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| Demographic Balancing Equation× | Proiezione demografica per coorte e componente× | |
|---|---|---|
| Campo | Demografia | Demografia |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 1976 | 2001 |
| Ideatore≠ | Classical demographic accounting identity | Preston, Heuveline & Guillot |
| Tipo≠ | Population accounting identity for change over a period | Demographic projection pipeline |
| Fonte seminale | Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 9781557864512 | Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 978-1-557-86451-2 |
| Alias≠ | Balancing Equation of Population Change, Population Accounting Equation, Components of Population Change Identity | Cohort-Component Method, Component Method of Population Projection, Age-Sex-Specific Population Projection, Kohort-Bileşen Projeksiyonu |
| Correlati≠ | 4 | 3 |
| Sintesi≠ | The demographic balancing equation is the fundamental accounting identity of population change: a population at the end of a period equals its size at the start, plus births, minus deaths, plus in-migrants, minus out-migrants. It is the bookkeeping rule that ties together all the components of population dynamics and guarantees internal consistency in population estimates and projections. Because it is an exact identity, it also serves as a powerful estimation tool — any single unknown component, most often net migration, can be recovered as the residual once the others are known. | Cohort-Component Projection is the standard demographic method for forecasting future population size and age-sex structure by explicitly tracking births, deaths, and migration for each age-sex cohort across discrete time steps. Systematically formalized in the textbook literature by Preston, Heuveline, and Guillot (2001), the method builds on foundational actuarial and demographic work dating to the early twentieth century and remains the workhorse technique used by national statistical offices and international organizations worldwide. |
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