Reframing policy responses to population aging in Iran

Gietel-Basten, S., Marois, G. ORCID:, Torabi, F., & Kabiri, K. (2024). Reframing policy responses to population aging in Iran. Genus 80 (1) e8. 10.1186/s41118-023-00210-z.

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Iran is aging rapidly and is expected to see negative population growth rates later this century. This change is generating significant concern for policymakers, whose response is to seek ‘demographic solutions’ to these issues: raise the fertility rate, decrease the divorce rate, and promote marriage among young people. Part of these policies has entailed curtailing access to free family planning services. This ‘call and response’ approach is unlikely to succeed in its stated aim, as it over-simplifies the real challenges of population aging as well as the multiple dimensions of population change. Such policies derive from simple representations of demographic change, most notably using the old-age dependency ratio. Using a microsimulation model, this paper suggests that increasing Iran’s currently low female labor force participation and translating educational gains into rising productivity is a more effective means of responding to the challenges of population aging, even under low fertility conditions. The advancement on previous such microsimulation exercises lies in the fact that this study explicitly considers the comparison between raising fertility and increasing female economic empowerment to offset population aging in a setting characterized by an overt pronatalist policy system. In tandem with reforming stressed institutional systems (such as the pension system), releasing the full potential of Iran’s existing (and future) human capital—especially of its women—is a far more effective policy direction than fertility-promoting policies.

Item Type: Article
Uncontrolled Keywords: Iran, Policy, Fertility, Projections, Female labor force participation, Human capital
Research Programs: Population and Just Societies (POPJUS)
Population and Just Societies (POPJUS) > Multidimensional Demographic Modeling (MDM)
Depositing User: Luke Kirwan
Date Deposited: 29 May 2024 07:59
Last Modified: 29 May 2024 07:59

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