Relative Governance and the Global Cross-Listing Decision: Extending the Bonding Hypothesis
Bibliographic record
Abstract
Using a comprehensive set of cross-listings, we extend the bonding hypothesis by developing what we term as the relative bonding hypothesis. We hypothesize that firms seek the advantages of stronger investor protections by listing in countries whose governance is relatively better than its own. This means that firms can achieve bonding without listing in the U.S and that the governance advantages of bonding are not only for ADRs. We find that firms are more likely to choose a cross-listing destination if the host country has better governance than the home country, except those firms from countries whose managers enjoy greater private benefits of control. We also find that there is valuation premium even when cross-listing occurs outside of the U.S. The premia are even stronger if the host country has better governance than that of the home country. We conclude that although bonding might explain the existence of ADRs, relative bonding helps to explain the extensive cross-listing which occurs outside of the U.S.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".