5900.0.00.003 - University output measures in the Australian National Accounts: experimental estimates, 2008 to 2017  
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Overview of methodology

The output of public universities is comprised of two broad streams: (a) teaching output; and (b) research output. Research output can be sub-divided into: (i) research degree completions; and (ii) research funded by government and industry. The existing ABS measure of the output of public universities is based on student enrolment numbers, and is therefore a measure of teaching output alone. The experimental estimates proposed in this paper integrate all three streams of output (one teaching and two research) and incorporate a quality dimension via the application of expenditure weights.

Changes in the volume of output for each of these streams of activity can be measured by compiling a volume index. A volume index for a particular product reflects the change in how much more or less of that product has been produced from one period to the next, with the impact of price changes removed. A volume index that represents an aggregate of all products produced (e.g. total output for an economy) requires a method to weight the products together.

In the case of public universities, the operating costs incurred by each university are used as weights. This type of expenditure data is used to weight the outputs instead of prices, which are not meaningful in the context of non-market production because prices are not deemed to be economically significant.

The intuition underlying this is that cost differences across the sector implicitly convey information about the relative quality of universities. A university that incurs greater costs in producing its output (perhaps by paying higher salaries to attract the best academic staff, or by enrolling fewer students per lecturer) is assumed to offer a higher quality service, and therefore its activity carries a higher weight in aggregation. In other words, universities that spend more on each unit of teaching and/or research effectively produce higher quality outputs. This intuition is discussed in depth in Schreyer (2010) and Diewert (2008, 2010).

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