Financial structure of PPPs deals post‐GFC: an international perspective
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the implications of the Global Financial Crisis (GFC) on Public Private Partnership (PPP) markets around the world. Specifically, it aims to highlight the extent of over reliance on debt finance, as well as the conditions needed to attract enhanced levels of institutional investment into key infrastructural provision. Design/methodology/approach Quantitative insight for the paper is derived from the Infrastructure Online Database. TheInfrastructure Journal(IJ) Online Database profiles PFI/PPP deals around the world depicting the key actors involved, as well as the capital value of deals and the financial structures applied in terms of debt, equity and Multilateral and Government Finance. The quantitative insight derived from theIJdatabase is complemented by interview evidence and forum‐based discussion. In total, 38 interviews were conducted with a diverse range of key stakeholder groupings from across the public and private sectors, including government advisers, client side representatives (Health and Education sectors), contractors, financiers and FM providers. Interviewees were drawn from five key PPP markets at different stages in the maturity cycle, namely, Australia, Canada, India, the UK and the USA. In addition to the interviews, three forum‐based discussions were undertaken as part of the investigation exploring the key themes to emerge from the interviews from multi‐stakeholder perspectives. Findings The findings from the study highlight a number of inherent deficiencies in the PPP model, including the over reliance on private sector debt. Additionally, the research profiles the extent and form of national government interventions in PPP markets around the world, highlighting the need for a more innovative, sustainable and balanced funding frameworks for essential infrastructure conducive to the next economic/financial cycle. Originality/value This study is distinct in that it examines the cross‐jurisdictional implications of the global financial crisis on PPP markets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 source (direct Gemma or distilled Codex), 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".