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Record W1934774039 · doi:10.3386/w13079

Has New York Become Less Competitive in Global Markets? Evaluating Foreign Listing Choices Over Time

2007· report· en· W1934774039 on OpenAlex
Craig Doidge, George Andrew Karolyi, René M. Stulz

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNational Bureau of Economic Research · 2007
Typereport
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsListing (finance)BusinessFinancial economicsEconomicsMonetary economicsInternational economicsFinance

Abstract

fetched live from OpenAlex

We study the determinants and consequences of cross-listings on the New York and London stock exchanges from 1990 to 2005. This investigation enables us to evaluate the relative benefits of New York and London exchange listings and to assess whether these relative benefits have changed over time, perhaps as a result of the passage of the Sarbanes-Oxley Act of Congress (SOX) in 2002. We find that cross-listings have been falling on U.S. exchanges as well as on the Main Market in London. This decline in cross-listings is explained by changes in firm characteristics rather than by changes in the benefits of cross-listings. We show that, after controlling for firm characteristics, there is no deficit in cross-listing counts on U.S. exchanges related to SOX. Investigating the cross-listing premium from 1990 to 2005, we find that there is a significant premium for U.S. exchange listings every year, that the premium has not fallen significantly in recent years, that it persists even when allowing for unobservable firm characteristics, and that there is a permanent premium in event time. In contrast, there is no premium for London listings for any year. Cross-listing in the U.S. leads firms to increase their capital-raising activity at home and abroad while a London listing has no such impact. Our evidence is consistent with the theory that an exchange listing in New York has unique governance benefits for foreign firms. These benefits have not been seriously eroded by SOX and cannot be replicated through a London 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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.914
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.416
GPT teacher head0.472
Teacher spread0.056 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it