Simulating the Effect of Population Aging and Government Policies on Economic Growth in the Context of an Overlapping Generation Model
In this paper, the effect of population aging on economic growth in a closed economy in which the element of human capital is endogenously formed is simulated. For this purpose the computable generalized Diamond overlapping generation’s model are used for a period of 50 years. First, the dynamic eff...
Main Authors: | , , , , |
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Format: | Article |
Language: | fas |
Published: |
Allameh Tabataba'i University Press
2022-06-01
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Series: | فصلنامه پژوهشهای اقتصادی ایران |
Subjects: | |
Online Access: | https://ijer.atu.ac.ir/article_14058_30a13d4be9095143e2f4c077df8fdb2a.pdf |
Summary: | In this paper, the effect of population aging on economic growth in a closed economy in which the element of human capital is endogenously formed is simulated. For this purpose the computable generalized Diamond overlapping generation’s model are used for a period of 50 years. First, the dynamic effect of aging on macroeconomic variables, especially economic growth, are simulated in the baseline scenario (current state of the Iranian economy).Then the dynamic effects of public policies under different scenarios of human capital and pensions ratios on economic growth for a period of 50 years are simulated. The results of the model showed that the government's general policies to increase human capital increase the share of skilled labor (effective labor) and therefore have a growth effect. At values of public policy tools above the baseline scenario(industrial status), the effect of productivity on aging prevails and long-term growth increases.In addition, the results showed that increasing the ratio of pensions to the level of developed countries encourages demand-based economic growth, but has a level effect and does not change long-term growth. The results show that increasing aging, if combined with government policies to promote human capital, can potentially offset the negative impact of aging on growth. |
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ISSN: | 1726-0728 2476-6445 |