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Despite a significant period of strong economic and jobs growth nationally, there is well-established evidence in Australia that the proceeds of this growth have not been shared equally, either between places or between individuals. Empirically, it is well known that particular socioeconomic groups have a higher risk of unemployment and it has become equally well established that there are particular geographic patterns of labour market disadvantage that suggest that local geographic context is also important. What is not well understood are the ways in which phenomena at the geographic level are associated with individual-level characteristics and other social contexts in ways that negatively impact on a range of social outcomes, including unemployment. The present paper specifically addresses this issue by using a multi-scalar approach and using survey data from the Housing, Income and Labour Force Dynamics Australia (HILDA) survey and aggregate level census data to model unemployment risk. The paper argues that to better understand unemployment and to add to sound policy development, approaches that incorporate a variety of contexts, including the impact of local geographies, are important. [ABSTRACT FROM AUTHOR]