Bibliographic record
Abstract
In this paper, we use a unique long-run dataset of regulatory constraints on capital account openness to explain stock market correlations. Since stock returns themselves are highly volatile, any examination of what drives correlations needs to focus on long runs of data. This is particularly true since some of the short-term changes in co-movements appear to reverse themselves (Delroy Hunter 2005). We argue that changes in the co-movement of indices have not been random. Rather, they are mainly driven by greater freedom to move funds from one country to another. In related work, Geert Bekaert and Campbell Harvey (2000) show that equity correlations increase after liberalization of capital markets, using a number of case studies from emerging countries. We examine this pattern systematically for the last century, and find it to be most pronounced in the recent past. We compare the importance of capital account openness with one main alternative explanation, the growing synchronization of economic fundamentals. We conclude that greater openness has been the single most important cause of growing correlations during the last quarter of a century, though increasingly correlated economic fundamentals also matter. In the conclusion, we offer some thoughts on why the effects of greater openness appear to be so much stronger today than they were during the last era of globalization before 1914.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".