Environmental Auditing, Public Finance, and Risk: Evidence from Moldova and Bulgaria
Bibliographic record
Abstract
The recent expansion of sustainability studies has reshaped corporate governance and public oversight with direct implications for financial exposure and risk management. In particular, environmental auditing generates decision-useful signals on environmental liabilities, remediation and compliance costs, and budgetary/fiscal risks that affect both corporate financing conditions (e.g., cost of capital) and public finance resilience. This study conducts a comparative examination of environmental auditing practices in Moldova and Bulgaria over 2020–2025, asking how audit mandates, coverage, and disclosure practices inform banks, insurers, investors, and budget holders. Using documents from national legal databases and supervisory portals, we apply descriptive content analysis across structural, substantive, and procedural dimensions, with special attention to financial-risk channels (contingent liabilities, sanction risk, value-for-money and procurement risks). We find that Bulgaria exhibits stronger institutional implementation capacity, while Moldova shows legislative innovation; in both cases, stronger transparency, public participation, and digital audit analytics are needed to quantify fiscal and enterprise-level ESG risks. Overall, this paper positions environmental auditing as a governance lever linking sustainability oversight to finance- and risk-related outcomes, aligning with focus on sustainable finance, ESG disclosure, and governance.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".