Roles and Practices in Accounting: Did Fair-Value Cause the Global Financial Crisis?
Bibliographic record
Abstract
This paper debates how did fair-value accounting (FVA) that were deeply affected by the global financial crisis (GFC). The GFC that started in advanced economies spreading to emerging markets and low-income countries, which has been affected in the middle of 2007 and into 2009, as have various empirical studies which have examined the role of FVA in the GFC. In this paper, using the quantitative methodology where value-relevance of fair value estimates of assets and liabilities reported under FVA provided by FAS 157, in terms of a simple theoretical and empirical analysis literature framework. This empirical study proposed that this is not a normal cyclical crisis of capitalism but a global crisis, which requires a change in the management policy to be tackled with new regulatory frameworks for financial institutions in order to stimulate economic activities. In other words, FVA may have amplified the crisis. These findings could be fruitful and helpful for outside users of accounting reports and also for regulators and legislators in their attempts to constrain the incidence of earnings accounting practises and to enhance the quality of accounting information. Future research is needed to meet up-to-date information regarding the nature of capital markets and financial institutions. This requires a new theory of economics; for instance, a change from equilibrium theory to reflexivity theory which requires a change in the underlying model of the economic activity framework and valuation challenges that arise from the use of FVA in financial reporting.
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 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 | 0.025 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.030 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".