1000 resultados para Population projection
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This contribution builds upon a former paper by the authors (Lipps and Betz 2004), in which a stochastic population projection for East- and West Germany is performed. Aim was to forecast relevant population parameters and their distribution in a consistent way. We now present some modifications, which have been modelled since. First, population parameters for the entire German population are modelled. In order to overcome the modelling problem of the structural break in the East during reunification, we show that the adaptation process of the relevant figures by the East can be considered to be completed by now. As a consequence, German parameters can be modelled just by using the West German historic patterns, with the start-off population of entire Germany. Second, a new model to simulate age specific fertility rates is presented, based on a quadratic spline approach. This offers a higher flexibility to model various age specific fertility curves. The simulation results are compared with the scenario based official forecasts for Germany in 2050. Exemplary for some population parameters (e.g. dependency ratio), it can be shown that the range spanned by the medium and extreme variants correspond to the s-intervals in the stochastic framework. It seems therefore more appropriate to treat this range as a s-interval covering about two thirds of the true distribution.
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Incluye CD-ROM
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Incluye CD-ROM
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Includes bibliography
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Publicación bilingüe (Español e inglés)
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Publicación bilingüe (Español e inglés)
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Publicación bilingüe (Español e inglés)
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Publicación bilingüe (Español e inglés)
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Publicación bilingüe (Español e inglés)
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In this paper we survey five streams of research that have made important contributions to population projection methodology over the last decade. These are: (i) the evaluation of population forecasts; (ii) probabilistic methods; (iii) experiments in the projection of migration; (iv) projecting dimensions additional to age, sex and region; and (v) the use of scenarios for 'what if?' analyses and understanding population dynamics. Key developments in these areas are discussed, and a number of opportunities for further research are identified. Copyright (c) 2005 John Wiley & Sons, Ltd.
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This paper presents a dynamic Overlapping Generations Computable General Equilibrium (OLG-CGE) model of Scotland. The model is used to examine the impact of population ageing on the labour market. More specifically, it is used to evaluate the effects of labour force decline and labour force ageing on key macro-economic variables. The second effect is assumed to operate through age-specific productivity and labour force participation. In the analysis, particular attention is paid to how population ageing impinges on the government expenditure constraint. The basic structure of the model follows in the Auerbach and Kotlikoff tradition. However, the model takes into consideration directly age-specific mortality. This is analogous to “building in” a cohort-component population projection structure to the model, which allows more complex and more realistic demographic scenarios to be considered.
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This paper presents a dynamic Overlapping Generations Computable General Equilibrium (OLG-CGE) model of Scotland. The model is used to examine the impact of population ageing on the labour market. More specifically, it is used to evaluate the effects of labour force decline and labour force ageing on key macro-economic variables. The second effect is assumed to operate through age-specific productivity and labour force participation. In the analysis, particular attention is paid to how population ageing impinges on the government expenditure constraint. The basic structure of the model follows in the Auerbach and Kotlikoff tradition. However, the model takes into consideration directly age-specific mortality. This is analogous to “building in” a cohort-component population projection structure to the model, which allows more complex and more realistic demographic scenarios to be considered.
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For seasonal migrants, logistical constraints have often limited conservation efforts to improving survival and reproduction during the breeding season only. Yet, mounting empirical evidence suggests that events occurring throughout the migratory life cycle can critically alter the demography of many migrant species. Herein, we build upon recent syntheses of avian migration research to review the role of non-breeding seasons in determining the population dynamics and fitness of diverse migratory taxa, including salmonid fishes, marine mammals, ungulates, sea turtles, butterflies, and numerous bird groups. We discuss several similarities across these varied migrants: (i) non-breeding survivorship tends to be a strong driver of population growth; (ii) non-breeding events can affect fitness in subsequent seasons through seasonal interactions at individual- and population-levels; (iii) broad-scale climatic influences often alter non-breeding resources and migration timing, and may amplify population impacts through covariation among seasonal vital rates; and (iv) changes to both stationary and migratory non-breeding habitats can have important consequences for abundance and population trends. Finally, we draw on these patterns to recommend that future conservation research for seasonal migrants will benefit from: (1) more explicit recognition of the important parallels among taxonomically diverse migratory animals; (2) an expanded research perspective focused on quantification of all seasonal vital rates and their interactions; and (3) the development of detailed population projection models that account for complexity and uncertainty in migrant population dynamics.
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2010 Mathematics Subject Classification: 60J85, 92D25.
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Objective-The purpose of mammographic screening is to reduce mortality from breast cancer. This study describes a method for projecting the number of screens to be performed by a mammographic screening programme, and applies this method in the context of New South Wales, Australia. Method-The total number of mammographic screens was projected as the sum of initial screens and re-screens, and is based on projections of the population, rates of new recruitment, rates of attrition within the programme, and the mix of screening intervals. The baseline scenario involved: 70% participation of women aged 50-69 years, 90% return rate for the second and subsequent re-screens, 5% annual screens (95% biennial screens), and a specified population projection. The results were assessed with respect to variations in these assumptions. Results-The projections were strongly influenced by: the rate of screening of the target age group; the proportion of women re-screened annually; and the rates of attrition within the programme. Although demographic change had a notable effect, there was little difference between different population projections. Standard assumptions about attrition within the programme suggest that the current target participation rates in NSW may not be achieved in the long term. Conclusions-A practical model for projecting mammographic screens for populations is described which is capable of forecasting the number of screens under different scenarios. Implications-Projections of mammographic screens provide important information for the planning and financing of equipment and personnel, and for testing the effects of variations in important operational parameters. Re-screening attrition is an important contributor to screening viability.
