The development of average price benchmarks involved the first national collection of information on VET qualification subsidies, fees and prices across Australia. The database forms a starting point from which to understand the variability in VET qualification pricing nationally for government subsidised qualifications and is the first step in the pathway to developing efficient prices for VET. This is one of the National Skills Commission’s (NSC’s) functions as set in legislation (see Appendix A).
The NSC commissioned Deloitte Access Economics to assist with this work. The collection and analysis focused on 50 priority qualifications (identified by 2018 government funded enrolments) for standard students (defined as located in a metropolitan area, not Aboriginal or Torres Strait Islander, has English as a first language, does not have a disability and is not long-term unemployed). The project was undertaken from March to August 2020.
Approach and data sources
Both publicly available information on subsidies, fees and prices, and data sourced through engagement with state and territory agencies were used in the construction of the database. In most cases, and unless specifically requested or instructed otherwise, publicly available information or the ‘most standard’ information available was used. Where fee data were not available, fees were collected directly from provider websites for 50 priority qualifications.
State and territory agencies were consulted to understand the approaches taken around subsidy, fee and price setting; and to request more detailed data as needed.
The database has over 17,000 observations of either subsidy, fees and/or prices for government funded qualifications. This includes observing subsidy and/or fee arrangements for over 2,000 distinct qualifications and skill sets. No observations were collected for fee-for-service delivery. An excerpt of the information collected in the database is shown in Figure 1 (noting some identification columns have been removed for the purpose of this extract).