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On Cohen's stochastic generalization of the strong ergodic theorem of demography

Published online by Cambridge University Press:  14 July 2016

Kenneth Lange
Kenneth Lange*
Affiliation:
University of California, Los Angeles
*
∗ Postal address: Department of Biomathematics, School of Medicine, University of California, Los Angeles, CA 90024, U.S.A. Research supported in part by the University of California, Los Angeles and NIH Special Research Resources Grant RR-3.
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Abstract

Cohen has generalized the classical strong ergodic theorem of demography to a stochastic setting. In this setting population projection matrices are chosen according to some homogeneous Markov chain. If this Markov chain converges to the same long-run distribution regardless of its starting point, then one can define an induced Markov chain on the product space of projection matrices and age structure vectors that also has a long-run distribution independent of its starting point. The present paper gives more natural conditions under which Cohen's result holds.

Keywords

DEMOGRAPHYAGE STRUCTUREMARKOV CHAINERGODICCONVERGENCE IN DISTRIBUTION
Type
Research Papers
Information
Journal of Applied Probability , Volume 16 , Issue 3 , September 1979 , pp. 496 - 504
Copyright
Copyright © Applied Probability Trust 1979 

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