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The Medium Term Outlook for Labour Demand: An Economy Wide Assessment

Listed author(s):
  • G.A. Meagher

This paper presents a detailed assessment of the medium term outlook for the demand for labour in Australia. Forecasts are reported for employment by industry, by occupation, by State and Territory, by hours worked and by skill level. The forecasts are driven, in the first instance, by a fully articulated view about the outlook for the macroeconomy. This macro view is then combined with projections for various industry specific variables prepared by relevant expert organisations. Coherence between the different sources is ensured by incorporating them in a single simulation using the MONASH model, a large applied general equilibrium model of the Australian economy. In deriving the forecasts, attention has been paid to the effect of technological and social change on the structure of the economy in recent years, and to the implications of that change for future labour demand. The paper deals particularly with technical change which affects the distribution of employment across occupations within industries, and the distribution across different categories of hours worked within occupations. Tables are included to illustrate how the forecasting system can be interrogated to reveal * the contributions of various industries to employment growth for a selected occupation, and * the relative importance of output growth, capital growth and labour saving technical change to industry employment growth. The paper concludes with a review of some issues associated with making a proper assessment of the forecasts.

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Paper provided by Victoria University, Centre of Policy Studies/IMPACT Centre in its series Centre of Policy Studies/IMPACT Centre Working Papers with number op-87.

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Date of creation: Apr 1996
Handle: RePEc:cop:wpaper:op-87
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  1. Adams, Philip D. & Dixon, Peter B. & McDonald, Daina & Meagher, G. A. & Parmenter, Brian R., 1994. "Forecasts for the Australian economy using the MONASH model," International Journal of Forecasting, Elsevier, vol. 10(4), pages 557-571, December.
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