Bibliographic record
Abstract
In this paper a two‐country overlapping generations model is presented in which the roles of financial factors in the international monetary transmission mechanism are studied and whether and how the two types of credit market imperfections, limited participation, and costly state verification may contribute to the high variability of exchange rates are examined. Liquidity effects generated by monetary disturbances are shown to have qualitatively similar effects on the world economy in the perfect information case and in the costly information case. However, quantitative differences provide dfferent predictions about the variability of economic variables in the world economy. JEL Classification: F31, F41 Ce mémoire présente un modèle de deux pays où les générations se chevauchent pour étudier le rôle des facteurs financiers dans le mécanisme de transmission monétaire international, et pour examiner si les deux types d'imperfection (participation limitée et contrôle étatique coûteux) peuvent contribuer à une grande variabilité des taux de change et de quelle manière. On montre que les effets de liquidité engendrés par les perturbations monétaires ont les mêmes effets qualitatifs sur l'économie mondiale que l'information soit parfaite ou coûteuse. Cependant, il y a des différences quantitatives. Ces différences suggèrent des écarts dans les prévisions quant à la variabilité des variables économiques dans l'économie mondiale.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".