Addressing structural inequality of employment redistribution policy targets. (June 2022) - Martinus, Kirsten; Biermann, Sharon
Abstract: Global trends of increased urbanisation have resulted in rising spatial inequality across cities, and land use challenges in providing adequate infrastructure, housing and employment for efficient, sustainable and productive urban systems. One policy response worldwide has been to use sub-regional quantity-driven job-housing targets, such as self-sufficiency, self-containment and jobs housing ratios, to redistribute jobs away from city central business districts into outer areas. To set these, city or state governments predict employment rises in often unclear and simplistic ways with no provision for job location differentials in type and residential access to opportunity. Despite the documented lack of success of such targets in addressing spatial inequality across a city, there is limited research into alternative tools. We address this gap by exploring a ratio to distinguish between strategic and population-driven jobs. Drawing on a case study of Greater Perth, Western Australia, we demonstrate rising spatial inequality despite over 60 years of land use policy measures to decentralise employment and equalise job provision across the city. Using Australian Bureau of Statistics (ABS) data, we classify and characterise 474 occupations into either strategic or population-driven jobs for the specific Greater Perth context. Our discussion highlights the importance of differentiating between job types, rather than targeting absolute growth, in order to implement more location-sensitive employment redistribution. Our findings highlight that disaggregated sub-regional job ratios may be a more appropriate land use planning tool to address spatial inequality than previous job-housing ratios. Highlights: Rising spatial inequality is often addressed via regional quantity-driven job-housing targets. Spatial inequality in Greater Perth, Western Australia persists despite long term use of targets. Using census data, we classify and characterise 474 occupations into strategic or population-driven. Highlights importance of differentiating job types rather than targeting absolute growth. Shows disaggregated job ratios may be more appropriate tools to address spatial inequality.