Vertaile menetelmiä

	Multiregional Demography	Net Migration Rate
Tieteenala	Väestötiede	Väestötiede
Menetelmäperhe	Process / pipeline	Process / pipeline
Syntyvuosi	1975	1976
Kehittäjä	Andrei Rogers	Classical vital-statistics measure (formalized by Shryock & Siegel)
Tyyppi	Matrix framework for multiregional population dynamics with migration	Rate of net population change due to migration per unit population
Alkuperäislähde	Rogers, A. (1975). Introduction to Multiregional Mathematical Demography. John Wiley & Sons, New York. ISBN: 9780471730354	Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 9781557864512
Rinnakkaisnimet	Multiregional Population Analysis, Multiregional Life Table, Rogers Multiregional Model	Net Migration Ratio, Crude Net Migration Rate, Net Migration per 1000
Liittyvät	4	4
Tiivistelmä	Multiregional demography extends the classical tools of mathematical demography — the life table, the Leslie matrix, and stable-population theory — from a single closed population to a system of interconnected regions linked by migration. Developed by Andrei Rogers, it tracks people not only by age but by region of residence, modeling birth, death, and interregional movement simultaneously. The result is a unified matrix framework that yields multiregional life tables, projections, and stable regional population shares, making it the foundation for analyzing how migration shapes the size and distribution of populations across space.	The net migration rate expresses the net effect of migration on a population's size as a rate: net migration — in-migrants minus out-migrants over a period — divided by the population at risk, conventionally stated per 1000 people. It is the migration counterpart to the rate of natural increase and a standard component of population accounting. Because directional migration flows are often poorly recorded, net migration is frequently not counted directly but estimated as a residual from the demographic balancing equation or by comparing surviving cohorts across two censuses.