Look at Me Now: The Role of Cross-Listing in Attracting U.S. Investors
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
We use a comprehensive 1997 survey to examine U.S. investors' preferences for foreign equities. We document a variety of firm characteristics that can influence U.S. investment, but the most important determinant is whether the stock is cross-listed on a U.S. exchange. Our selection bias-corrected estimates imply that firms that cross-list can increase their U.S. holdings by 8 to 11 percent of their market capitalization, roughly doubling the amount held without cross-listing. All else equal, we find that firms experience smaller increases in U.S. shareholdings upon cross-listing if they are Canadian, from English-speaking countries, are members of the MSCI World index, or had higher quality accounting standards prior to cross-listing. We argue that these findings suggest that improvements in information production explain U.S. investors' attraction to foreign stocks that cross-list in the United States.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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