Authors: G.A.Meagher and Felicity Pang
A primary motivation for providing education and training is to equip the workforce with the skills it requires to meet the needs of industry. Furthermore, as training takes some time to accomplish, the training that is provided today must be targeted at the needs of industry at some time in the future. Hence workforce development requires access to a labour market forecast of some kind.
Formal labour market forecasts produced using an economy-wide model have several features which ought to make them attractive to policy makers. For example, they embody modern economic theory and large amounts of relevant economic data, they are comprehensive and coherent, and they can be updated regularly at reasonable cost. Yet many training professionals are reluctant to avail themselves of formal forecasts, preferring instead to rely on more informal methods such case studies, graduate destination surveys and surveys of business opinion. Formal forecasts are held to be too unreliable for most policy purposes. It is argued in this paper that the reluctance is misplaced and, indeed, that it constitutes an unnecessary barrier to efficient workforce development.
The discussion draws on a detailed analysis of the performance of a labour market forecasting system built around the MONASH applied general equilibrium model of the Australian economy. Using forecasts published over the last thirteen years, the paper reviews their accuracy for industries, occupations and regions, and compares them with forecasts derived from time series extrapolation. The paper also reviews various qualitative arguments concerning reliability that have been advanced in the literature. Finally it considers the system adopted for allocating training resources in Australia, noting particularly that it fails to deliver a suitably articulated view of the future state of the economy which it is designed to service.
The paper also reviews various qualitative arguments that have been advanced against the use of formal labour market forecasts in workforce development. It suggests five propositions which should guide such considerations, but which are often ignored by the education and training community.
JEL classification: C53, D58, I28, J21, O56.
Keywords: labour market forecasting, computable general equilibrium, workforce development, skill mismatch, Australia.
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