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Record W4382561827 · doi:10.1016/j.irfa.2023.102776

The improvement of legal system, entrepreneur immigration, and corporate cash holdings

2023· article· en· W4382561827 on OpenAlex

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

VenueInternational Review of Financial Analysis · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInstrumental variableCashImmigrationBusinessMatching (statistics)ChinaCash managementPropensity score matchingMonetary economicsEconomicsFinanceLawEconometricsPolitical science

Abstract

fetched live from OpenAlex

This study investigates the relationship between controlling persons' foreign residency rights and the cash holdings of non-state-owned listed firms in China from 2005 to 2018. Our findings indicate that the immigration status of entrepreneurs affects the amount of cash held by their firms, as it reduces legal costs in a weak legal system. This result remains robust under propensity score matching , instrumental variable method, and Heckman two-stage regression. What is more, the improvement of the legal system moderates the impact of entrepreneur immigration on corporate cash holdings, deters their short-sighted tunneling, and motivates them to put more effort into long-term innovation. This study enhances our understanding of the behavioral patterns of immigrant entrepreneurs and contributes to the literature on corporate cash holdings and upper echelons by highlighting the role of the legal system in improving their behavior in emerging markets.

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)0.001
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 score0.440
Threshold uncertainty score0.318

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.222
Teacher spread0.211 · 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