66 resultados para Sectoral shocks

em CentAUR: Central Archive University of Reading - UK


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Recent research documents the importance of uncertainty in determining macroeconomic outcomes, but little is known about the transmission of uncertainty across such outcomes. This paper examines the response of uncertainty about inflation and output growth to shocks documenting statistically significant size and sign bias and spillover effects. Uncertainty about inflation is a determinant of output uncertainty, whereas higher growth volatility tends to raise inflation volatility. Both inflation and growth volatility respond asymmetrically to positive and negative shocks. Negative growth and inflation shocks lead to higher and more persistent uncertainty than shocks of equal magnitude but opposite sign.

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This paper reports the proceedings of a conference held at Reading University in 1993 which addressed the issues of new technological developments at the regional and sub-regional levels in Britain and France. These new technological clusters - the `Technopoles' - are investigated in a series of papers in both English and French which examines their spatial, sectoral and economic aspects to determine what lessons can be learned from their development and what their future economic significance is likely to be. Two recurring themes are of particular significance in the papers - the link between R& D and regional development, and the different forms which innovation assumes within the various technopoles under scrutiny.

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In response to evidence of insect pollinator declines, organisations in many sectors, including the food and farming industry, are investing in pollinator conservation. They are keen to ensure that their efforts use the best available science. We convened a group of 32 ‘conservation practitioners’ with an active interest in pollinators and 16 insect pollinator scientists. The conservation practitioners include representatives from UK industry (including retail), environmental non-government organisations and nature conservation agencies. We collaboratively developed a long list of 246 knowledge needs relating to conservation of wild insect pollinators in the UK. We refined and selected the most important knowledge needs, through a three-stage process of voting and scoring, including discussions of each need at a workshop. We present the top 35 knowledge needs as scored by conservation practitioners or scientists. We find general agreement in priorities identified by these two groups. The priority knowledge needs will structure ongoing work to make science accessible to practitioners, and help to guide future science policy and funding. Understanding the economic benefits of crop pollination, basic pollinator ecology and impacts of pesticides on wild pollinators emerge strongly as priorities, as well as a need to monitor floral resources in the landscape.

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Climate change due to anthropogenic greenhouse gas emissions is expected to increase the frequency and intensity of precipitation events, which is likely to affect the probability of flooding into the future. In this paper we use river flow simulations from nine global hydrology and land surface models to explore uncertainties in the potential impacts of climate change on flood hazard at global scale. As an indicator of flood hazard we looked at changes in the 30-y return level of 5-d average peak flows under representative concentration pathway RCP8.5 at the end of this century. Not everywhere does climate change result in an increase in flood hazard: decreases in the magnitude and frequency of the 30-y return level of river flow occur at roughly one-third (20-45%) of the global land grid points, particularly in areas where the hydro-graph is dominated by the snowmelt flood peak in spring. In most model experiments, however, an increase in flooding frequency was found in more than half of the grid points. The current 30-y flood peak is projected to occur in more than 1 in 5 y across 5-30% of land grid points. The large-scale patterns of change are remarkably consistent among impact models and even the driving climate models, but at local scale and in individual river basins there can be disagreement even on the sign of change, indicating large modeling uncertainty which needs to be taken into account in local adaptation studies.

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The overall global-scale consequences of climate change are dependent on the distribution of impacts across regions, and there are multiple dimensions to these impacts.This paper presents a global assessment of the potential impacts of climate change across several sectors, using a harmonised set of impacts models forced by the same climate and socio-economic scenarios. Indicators of impact cover the water resources, river and coastal flooding, agriculture, natural environment and built environment sectors. Impacts are assessed under four SRES socio-economic and emissions scenarios, and the effects of uncertainty in the projected pattern of climate change are incorporated by constructing climate scenarios from 21 global climate models. There is considerable uncertainty in projected regional impacts across the climate model scenarios, and coherent assessments of impacts across sectors and regions therefore must be based on each model pattern separately; using ensemble means, for example, reduces variability between sectors and indicators. An example narrative assessment is presented in the paper. Under this narrative approximately 1 billion people would be exposed to increased water resources stress, around 450 million people exposed to increased river flooding, and 1.3 million extra people would be flooded in coastal floods each year. Crop productivity would fall in most regions, and residential energy demands would be reduced in most regions because reduced heating demands would offset higher cooling demands. Most of the global impacts on water stress and flooding would be in Asia, but the proportional impacts in the Middle East North Africa region would be larger. By 2050 there are emerging differences in impact between different emissions and socio-economic scenarios even though the changes in temperature and sea level are similar, and these differences are greater in 2080. However, for all the indicators, the range in projected impacts between different climate models is considerably greater than the range between emissions and socio-economic scenarios.

