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Record W1560681437 · doi:10.1111/jbfa.12022

Government Intervention and Investment Comovement: Chinese Evidence

2013· article· en· W1560681437 on OpenAlex
Donghua Chen, Saqib Khan, Xin Yu, Zhou Zhang

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

VenueJournal of Business Finance &amp Accounting · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsIntervention (counseling)Investment (military)Government (linguistics)Monetary economicsEconomic interventionismBusinessSample (material)Foreign direct investmentEconomicsMacroeconomicsPolitics

Abstract

fetched live from OpenAlex

Abstract This study examines whether government intervention affects corporate investment comovement, and whether this impact varies across firms with different types of ownership. We use a large Chinese sample to investigate these questions, and perform a regional as well as firm‐level analysis. We show that government intervention is positively and significantly associated with investment comovement. We also find that the impact of government intervention on investment comovement is higher and more significant for state‐owned firms than for domestic private and foreign firms. Finally, we show that investment comovement hinders corporate performance for state‐owned and domestic private firms but not for foreign firms.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.008
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 head0.018
GPT teacher head0.222
Teacher spread0.204 · 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