Private Assets Ascending: Public Pension Capital and New Financial Market Forces
Bibliographic record
Abstract
The authors of this article, Nicolas Firzli, WPC, David Weeks, AMNT, and the Hon. Nick Sherry, SEF, co-chaired the main financial roundtable during the COP21/Paris Agreement conference: the Paris Climate Finance Roundtable (CFR) , alongside Dr. Jeffrey Sachs, Director, Center for Sustainable Development (CSD), Columbia University. This high-level conference spearheaded the twin notions that a “climate smart future is an imperative for meeting the Sustainable Development Goals” and that “the secular quest for yields” fuelled by monetary complacency, combined with “the coming Sino-American rivalry”, would eventually accelerate the deployment of pension and sovereign wealth fund (PSWF) capital towards “private market assets” such as real estate, infrastructure, private equity, venture capital and farmland. As part of the preparatory work (‘travaux preparatoires’) of the 2021 ESG Summit and G20 Pensions Forum held later this year in Paris (28 & 29 October 2021), on the sidelines of the G20 Summit (Rome Summit, 31 October 2021), the authors sat with experts from key jurisdictions, including the United Kingdom, Singapore, the United States, the European Union (EU), Australia, China and the MENA area, to take stock of and discuss key issues such as ‘the rise of private market assets’, the ‘Biden Infrastructure Investment Plan’ in the United States, the G7's ‘New Global Infrastructure Initiative’ (NGII) focusing on the Indo-Pacific area, Centra Asia and Africa, and, more generally, the rise of fiduciary capitalism in the ‘Post-Covid Era’. The authors also discuss the latest version of their Private Market Assets Matrix (PMAM), also called Infrastructure and Private Markets Investment Matrix (IPMIM), an original strategic assessment tool first developed at the start of the previous decade by North American and EU experts. This updated and expanded version of the PMAM matrix was first presented by Firzli at the ‘Frontiers in Innovative Finance’ session (24 May 2021) of the World Bank Infrastructure Forum 2021, held in Washington DC and digitally (17 – 27 May 2021). The strategic matrix “allows investors and policy makers to map out the future of institutional investment by visualising dynamically the proportion of assets allocated to infrastructure (Y axis) and non-listed assets overall (X axis) for a cross-section of pension funds perceived as highly representative of future trends.” The authors also show why large institutional asset owners could double their allocation to such assets in the next four years, shifting hundreds of billions of dollars annually towards infrastructure assets domestically and accelerating the investment flows coming into the United States from cash-rich Canadian, Northern EU, Singaporean, Gulf Arab and Australian pension and sovereign wealth funds. As a consequence, private market assets under management may grow by up to 20% per annum in the coming years (2021 – 2025), more than double the current rate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".