FOREIGN CAPITAL AND DOMESTIC FUNDING CONDITIONS: A MUNDELLIAN TRILEMMA PERSPECTIVE
Bibliographic record
Abstract
This study investigates and evaluates the impact of global funding conditions on private sector credit growth and controlling for the Mundellian Trilemma configuration. We contribute to the empirical literature by investigating the role of other conditioning factors such as the size of economies and their level of economic development. The more specific research goals are as follows: (i) To explore the different Trilemma configurations by income group and size of the economies; (ii) to enrich international macroeconomics literature on the role of Trilemma configurations and countries’ idiosyncrasies in assessing the impact of global financial conditions; and (iii) to formulate policy-relevant conclusions. We argue that — when assessing the impact of global financial conditions — the exchange rate regime and financial openness matter and the size of the economy and its income level. The high volatility in gross and net international capital flows redefined many trilemma configurations in the Great Recession aftermath. Many countries decided to shield their financial markets by reducing the degree of financial openness and moving toward intermediate or middle-ground positions in their Trilemma configurations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".