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Record W2890156283 · doi:10.4324/9780203084540-11

The poor performance of compulsory saving in Australia: superannuation and corporate governance

2012· book-chapter· en· W2890156283 on OpenAlexaboutno aff
Christine Brown, Deborah Ralston

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceBusinessAccountingFinance

Abstract

fetched live from OpenAlex

As at June 2010, superannuation funds under management in Australia totalled $1.23 trillion. This figure includes a large pool of compulsory savings contributed by the 85 per cent of the adult population now covered by the Superannuation Guarantee Contribution (SGC). While this pool of savings is only one pillar of the retirement system, which also includes the age pension, voluntary superannuation savings and personal savings, including home ownership, it is a critical pillar. An emerging theme in the recent Cooper Review (2009c), which was charged with examining the equity, simplicity and efficiency of the system, has been that, given the dependence of the Australian retirement system on compulsory superannuation saving, the heavy emphasis on defined contribution funds and the wide range of choices available, individuals tend to bear a higher level of investment and other financial risks than is the case in many other pension systems worldwide. Consequently, the need to maximize the safety and efficiency of the superannuation system takes on particular importance. In the final report, Cooper (2010) stated that improving governance practices and structures is the key to improving member outcomes. In this chapter, we focus on exploring potential factors behind the low returns on superannuation funds, such as differences in the structure of funds and the governance issues that can lead to higher costs and consequently lower subsequent rates of return to members. We develop a framework to explore possible links between governance models and their impact on agency and direct costs. Compulsory superannuation has been a feature of retirement savings in Australia since 1992 when the superannuation guarantee was introduced, requiring employers to make tax-deductible superannuation contributions on behalf of their employees. While compulsory superannuation contributions are made by employers, in the longer run it is better to think of them as ‘forced savings’ of employees out of wages rather than as involving higher labour costs for employers. From a base of 3 per cent, higher levels of compulsory contributions were phased in over a ten-year period, reaching the maximum of 9 per cent in 2002-3. As a result of this mandatory saving over the last decade, superannuation assets have trebled and, since 1994, the managed fund industry has enjoyed a compound growth rate of over 10 per cent per annum. Consequently, Australia now has almost $1.03 trillion invested in superannuation assets (Cooper Review, 2009a). As a consequence, Australia has the fourth largest funds management industry in the world and the largest in the Asia Pacific region. Apart from the depth of the savings pool, another key strength of the Australian system is its breadth of coverage. While the superannuation guarantee provides exemptions for some categories of employees,1 the current Australian superannuation system stands up well under international comparisons, with around 85 per cent of the working population having superannuation accounts (OECD, 2008). But despite the relatively broad coverage of superannuation and the large amount of funds invested, the adequacy of the Australian retirement system is not particularly strong.2 Indeed, in the Melbourne Mercer Global Pension Index (Melbourne Centre for Financial Studies, 2009), which provides an international comparison of the adequacy of benefits in 11 countries around the globe, Australia was ranked fourth behind the Netherlands, Canada and Sweden. Interestingly, all of these countries have a much larger average fund size and structures which are primarily defined benefit. In the recent Review into the Governance, Efficiency, Structure and Operation of Australia’s Superannuation System (Cooper Review), which reported in June 2010, a number of areas of weakness that have impacted on the performance of superannuation funds and, consequently, on the net returns of compulsory savings were identified. These include lack of scale, poor operational efficiency in manual back-office processes, fees that are too high, excessive complexity, poor reporting and disclosure, and a number of issues related to governance of superannuation funds. The Super System Review Final Report (hereafter Cooper, 2010)3 points out that system design and regulatory settings have not adequately ensured that member interests have remained paramount in a system that is compulsory and fully outsourced to the private sector. In terms of governance, the Cooper Review has identified a number of agency and structural issues which constrain the opportunity for member vigilance and give rise to a lack of incentive for agency vigilance. Cooper states (p. 2) that ‘improving governance practices and structures is the key to improving member outcomes’. Superannuation governance has been complicated over recent years by the move in funds from defined benefit (DB) to a defined contribution (DC) structure.4 In making this change, funds have exchanged the complexities of DB liabilities for complexities in the design and management of DC assets (Clark and Urwin, 2010). This is especially true for smaller DC funds which lack a depth of in-house expertise and therefore develop a complex web of outsourcing relationships to manage their portfolios. This chapter’s central focus is an examination of the governance structure of superannuation funds in Australia and how it relates to their performance. The remainder of the chapter is structured as follows. The development and performance of the Australian superannuation industry is outlined first. Then we investigate the governance problem and review the relevant literature, before considering the recent performance of Australian superannuation funds. Throughout, key recommendations from the Cooper Review inform the analysis. The superannuation industry in Australia The superannuation industry in Australia has developed considerably over the past decade. We first describe the rationale and development of the industry as a tool for establishing a pool of compulsory saving, before reviewing recent rates of return of superannuation funds, their expense ratios and their investment strategies in order to build a picture of relative performance of the different types of funds and the different benefit structures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.213
Teacher spread0.157 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2012
Admission routes1
Has abstractyes

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