Green Accounting Practices and Shareholders’ Value of Listed Consumer Goods Companies in Nigeria
Bibliographic record
Abstract
The severity of environmental degradation has its adverse impact on the quality of lives. Measures are being taken both at the national and international level to reduce and mitigate its impact on the environment, social, economic, and political sphere. This study investigated the effect of green accounting practices on shareholders’ value in Nigeria by drawing samples from listed consumer goods firms on the floor of the Nigerian Exchange Group from 2012 to 2021. Ex post facto design was used, secondary data were employed and least square dummy variable regression was used in analyzing the data. A sample size of 20 companies were determined using Tato Yamane formula and these companies were selected using simple random sampling technique. Green accounting being the dependent variable was proxied by biodiversity disclosure, emission disclosure, waste disclosure, water & effluents disclosure, and compliance to environmental laws & regulations disclosure. The dependent variable of this study was shareholders’ value proxied by shareholders’ value added (SHVA). The result showed that biodiversity disclosure and compliance to environmental laws disclosures have a positive significant effect on shareholders’ value added; water & effluents disclosures have a positive significant effect on shareholders’ value added of listed consumer goods firms in Nigeria during the period under study. It was thus concluded that green accounting practices have significant effect on shareholders’ value added of manufacturing companies in Nigeria. Therefore, it was recommended among others that compliance to green accounting practices should be made mandatory for all companies because standard green accounting disclosures are signals to all stakeholders that the companies are ‘green’ and eco- friendly companies and this in turn boost shareholders value.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".