Author: G.A. Meagher
In a recent report, the Organisation for Economic Cooperation and Development has argued that certain key developments, including globalisation, population ageing and the diffusion of information technologies, are causing a shift in the demand for labour in modern advanced economies. Demand is thought to be moving away from relatively low-skilled agricultural and production occupations in favour of highly-skilled professional, technical, administrative and managerial occupations. Moreover, rising turnover in the labour market is tending to increase the rate at which existing skills are rendered obsolete. Hence workers in OECD countries are coming under mounting pressure to adapt and enhance their skills on an ongoing basis; that is, today's workers must participate in lifelong learning.
This paper investigates the quantitative evidence for the proposition using, as a case study, the distribution of employment across occupations in Australia. Three changes in this distribution are considered: the change that actually occurred between 1986-87 and 1994-95, a forecast of the change that is likely to occur between 1994-95 and 2002-03, and an estimate of the change that will result from trade liberalisation proposals advanced by the Asia Pacific Economic Cooperation forum. In each case the change in the occupational distribution is used to infer the effect on the demand for labour differentiated by qualification level, qualification field and age group. Unlike much of the structural analysis that accompanies discussions of lifelong learning, the approach here is comprehensive. The analysis is not restricted to occupations thought on a priori grounds to have a particular affinity to lifelong learning, but considers changes in employment across all occupations. Hence the role of particular occupations, such as those associated with information technology, for example, are able to be placed in a an economy-wide perspective.
The analysis reveals that the factors driving the demand for labour are numerous and diverse, and suggests that generalisations and "stylised facts" are likely to be of only limited usefulness in determining training priorities.
JEL Classification: C68, D58, E47, F17, J21, I20, J23.
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