TY - JOUR
T1 - Not in Employment, Education, or Training (NEET)
T2 - More than a Youth Policy Issue
AU - Mitrou, Francis
AU - Haynes, Michele
AU - Perales, Francisco
AU - Zubrick, Stephen R.
AU - Baxter, Janeen
PY - 2021/1/1
Y1 - 2021/1/1
N2 - Introduction Australians who are Not in Employment, Education or Training (NEET) and receive income support span a wide spectrum of working ages. Australian research has concentrated on NEETs aged 15-29 years, in line with international standards. This paper investigates extending the NEET concept to include all working age persons 15-64 years and the value added to welfare policy through analysis of a new linked dataset. Methods An observational study design was implemented with individuals aged 15-64 years recorded as receiving Department of Social Services (DSS) income support payments from September 2011 being linked with Australian Bureau of Statistics (ABS) Census data from August 2011 to create a linked dataset for analysis. Descriptive analyses were undertaken of NEET status by Census sociodemographic characteristics, and we modelled the adjusted likelihood of NEET status by Census demographics. Results Some 1.37 million or 45.2% of linked DSS payment recipients qualified as NEET. Of NEETs, more than twice as many were female, nearly half were aged 45-64 years, and under 1-in-5 were aged 15-29 years. Multivariate analyses showed that NEETs were more likely to be older, have low educational attainment, have a disability, and to be Indigenous. Conclusions Young NEETs aged 15-29 years represented less than 20% of linked DSS payment recipients classified as NEET, suggesting that standard NEETs reporting neglects information on around 80% of the working age NEET population in Australia. Combined with other demographic insights, these results have implications for welfare policy, and indicate a wider range of demographics should be considered under the NEET classification. This may also have implications for Organisation for Economic Co-operation and Development (OECD) reporting. © Research in Plant Disease 2021.
AB - Introduction Australians who are Not in Employment, Education or Training (NEET) and receive income support span a wide spectrum of working ages. Australian research has concentrated on NEETs aged 15-29 years, in line with international standards. This paper investigates extending the NEET concept to include all working age persons 15-64 years and the value added to welfare policy through analysis of a new linked dataset. Methods An observational study design was implemented with individuals aged 15-64 years recorded as receiving Department of Social Services (DSS) income support payments from September 2011 being linked with Australian Bureau of Statistics (ABS) Census data from August 2011 to create a linked dataset for analysis. Descriptive analyses were undertaken of NEET status by Census sociodemographic characteristics, and we modelled the adjusted likelihood of NEET status by Census demographics. Results Some 1.37 million or 45.2% of linked DSS payment recipients qualified as NEET. Of NEETs, more than twice as many were female, nearly half were aged 45-64 years, and under 1-in-5 were aged 15-29 years. Multivariate analyses showed that NEETs were more likely to be older, have low educational attainment, have a disability, and to be Indigenous. Conclusions Young NEETs aged 15-29 years represented less than 20% of linked DSS payment recipients classified as NEET, suggesting that standard NEETs reporting neglects information on around 80% of the working age NEET population in Australia. Combined with other demographic insights, these results have implications for welfare policy, and indicate a wider range of demographics should be considered under the NEET classification. This may also have implications for Organisation for Economic Co-operation and Development (OECD) reporting. © Research in Plant Disease 2021.
UR - http://www.scopus.com/inward/record.url?scp=85117792600&partnerID=8YFLogxK
U2 - 10.23889/ijpds.v6i1.1676
DO - 10.23889/ijpds.v6i1.1676
M3 - Article
C2 - 34589617
SN - 2399-4908
VL - 6
JO - International Journal of Population Data Science
JF - International Journal of Population Data Science
IS - 1
M1 - A3
ER -