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Record W2606434200 · doi:10.1111/abac.12106

Why Do Canadian Firms Cross‐list? The Flip Side of the Issue

2017· article· en· W2606434200 on OpenAlex
Andreas Charitou, Christodoulos Louca

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAbacus · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsCross listingIncentiveBusinessListing (finance)AccrualEarnings managementStock (firearms)EarningsAccountingPrivate information retrievalStock optionsStock priceFinanceMonetary economicsEconomicsMicroeconomics

Abstract

fetched live from OpenAlex

We investigate the relation between managerial incentives and the decision to cross‐list by comparing Canadian firms cross‐listed on US stock exchanges to industry‐ and size‐matched control firms. After controlling for firm and ownership structure characteristics, we find a positive association between substantial holdings of vested options held by CEOs prior to cross‐listing and the decision to cross‐list. Further, firms managed by CEOs with substantial holdings of vested options exhibit positive announcement returns and negative post‐announcement long‐run returns. CEOs of cross‐listed firms seem to take advantage of the aforementioned market behaviour, because they abnormally exercise vested options and sell the proceeds during the year of listing only when their firms underperform during the subsequent year. In addition, there is a positive relation between substantial holdings of vested options and discretionary accruals during the year of listing, consistent with the view that CEOs manage earnings to keep stock prices at high levels. Overall, these results have significant implications for the cross‐listing literature, suggesting an association between cross‐listing and CEO incentives to maximize CEO private benefits.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

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

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 head0.016
GPT teacher head0.226
Teacher spread0.210 · 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