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Record W2963323202 · doi:10.1002/csr.1816

What drives social responsibility indices returns? Macroeconomics matters

2019· article· en· W2963323202 on OpenAlexaff
Li‐Kai Liao, Yu‐Wei Fan, Ming‐Hsin Shih

Bibliographic record

VenueCorporate Social Responsibility and Environmental Management · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsPricewaterhouseCoopers (Canada)
Fundersnot available
KeywordsIndex (typography)Cash flowEconomicsStock (firearms)Free cash flowFinancial economicsMonetary economicsBusinessFinance

Abstract

fetched live from OpenAlex

Abstract This study investigates the responsiveness of a social responsibility index's returns to cash flow news compared with a broad stock index. The study contributes by comprising the synergy of corporate social responsibility to reflect the influence of the macroeconomy and by increasing model appropriateness. The empirical results show that cash flow news is the primary factor to drive both index returns, but the effect is stronger for the S&P 500 Index. Consistently, the investors of the S&P 500 Index react to cash flow news appropriately. Before adding the macroeconomic state variable, cash flow news under explains FTSE4Good US 100 Index returns, but investors overreact to that information. After adjusting, the explanation power of cash flow news increases, and its investors rather underreact to that information.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, 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: Empirical
Teacher disagreement score0.171
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.004
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.021
GPT teacher head0.231
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

Classification

machine, unvalidated

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

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

Citations3
Published2019
Admission routes1
Has abstractyes

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