Host's dilemma in international political economy: The regulation of cross-border banking in emerging Europe, 2004-2010
Bibliographic record
Abstract
Cross-border banking and foreign affiliates came to dominate the financial systems of many countries in Eastern Europe, Latin America, and Sub-Saharan Africa in the 1990s. Yet, the regulatory reform agenda, set by countries with limited exposure to foreign banks at home, has largely neglected the needs of host jurisdictions. Thus, host regulators with foreign-dominated banking systems find themselves with a de facto lack of control over their financial systems while being at the same time largely shut out from key international decision-making forums. This presents host regulators with a dilemma between undertaking potentially costly national policies in a global financial system or relying on cooperative solutions by forums in which they have little voice. This paper develops how this situation differs from the well-known "regulator's dilemma" in IPE and how it shapes the demand for cooperation by host states under conditions of asymmetric interdependence. It then illustrates the "host's dilemma" experienced by emerging European states between 2004 and 2007 before highlighting the surprisingly effective response of international institutions once the crisis hit the region in 2008. Based on this, it suggests three conditions under which international institutions might successfully mitigate the host's dilemma: low politicization, high ideational consensus, and high implementation capacity.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.003 | 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".