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This paper briefly analyses the shifts in economic theory that have moved policy makers from unambiguously pursuing full employment to the current state where full employability is justified as being optimal. We also explore how these theoretical developments translated in practice, culminating in the 1994 OECD Jobs Study, which eschewed a role for macroeconomic policy in reducing unemployment. The final sections of the paper outline an alternative view of macroeconomic theory and policy opportunities. We argue that a central plank in modern macroeconomic policy settings should be the introduction of employment guarantees, which we term the Job Guarantee (JG).

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This paper continues our work focused on developing a new socio-economic geography for Australia such that the chosen spatial aggregation of data is based on an analysis of economic behaviour. The underlying hypothesis is that the development of a geographical classification based on underlying economic behaviour will provide new insights into critical issues of regional performance, including unemployment differentials, the impact of industry, infrastructure and changes in local public expenditure on local labour markets. As a precursor to detailed work on the 2006 Census of Population and Housing data, we establish the proof of concept in this paper of the Intramax methodology using 2001 Journey-to-Work data from the Australian Bureau of Statistics (ABS) for the state of New South Wales. The functional regionalisation generated by the Intramax method is then tested using ABS labour force data. We compare 2001 ABS Census of Population and Housing data aggregated by the ABS labour force regions to the same data aggregated using our functional regions. The results demonstrate the potential value of this technique for the development of a new geography. KEY WORDS spatial aggregation; functional economic areas; intramax algorithm; spatial clustering IntroductionThis paper continues our work focused on developing a new socio-economic geography for Australia such that the chosen spatial aggregation of data is based on an analysis of economic behaviour (see Watts et al. 2006). The underlying hypothesis that has motivated this work is that the development of a geographical classification based on an analysis of labour market behaviour will provide new insights into critical issues of regional performance, including unemployment differentials, the impact of industry, infrastructure and changes in local public expenditure on local labour markets. A systematic understanding of levels of interaction between neighbouring areas, will facilitate an assessment of the adequacy of the administrative geographical

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