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Current methods for initialising coupled atmosphere-ocean forecasts often rely on the use of separate atmosphere and ocean analyses, the combination of which can leave the coupled system imbalanced at the beginning of the forecast, potentially accelerating the development of errors. Using a series of experiments with the European Centre for Medium-range Weather Forecasts coupled system, the magnitude and extent of these so-called initialisation shocks is quantified, and their impact on forecast skill measured. It is found that forecasts initialised by separate ocean and atmospheric analyses do exhibit initialisation shocks in lower atmospheric temperature, when compared to forecasts initialised using a coupled data assimilation method. These shocks result in as much as a doubling of root-mean-square error on the first day of the forecast in some regions, and in increases that are sustained for the duration of the 10-day forecasts performed here. However, the impacts of this choice of initialisation on forecast skill, assessed using independent datasets, were found to be negligible, at least over the limited period studied. Larger initialisation shocks are found to follow a change in either the atmospheric or ocean model component between the analysis and forecast phases: changes in the ocean component can lead to sea surface temperature shocks of more than 0.5K in some equatorial regions during the first day of the forecast. Implications for the development of coupled forecast systems, particularly with respect to coupled data assimilation methods, are discussed.

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This paper studies the impact of exogenous and endogenous shocks (exogenous shock is used interchangeably with external shock; endogenous shock is used interchangeably with domestic shock) on output fluctuations in post-communist countries during the 2000s. The first part presents the analytical framework and formulates a research hypothesis. The second part presents vector autoregressive estimation and analysis model proposed by Pesaran (2004) and Pesaran and Smith (2006) that relates bank real lending, the cyclical component of output and spreads and accounts for cross-sectional dependence (CD) across the countries. Impulse response functions show that exogenous positive shock lead to a drop in output sustainability for 9 over 12 Central Eastern European countries and Russia, when the endogenous shock is mild and ambiguous. Moreover, the effect of exogenous shock is more significant during the crises. Variance decompositions show that exogenous shock in the aftermath of crisis had a substantial impact on economic activity of emerging economies.

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Strategies to Reduce Emissions from Deforestation and Degradation (REDD) are being pursued in numerous developing countries. Proponents contest that REDD mechanisms could deliver sustainable development by contributing to both environmental protection and economic development, particularly in poor forest communities. However, among the challenges to REDD, and natural resource management more generally, is the need to develop a comprehensive understanding of cross-sectoral linkages and addressing how they impact the pursuit of sustainable development. Drawing on an exploratory case-study of Ghana, this paper aims to outline the linkages between the forestry and minerals sectors. It is argued that contemporary debates give incommensurate attention to the reclamation of large-scale mine sites located in forest reserves, and neglect to consider more nuanced links which characterise the forestry-mining nexus in Ghana. A review of key stakeholders further elucidates the complex networks which characterise these linkages and highlights the important role of traditional authorities in governing across sectors. If the multiple roles of local resource users and traditional authorities continue to be neglected in policy mechanisms, schemes such as REDD will continue to fall short of achieving sustainable development.

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This paper describes benchmark testing of six two-dimensional (2D) hydraulic models (DIVAST, DIVASTTVD, TUFLOW, JFLOW, TRENT and LISFLOOD-FP) in terms of their ability to simulate surface flows in a densely urbanised area. The models are applied to a 1·0 km × 0·4 km urban catchment within the city of Glasgow, Scotland, UK, and are used to simulate a flood event that occurred at this site on 30 July 2002. An identical numerical grid describing the underlying topography is constructed for each model, using a combination of airborne laser altimetry (LiDAR) fused with digital map data, and used to run a benchmark simulation. Two numerical experiments were then conducted to test the response of each model to topographic error and uncertainty over friction parameterisation. While all the models tested produce plausible results, subtle differences between particular groups of codes give considerable insight into both the practice and science of urban hydraulic modelling. In particular, the results show that the terrain data available from modern LiDAR systems are sufficiently accurate and resolved for simulating urban flows, but such data need to be fused with digital map data of building topology and land use to gain maximum benefit from the information contained therein. When such terrain data are available, uncertainty in friction parameters becomes a more dominant factor than topographic error for typical problems. The simulations also show that flows in urban environments are characterised by numerous transitions to supercritical flow and numerical shocks. However, the effects of these are localised and they do not appear to affect overall wave propagation. In contrast, inertia terms are shown to be important in this particular case, but the specific characteristics of the test site may mean that this does not hold more generally.

