What Companies Need to Know About International Cross‐Listing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article addresses four questions about cross‐listing by non‐U.S. companies on a U.S. stock exchange: Why do companies cross‐list? Does a U.S. listing increase firm value? If so, what are the sources of the increased valuation? And finally, how has the Sarbanes‐Oxley Act (SOX) affected the value of a U.S. listing? Both managerial surveys and academic research show that companies list in the U.S. to increase visibility and share liquidity, to broaden their shareholder base, to gain access to cheaper financing and reduce the cost of capital, and, in some cases, to implement a global business strategy. Foreign companies also typically cross‐list after periods of strong market performance and experience a positive valuation effect around the time of listing, but then underperform the market in the period after the cross‐listing. On average, cross‐listed companies exhibit higher valuations than their home‐market peers, but with significant variation based on firm characteristics: The valuation premiums are larger for smaller companies with higher past sales growth, higher ROAs, and lower financial leverage. In the long run, the companies that show a permanent increase in valuation are those that succeed in expanding their U.S. shareholder base and improving their levels of shareholder protection. Finally, the evidence suggests that SOX, while perhaps deterring some would‐be overseas listings, has not seriously eroded the net benefits of a U.S. listing.
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.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it