Private sector influence and the international political economy of banking regulation: The formation of the Basel II Accord 1998-2004.
Bibliographic record
Abstract
This study undertakes an empirical investigation of private sector influence over transnational financial regulatory policymaking. I examine the relationship between the content, context, and success of private sector attempts to influence the formation of the Basel II Accord between 1998 and 2004. I call these efforts 'private sector campaigns', and engage in an empirical analysis of campaigns organized at both the transnational level and at the national levels in Canada, Germany, Japan, the United Kingdom and the United States. The analysis employs a mixed-method research design involving process tracing analysis, fuzzy-set Qualitative Comparative Analysis (fsQCA) and statistical regression analysis. Using extensive primary source material, I test a number of different hypotheses prevalent within relevant academic literatures regarding the specific means that private sector groups use to influence their regulators, as well as the transnational and national pathways by which private sector influence translates into actual regulatory policy change. While I find evidence for a number of important instances of private sector influence over the content of the Basel II Accord, I find that this influence is much more contingent and context-dependent than depictions of 'regulatory capture' in the IPE of finance literature suggest. In particular, the presence of business conflict strongly affects the success of private sector campaigns. Furthermore, I find that while there are a number of necessary conditions that have to be in place for influence to occur, there is no individually sufficient condition for influence. Rather, only a particular combination of conditions is sufficient in generating private sector influence. This particular set of conditions is, however, highly fragile.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".