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The problem of modeling solar energetic particle (SEP) events is important to both space weather research and forecasting, and yet it has seen relatively little progress. Most important SEP events are associated with coronal mass ejections (CMEs) that drive coronal and interplanetary shocks. These shocks can continuously produce accelerated particles from the ambient medium to well beyond 1 AU. This paper describes an effort to model real SEP events using a Center for Integrated Space weather Modeling (CISM) MHD solar wind simulation including a cone model of CMEs to initiate the related shocks. In addition to providing observation-inspired shock geometry and characteristics, this MHD simulation describes the time-dependent observer field line connections to the shock source. As a first approximation, we assume a shock jump-parameterized source strength and spectrum, and that scatter-free transport occurs outside of the shock source, thus emphasizing the role the shock evolution plays in determining the modeled SEP event profile. Three halo CME events on May 12, 1997, November 4, 1997 and December 13, 2006 are used to test the modeling approach. While challenges arise in the identification and characterization of the shocks in the MHD model results, this approach illustrates the importance to SEP event modeling of globally simulating the underlying heliospheric event. The results also suggest the potential utility of such a model for forcasting and for interpretation of separated multipoint measurements such as those expected from the STEREO mission.

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Rationalizing non-participation as a resource deficiency in the household, this paper identifies strategies for milk-market development in the Ethiopian highlands. The additional amounts of covariates required for Positive marketable surplus -'distances-to market'-are computed from a model in which production and sales are correlated; sales are left-censored at some Unobserved thresholds production efficiencies are heterogeneous: and the data are in the form of a panel. Incorporating these features into the modeling exercise ant because they are fundamental to the data-generating environment. There are four reasons. First, because production and sales decisions are enacted within the same household, both decisions are affected by the same exogenous shocks, and production and sales are therefore likely to be correlated. Second. because selling, involves time and time is arguably the most important resource available to a subsistence household, the minimum Sales amount is not zero but, rather, some unobserved threshold that lies beyond zero. Third. the Potential existence of heterogeneous abilities in management, ones that lie latent from the econometrician's perspective, suggest that production efficiencies should be permitted to vary across households. Fourth, we observe a single set of households during multiple visits in a single production year. The results convey clearly that institutional and production) innovations alone are insufficient to encourage participation. Market-precipitating innovation requires complementary inputs, especially improvements in human capital and reductions in risk. Copyright (c) 20 08 John Wiley & Sons, Ltd.

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Natural resource-dependent societies in developing countries are facing increased pressures linked to global climate change. While social-ecological systems evolve to accommodate variability, there is growing evidence that changes in drought, storm and flood extremes are increasing exposure of currently vulnerable populations. In many countries in Africa, these pressures are compounded by disruption to institutions and variability in livelihoods and income. The interactions of both rapid and slow onset livelihood disturbance contribute to enduring poverty and slow processes of rural livelihood renewal across a complex landscape. We explore cross-scale dynamics in coping and adaptation response, drawing on qualitative data from a case study in Mozambique. The research characterises the engagements across multiple institutional scales and the types of agents involved, providing insight into emergent conditions for adaptation to climate change in rural economies, The analysis explores local responses to climate shocks, food security and poverty reduction, through informal institutions, forms of livelihood diversification and collective land-use systems that allow reciprocity, flexibility and the ability to buffer shocks. However, the analysis shows that agricultural initiatives have helped to facilitate effective livelihood renewal, through the reorganisation of social institutions and opportunities for communication, innovation and micro-credit. Although there are challenges to mainstreaming adaptation at different scales, this research shows why it is critical to assess how policies can protect conditions for emergence of livelihood transformation. (C) 2008 Elsevier Ltd. All rights reserved.