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Cohort Change Ratios (CCRs) have a long history of use in demography. In spite of their history of use, they appear, however, to have been overlooked in regard to a major canon of formal demography, stable population theory. In this paper, CCRs are explored as a tool for examining the idea of a stable population. In comparing the approach using CCRs to the traditional analytical approach, benefits and drawbacks are noted. The paper also introduces an Index of Stability, which is used in a regression model to estimate the number of years before the population in question becomes (approximately) stable. The regression model works reasonably well and, as such, provides something not available in the traditional analytical approach, which is an estimate of the time to (approximate) stability for a given population. Continuing the use of regression analysis, we also find that a regression model works reasonably well in estimating the intrinsic rate of increase from the initial rate of increase. We know that regression models are generally not as satisfying as analytical expressions in regard to describing relationships. It would be much more elegant to express the time to stability in terms of an analytic expression that incorporates the initial stability index (and probably other information about initial conditions) than it is to express the relationship in the form of a regression model. The same can be said about the relationship between the initial rate of increase in a given population and its intrinsic rate of increase. However, we also note that regression analysis has already been successfully employed in conjunction with stable population analysis, to include estimating intrinsic r from the proportional age distribution of a given population, mean generation length from a trial value of the intrinsic rate of increase, and the generation of model life table families and stable populations.

Exploring Stable Population Concepts from the Perspective of Cohort Change Ratios