While countries around the world have experienced unprecedented shifts in their population age structures over the last 70 years, it has only really been over the last 20 years that research into the impact of the structure of the population on the economy has gained momentum. Analytically, it is the recognition that engagement in the economy and the resulting economic flows between individuals vary with age that underpins this impact: children consume more than they produce; prime working-age cohorts produce more than they consume, transferring surpluses to others or saving them for old age; and the elderly use transfers from others, asset income or dissaving to finance their consumption given low levels of labour income. These economic flows at each age are quantified by the National Transfer Accounts (NTA) methodology, providing a view of the so-called generational economy and allowing us to see how different age groups produce, consume, share, and save resources at a given point in time. NTAs are constructed from a variety of data sources—including household survey data, administrative data, national accounts data and population data—to be consistent with National Accounts and can be thought of as age-disaggregations of various national accounting aggregates. NTAs have been constructed for a growing number of countries around the world, with South Africa one of the first countries on the African continent to have constructed NTAs. This thesis utilises the NTA methodology to construct partial or full accounts for South Africa for five years between 1995 and 2015. These accounts are used to analyse three aspects of the generational economy or economic lifecycle. First, the estimates are used to estimate the magnitude of South Africa’s demographic dividend, the potential economic benefits that arise due to the changing population age structure as the working-age population grows relative to the total population. Second, the NTA estimates for 2015 are disaggregated by race to assess differences in the economic lifecycle across these groups, which are used as proxies for socioeconomic status, and to assess the implications of high levels of inequality on the estimates themselves and on projections of the profiles into the future. Finally, by incorporating time use data to estimate time allocations to unpaid housework and care activities for men and women across the lifecycle, the exclusion of non-market services from the national accounts production boundary, and therefore from NTA, is addressed, making it possible to properly assess the full economic contributions of men and women across the life course.
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