Bubbles and Capital Flow Volatility: Causes and Risk Management
Bibliographic record
Abstract
Emerging market economies are fertile ground for the development of real estate and other financial bubbles. Despite these economies' significant growth potential, their corporate and government sectors do not generate the financial instruments to provide residents with adequate stores of value. Capital often flows out of these economies seeking these stores of value in the developed world. Bubbles are beneficial because they provide domestic stores of value and thereby reduce capital outflows while increasing investment. But they come at a cost, as they expose the country to bubble-crashes and capital flow reversals. We show that domestic financial underdevelopment not only facilitates the emergence of bubbles, but also leads agents to undervalue the aggregate risk embodied in financial bubbles. In this context, even rational bubbles can be welfare reducing. We study a set of aggregate risk management policies to alleviate the bubble-risk. We show that liquidity requirements, sterilization of capital inflows and structural policies aimed at developing public debt markets "collateralized" by future revenues, all have a high payoff in this environment.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".