This statistical indicators publication sets out NSW regional labour force trends on an annual basis for the period January 2008 to January 2013. It uses data from the ABS publication, Labour Force, Australia, Detailed – Electronic Delivery, Jan 2013, which starts in November 2007. Following the methodology adopted by the Department of Education, Employment and Workplace Relations in its Labour Market Information Portal, all the data presented are three-month averages. While the commentary pays particular attention to changes between January 2008 and January 2013, it is worth noting that figures may fluctuate substantially across the period.
There are 13 labour force regions (LFRs) in metropolitan NSW and 6 in regional NSW, two of which are split in two by the ABS: the Hunter LFR is split into the Hunter (excl. Newcastle) region and the Newcastle region; and the Illawarra LFR is split into the Illawarra (excl. Wollongong) region and the Wollongong region. A map of the regions precedes the labour force indicators. Data is provided for each of the regions along with State, metropolitan NSW and regional NSW figures for comparative purposes.
Six labour force indicators are included in this publication: total employment; participation rate; full-time employment; part-time employment; unemployment; and the unemployment rate. While these indicators could have been broken down across several demographic variables, only gender has been selected for the purposes of this publication, and then only for selected indicators: the participation rate; part-time employment figures; and the unemployment rate.
It is important to note that the data source – the ABS Labour Force Survey – is based on a sample of private dwellings (approximately 29,000 houses, flats etc) and non-private dwellings, such as hotels and motels. The sample covers about 0.33% of the Australian civilian population aged 15 years or over. The primary purpose of the survey is to provide labour force estimates for the nation and, secondarily, for each State and Territory. Consequently, regional-level data may be more likely to be subject to errors.