Environmental, Social, and Governance Performance and Value Creation in Product Market: Evidence from Emerging Economies
Bibliographic record
Abstract
Using a unique sample of 13,412 firm-year observations from 19 countries of the emerging economies for the period of 2011 to 2019, we investigate the association between the firms’ environmental, social, and governance (ESG) performance and their value creation in the product market. Specifically, we first used the pooled OLS regression model for panel data as our baseline model and found that ESG performance (as well as its pillars) has a strong positive effect on the future value creation of the firms in the product market. We also conducted some additional analyses using various regression models, as well as adopting multiple tests for endogeneity, and the additional analyses revealed that the results are robust under different scenarios. Overall, the findings of this study highlight the importance of firm-level ESG performance for the value creation of firms in the product market in emerging economies and have theoretical and practical implications for academic researchers, market participants, and government entities in studying, evaluating, and governing firms’ ESG performance and reporting.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".