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  • Overview

    We use an estimation model that applies averages for various self-managed super fund (SMSF) quantities to the entire population of active SMSFs, to arrive at estimated totals.

    Both the Australian Prudential Regulation Authority (APRA) and the Australian Bureau of Statistics (ABS) agree with the model methodology. However, in using or presenting this data it is important to stress that it is a statistical estimate.

    Data sources

    The primary source of data is the SMSF annual return. The key limitations associated with these returns are their frequency (annual) and their currency – the returns are due some months after the end of the financial year.

    Number of SMSFs

    A significant figure for estimating SMSFs statistics is the number of funds. This is obtained from the formula:

    Number of funds =

    (Number of SMSFs established with us)
    − (Number of. SMSFs that have notified us they have wound up.)

    This figure will be subject to historical revisions due to late notice of both establishments and wind-ups. A potential concern is SMSFs winding up and failing to notify us, although it is thought the compulsory nature of the annual returns will help minimise this.

    Newly established funds

    The characteristics of SMSFs in their first year of establishment ('new funds') and older funds ('continuing funds') are significantly different, especially with regard to 'flows' into and out of the fund, such as contributions, transfers and benefits. The two categories are treated separately, and then combined, in the production of estimates.

    Assets and liabilities

    Total assets for the June quarter each year is estimated by referring to return data for that year, when sufficient data becomes available, using the formula below.

    Total assets =

    (Number of new funds × Average value for new funds)
    + (Number of continuing funds × Average value for continuing funds)

    The calculation for total assets or liabilities for other quarters must take into account growth over the period as well as monies flowing into and out of SMSFs. For example, total assets or liabilities for non-June quarters are obtained by estimating the changes for each asset or liability type from the most recent June quarter, using the following formula:

    Assets =

    (Previous quarter assets)
    + (Previous quarter assets × Investment return for each asset type)
    + (Apportionment of 'flows'*)

    * For more information, see:

    Contributions, benefits, transfers and expenses.

    Estimated investment return for each asset type is based on indices and detailed below:

    Appendix A

    Net assets

    Net assets for each quarter are estimated using the following formula:

    Net assets =

    (Total assets)
    − (Borrowings)
    − (Other liabilities)

    Contributions, benefits, transfers and expenses

    Monies flowing into or out of an SMSF increase or decrease the value of assets held in that SMSF. The values of contributions (member and employer), transfers (inward and outward), benefit payments, and operating expenses are calculated using the formula above (where Total assets represent the quantity being estimated).

    Total net flows are then calculated as:

    Net flows  =

    (Member contributions)
    + (Employer contributions)

    + (Inward transfers)
    − (Outward transfers)
    − (Benefit payments)
    − (Operating expenses)

    This total is essentially divided by four to provide an estimated quarterly figure. Adjustments are made to account for new funds entering the system, as well as funds that wind up, with ‘net flows’ then apportioned appropriately across the different types of assets and liabilities.


    Similarly, for the estimated number of members, separate averages are calculated for new and continuing funds from the return data, using the formula below:

    Number of members =

    (Number of new funds × Average members of new funds)


    (Number of continuing funds × Average members of continuing funds)

      Last modified: 10 Dec 2018QC 21271