Bibliographic record
Abstract
According to standard theory, one of the central benefits of international financial markets is the possibility of reducing national consumption risk. A basic measure of risk sharing is hence the degree to which national consumption rates move in unison across countries. In the simplest theoretical model of international financial markets, efficient risk sharing implies that consumption growth in a given country closely tracks world consumption growth. With integrated financial markets, consumption growth should hence be highly correlated across countries--and more highly correlated than output growth. Yet, despite the liberalization of international financial markets and the strong growth in international capital flows during the past few decades, this prediction is sharply at variance with the evidence. Empirically, national consumption closely tracks national output, while cross-country consumption correlations are generally lower than cross-country output correlations. Hence, it would seem that countries are not fully exploiting the welfare benefits of international risk pooling. Documenting the pattern of (incomplete) risk sharing, and understanding the financial frictions at its roots, is thus of great interest for economic research and policy. This special issue of the Canadian Journal of Economics consists of a selection of papers that offer novel empirical and theoretical perspectives on international risk sharing. All papers were presented at a conference on ‘International Risk Sharing’ held at ECARES (Université Libre de Bruxelles), in October 2010.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.035 | 0.005 |
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".