Two-Sex Demographic Models
AbstractClassical stable population theory, the standard model of population age structure and growth, is ill suited to addressing many issues that concern economists and demographers because it is a "one-sex" theory. This paper investigates the existence, uniqueness, and dynamic stability of equilibrium in the birth matrix-mating rule model, a new model of age structure and growth for two-sex, monogamously mating, populations. The paper shows, by means of examples, that the birth matrix-mating rule model can have multiple nontrivial equilibria and establishes sufficient conditions for uniqueness. It generalizes a theorem of W. Brian Arthur to nonlinear systems and uses it to establish sufficient conditions for local dynamic stability. Copyright 1990 by University of Chicago Press.
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Bibliographic InfoArticle provided by University of Chicago Press in its journal Journal of Political Economy.
Volume (Year): 98 (1990)
Issue (Month): 2 (April)
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Other versions of this item:
- Pollak, R.A., 1990. "Two-Sex Demographic Models," Discussion Papers in Economics at the University of Washington 90-07, Department of Economics at the University of Washington.
- Pollak, R.A., 1990. "Two-Sex Demographic Models," Working Papers 90-07, University of Washington, Department of Economics.
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- Rune Johansen & John K. Dagsvik, 1999. "The Dynamics of a Behavioral Two-Sex Demographic Model," Discussion Papers 247, Research Department of Statistics Norway.
- Sudeshna Maitra, 2006. "Population Growth and Rising Dowries: The Long-Run Mechanism of a Marriage Squeeze," Working Papers 2006_9, York University, Department of Economics.
- Robert A. Pollak, 2004.
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- Eugene Choo & Aloysius Siow, 2006. "Estimating a marriage matching model with spillover effects," Demography, Springer, vol. 43(3), pages 463-490, August.
- Aloysius Siow & Xiaodong Zhu, 2002. "Differential Fecundity and Gender-Biased Parental Investments in Health," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 5(4), pages 999-1024, October.
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