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Record W4386268114 · doi:10.1080/16081625.2023.2250808

The informational role of analyst coverage on firm innovation: evidence from China

2023· article· en· W4386268114 on OpenAlexaboutno aff
Xiaori Zhang, Fangfang Sun, Yin-Che Weng, Yuan Yin, Wen Shi

Bibliographic record

VenueAsia-Pacific Journal of Accounting & Economics · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
FundersHarbin Institute of TechnologyFudan UniversityNational Natural Science Foundation of China
KeywordsBusinessStock exchangeChinaInstitutional investorInstrumental variableMonetary economicsStock marketStock (firearms)Quarter (Canadian coin)Information asymmetryContext (archaeology)AccountingFinancial economicsEconomicsFinanceCorporate governanceEconometrics

Abstract

fetched live from OpenAlex

We examine the effect of financial analysts’ informational and monitoring roles on firm innovation in the developing Chinese market. The findings demonstrate that analyst coverage has a positive influence on the number of corporate patent and invention applications. Causality is established by using an instrumental variable, and is reinforced by implementing a regression-discontinuity design (RDD) based on index reconstitutions and a difference-in-difference (DiD) analysis using the Shanghai-Hong Kong Stock Connect program as a plausible exogenous shock. Further, the positive effects are more pronounced for firms with severer financial constraints, higher information asymmetry, lower tolerance for failure among investors, and lower institutional ownership. These findings indicate that the informational role of financial analysts is more salient than their monitoring role in the context of developing 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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
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 head0.011
GPT teacher head0.210
Teacher spread0.199 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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