Forecasting mortality in developed countries : insights from a statistical, demographic, and epidemological perspective
著者
書誌事項
Forecasting mortality in developed countries : insights from a statistical, demographic, and epidemological perspective
(European studies of population, v. 9)
Kluwer Academic Publishers, c2001
大学図書館所蔵 全2件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references
内容説明・目次
内容説明
Information on future mortality trends is essential for population forecasts, public health policy, actuarial studies, and many other purposes. Realising the importance of such needs, this volume contains contributions to the theory and practice of forecasting mortality in the relatively favourable circumstances in developed countries of Western Europe.
In this context techniques from mathematical statistics and econometrics can provide useful descriptions of past mortality. The naive forecast obtained by extrapolating a fitted model may give as good a forecast as any but forecasting by extrapolation requires careful justification since it assumes the prolongation of historical conditions. On the other hand, whilst it is generally accepted that scientific and other advances will continue to impact on mortality, perhaps dramatically so, it is impossible to quantify more than the outline of future consequences with a strong degree of confidence. The decision to modify an extrapolation of a model fitted to historical data (or conversely choosing not to modify it) in order to obtain a forecast is therefore strongly influenced by subjective and judgmental elements, with the quality of the latter dependent on demographic, epidemiological and indeed perhaps more general considerations. The thread running through the book reflects therefore the necessity of integrating demographic, epidemiological, and statistical factors to obtain an improvement in the prediction of mortality.
目次
Foreword. Preface. List of Authors. List of Figures. List of Tables. Part 1: Introduction. 1. A Review of Demographic Forecasting Models for Mortality. 2. A Review of Epidemiological Approaches to Forecasting Mortality and Morbidity. Part 2: Theoretical Perspectives on Forecasting Mortality. 3. A Regression Model of Mortality, with Application to the Netherlands. 4. Forecasting Mortality from Regression Models: the Case of the Netherlands. 5. Gompertz in Context: the Gompertz and Related Distributions. 6. Comparing Theoretical Age Patterns of Mortality Beyond the Age of 80. Part 3: From Theory to Practice. 7. Predicting Mortality from Period, Cohort or Cause-Specific Trends: a Study of Four European Countries. 8. Incorporating Risk Factor Epidemiology in Mortality Projections. 9. Projecting Mortality in Population Forecasts in the Netherlands. 10. The Latest Mortality Forecasts in the European Union. Part 4: Issues for the Future: More Consistency and Transparency. 11. Mortality Models Incorporating Theoretical Concepts of Ageing. 12. Towards an Integration of the Statistical, Demographic and Epidemiological Perspectives in Forecasting Mortality.
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