Patrick Carvalho, writing for the Centre of Independent Studies, in his piece 50 Shades of Youth Unemployment, makes some very useful and constructive contributions to the analysis of Australian Youth Unemployment.
He points out the difficulties of single measures such as the Unemployment Rate, and the definitional vagaries [my interpretation] of policy responses to broad rather than deep analysis.
As I follow these figures closely, I am ever-more haunted by what clearly appears to me to be the growing risk of de-coupling or structural-separation of the youth employment/labour-market trends from the rest of the market. I often hear the recent words of Ken Henry, former Secretary of the Australian Treasury, when his forward assessment of youth unemployment led him to observe that he believed we were witnessing the “capability deprivation” of a generation and was moved to say:
“I believe there is a special case for taking an interest in youth unemployment. Australia simply cannot afford this level of youth unemployment.”
As a rule-of thumb, the International Labour Organisation [ILO] in their Key Indicators of Labour Markets [KILM] suggest that where the unemployment rates are closer together (e.g. a ratio of 2), unemployment is generally considered to be a problem for the whole population.
Where the ratio is 3.5 or higher, young people are thought to be disproportionately impacted by unemployment.
I work with a number of communities/regions where that number is at or well above the 3.5 ratio yet it is unclear that policy responses in these jurisdictions are able to ascertain or respond to these variations.
Carvalho wisely suggests analysis of the issue [ Youth Unemployment] should also include measurements of young people not in education, employment or training (NEETs). In particular, it is important to separate the active NEETs (unemployed youth not studying/training) and inactive NEETs (completely outside the labour market and education/training).
He suggests measures such as the youth unemployment-to-population ratio, which considers the number of jobless youth as a percentage of the respective young population.
My graph below supports his contention.
Youth Employment Ratio
- Employment-to-population ratios for young people appear to have collapsed since the GFC
- 15-19 Year Old ratios are abysmal, Males 41.6% Females 45.1%
- 15-24 Year Olds, slightly better at approx 57.8%
His summary analysis is that:
The important message is that there is no single statistics able to fully inform about the youth unemployment subject. The issue comes in many shades, shapes and sizes, with no black-and-white, one-size-fits-all picture.
What’s to be done?
Caveat: I am currently a contractor for a number of the Networks I refer to below.
Clearly, more targeted and focussed collection and analysis of specific, place-based data is critical for such assessments. The role of statutory bodies such as the ABS are MORE critical now than they have ever been.
PLACE is the central policy challenge here [and always has been in my view], not SECTOR.
This produces immediate definitional and jurisdictional challenges for government and requires expertise and mediation at scales that are generally not suited to central policy. Accountability is ultimately diluted.
Place-based planning networks are critical for these developing challenges. The original Kirby Report [August 2000] said it best when the panel suggested Victoria should:
…develop collaborative approaches towards planning and improved delivery of post-compulsory education and training programs and services.
This ultimately led to the establishment of the Local Learning and Employment Networks in Victoria and has proven valuable and effective for more than a decade. It is perhaps still a greatly untapped resource when it comes to strategic, place-based policy responses because it is the ONLY structure that combines all of the LOCAL stakeholders from across the employment, education and community sectors.
A more strategiclly-engaged and pro-active collaboration between all three jurisdictions of Government [Local, State and Federal], centred around such networks, combined with the bold use of detailed data and genuine locally-filtered FUNDING frameworks would be one of the most efficient ways to build on existing strengths and respond to Carvalho’s challenge to respond to the complex “shades, shapes and sizes” of the problem.