Corporate Governance Reforms and <scp>Cross‐Listings</scp>: International Evidence*
Bibliographic record
Abstract
ABSTRACT In this study, we examine whether a country's implementation of major corporate governance reforms affects firms' cross‐listing activities. Cross‐listing is important in overcoming international investment barriers and thus it is worth investigating whether enhanced corporate governance at the country level contributes to the integration of international capital markets. Using a difference‐in‐differences research design, we predict and find that following the implementation of corporate governance reforms in their home countries, firms are more likely to engage in cross‐listing activities and tend to cross‐list in host countries with stronger investor protection and more developed markets than those in countries with no reforms in the same period. The results from country‐level cross‐sectional tests indicate that this effect is greater for firms in home countries with weaker investor protection and less developed stock markets in the prereform period. The reforms also have a stronger effect on firms subject to less analyst following and greater external finance dependence. Finally, we find a stronger association between cross‐listing activities and institutional ownership after the reforms. Taken together, this study increases understanding of the trade‐off between cross‐border capital supply and demand. Our finding suggests that country‐level corporate governance plays an important role in facilitating the supply of cross‐border capital, which in turn incentivizes firms to cross‐list. Our study also offers policy implications for national stock exchanges and securities regulators by suggesting that countries without well‐developed capital markets should strengthen their corporate governance to improve firms' ability to raise external financing and attract cross‐border capital flows.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".