Probabilistic Approaches to Population Forecasting
Dados Bibliográficos
| ID | 4120967 |
|---|---|
| Autores | Ronald D Lee (0000-0001-9755-0436, autor correspondente) |
| Ano | 1998 |
| Volume | 24 |
| Páginas | 156 |
| Data de publicação | 1998-01-01 |
| Peer Reviewed | Sim |
| Open Access | Não |
| Tipo | ARTICLE |
| Periódico | Population and Development Review (JOURNAL) |
| Identificadores do periódico | ISSN: 0098-7921 • E-ISSN: 1728-4457 |
| Editora | JSTOR (PUBLISHER) |
| DOI | 10.2307/2808055 |
| OpenAlex | W2017965556 |
| Idioma | EN |
| Citações recebidas | 40 |
| Referências citadas | 5 |
ON AVERAGE people live long lives, have a long lag between birth and childbearing, and experience demographic rates with highly regular age patterns. These patterns generally change quite slowly. For these reasons, population is reliably predictable over fairly long periods compared to economic performance or the weather. Nonetheless, demographic forecasting does involve a good deal of uncertainty. We know that the US population will age rapidly between 2010 and 2035 as the huge baby boom generations move into old age; but we do not know what share of these generations will survive to old age, or how many potential workers will be born and survive throughout their working years to help support the elderly. We all know that demographic are often seriously wrong, and realize that forecasting errors are inevitable. It is generally agreed that demographers have a responsibility to indicate how certain or uncertain their may be. Traditional assess and communicate the uncertainty surrounding the middle, or preferred, forecast through the use of high and low versions. Each scenario, or set of assumptions underlying one of these three versions, contains an assumed trajectory for fertility, another for mortality, and another for migration. These scenario-based indications of uncertainty are of some use, but they have certain serious problems: no probability is attached to their high-low ranges, and they are internally inconsistent in the sense that they misrepresent the relative uncertainty in different measures such as population size, fertility, and old-age dependency ratios, for reasons that will be explained later. One visible and inevitable sign of this problem is that when the high-low scenarios are chosen to bracket the long-term population growth or age distribution, the annual values of fertility or births often fall outside the high-low range soon after the are published, making the forecasters appear (unjustly) to be incompetent. population offer an alternative approach to assessing and communicating uncertainty. Probabilistic forecasts can be un
Econometrics · Economics · Population · Probabilistic logic · Sociology · Artificial Intelligence · Computer Science · demographic modeling and climate adaptation · Demography · Global Health Care Issues · Insurance, Mortality, Demography, Risk Management
Fertility Response to the Covid-19 Pandemic in Developed Countries – On Pre-pandemic Fertility Forecasts
Die Bevölkerungsentwicklung der Metropolregion Rhein-Neckar
Recent developments in population projection methodology
The forecast accuracy of Australian Bureau of Statistics national population projections
A Guide to Global Population Projections
Australia's uncertain demographic future
Why population forecasts should be probabilistic - illustrated by the case of Norway
Time series analysis and stochastic forecasting
Análisis de los supuestos sobre la migración internacional en las proyecciones de población de México 2001-2050 y 2006-2050
Insights from the Evaluation of Past Local Area Population Forecasts
Empirical Prediction Intervals for County Population Forecasts
Previsão Pelo Serviço De Fornecimento De Água No Semiárido Brasileiro
Análise e previsão demográfica utilizando-se matrizes de crescimento e distribuição populacional intermunicipal
Long-range trends in adult mortality
Stochastic Population Forecasting Based on Combinations of Expert Evaluations Within the Bayesian Paradigm
Demographic Techniques
Aging in Advanced Industrial States
Demographic forecasting
An Expert-Based Framework for Probabilistic National Population Projections
Spatio-Temporal Machine Learning Analysis of Social Media Data and Refugee Movement Statistics
A probabilistic projection of beneficiaries of long-term care insurance in Germany by severity of disability
Lessons from stochastic small-area population projections
The end of population growth in Asia
Ageing of a giant
New Approaches to the Conceptualization and Measurement of Age and Aging
Long-Range Population Projections Made Simple
How Long Will We Live
Probabilistic population forecasts for small regions
Predictive Intervals for Age-Specific Fertility
Bayesian Probabilistic Projections of Life Expectancy for All Countries
Probabilistic Forecasting Using Stochastic Diffusion Models, With Applications to Cohort Processes of Marriage and Fertility
Demographic Metabolism
Does Specification Matter? Experiments with Simple Multiregional Probabilistic Population Projections
European Demographic Forecasts Have Not Become More Accurate Over the Past 25 Years
Trends in Causes of Death in Low-Mortality Countries
Bayesian population reconstruction of female populations for less developed and more developed countries
Coherent forecasts of mortality with compositional data analysis
Regional probabilistic fertility forecasting by modeling between-country correlations
Integrating uncertainty in time series population forecasts
Probabilistic household forecasts based on register data- the case of Denmark and Finland
| Obras citantes distintas | 40 |
|---|---|
| Citações por ano | 1,43 |
| Intervalo de citações | 1998 - 2026 (29) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 25 |