Uncertainty in population projections
The State of the Art
Bibliographic Data
| ID | 2953136 |
|---|---|
| Authors | Raquel Rangel De Meireles Guimarães (0000-0003-1754-9238, Universidade Federal do Paraná, corresponding author) |
| Year | 2014 |
| Volume | 31 |
| Issue | 2 |
| Pages | 277-290 |
| Publication date | 2014-12-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Revista Brasileira de Estudos de População (JOURNAL) |
| Journal identifiers | ISSN: 0102-3098 • E-ISSN: 1980-5519 |
| Publisher | FapUNIFESP (SciELO) (PUBLISHER) |
| DOI | 10.1590/s0102-30982014000200003 |
| OpenAlex | W1981776441 |
| SCIELO_PID | S0102-30982014000200003 |
| Language | EN |
| Citations received | 4 |
| References cited | 12 |
In this paper I critically review the state of the art in population projections, focusing on how uncertainty is handled in three approaches: the classical cohort-component, the frequentist probabilistic model and the Bayesian paradigm. Next, I focus on recent developments on mortality, fertility and migration projections under the Bayesian setting, which have been clearly at the frontier of knowledge in demography. By evaluating the merits and limitations of each framework, I conclude that in the near future the Bayesian paradigm will offer the most promising approach to population projections, since it combines expert opinion, information that demographers have readily available from their empirical analyses and sophisticated statistical and computational methods to deal with uncertainty. Hence, the availability of population forecasts that take uncertainty carefully into account may enhance communication among demographers by allowing for greater flexibility in reflecting demographic beliefs
Bayesian inference · Bayesian probability · Data science · Econometrics · Economics · Fertility · Flexibility (engineering · Focus (optics · Frequentist inference · Population · Probabilistic logic · Projections of population growth · Sociology · Statistics · Artificial Intelligence · Computer Science · demographic modeling and climate adaptation · Demography · Global Health Care Issues · Insurance, Mortality, Demography, Risk Management · Mathematics
Modeling and Forecasting U. S. Mortality
Recent developments in population projection methodology
Population Scenarios Based on Probabilistic Projections
An Expert-Based Framework for Probabilistic National Population Projections
Bayesian Probabilistic Projections of Life Expectancy for All Countries
Empirical bayes estimation of demographic schedules for small areas
Probabilistic Projections of the Total Fertility Rate for All Countries
Evaluating the performance of the lee-carter method for forecasting mortality
Mapping the Timing, Pace, and Scale of the Fertility Transition in Brazil
European Demographic Forecasts Have Not Become More Accurate Over the Past 25 Years
Expert-Based Probabilistic Population Projections
Demography, Measuring and Modeling Population Processes
| Unique citing works | 4 |
|---|---|
| Citations per year | 0,5 |
| Citation span | 2018 - 2026 (9) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 4 |