Corporate Social Responsibility and Capital Allocation Efficiency in Australia and New Zealand
Bibliographic record
Abstract
In this paper, we investigate whether a firm’s Corporate Social Responsibility initiatives could affect its financial performance. We specifically investigate the firm’s capital allocation efficiency as a moderating channel affecting their performance. We employ a comprehensive sample of Australian and New Zealand stock exchange-listed firms consisting of 3324 firm-year observations for the period 2004–2017. We do not find that the firm’s capital allocation efficiency is negatively affected by the overall CSR scores or its two main components, namely the environmental or social dimensions. However, our empirical analysis exposes a challenging result for the firms in that we find strong evidence that extremely costly environmental CSR initiatives or policies (e.g., emission reduction, employee health and safety improvements, clean energy products) could reduce the firm’s investment efficiency. Hence, firms need to follow a balancing act when contemplating CSR plans and investing in them. While investors appreciate moderate levels of investment in CSRs, they penalize those firms that invest excessively in such initiatives.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".