each Lower Super Output Area in Great Britain, to enable local partners to conduct their own follow-up research into the issues locally. This has been simultaneously published alongside this report