Does Capital Expenditure Matter for ESG Disclosure? A UK Perspective
Bibliographic record
Abstract
This study examines how capital expenditure (capex) affects Environmental, Social, and Governance (ESG) reporting and how corporate governance moderates this effect. We use data from non-financial firms in the FTSE All Share index from 2012 to 2021 and measure ESG disclosure with the Bloomberg ESG Disclosure Score, capex with logarithm of the ratio of capital expenditure to total assets, and corporate governance with a composite index based on Board Size, Independent Board, Board Diversity, and Audit Committee Non-Executives. We also examine the non-linear and threshold effects of capex on ESG disclosure with spline regression models. We find that capex is positively linked to ESG disclosure and that this association is robust for firms with better corporate governance. Our findings imply that capex improves ESG performance and impact and that corporate governance enables ESG communication to stakeholders. Our research advances the existing literature by revealing the link between capex, governance, and ESG reporting in a dynamic and uncertain environment. Our study holds practical significance for companies, investors, and regulators who want to incorporate ESG factors into capex decisions and reporting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".