Board Gender Diversity and Firm Performance: Recent Evidence from Japan
Bibliographic record
Abstract
Gender diversity is increasingly recognized as a critical element in corporate management. However, existing research on its impact on firm performance demonstrates inconsistency in a global context. This study employs 1990 publicly listed Japanese companies from 2006 to 2023 and examines the effect of board gender diversity on firm performance in Japan. Findings from the fixed-effects regression model revealed a significant negative impact of board gender diversity on firm performance. This adverse correlation is more pronounced in smaller firms, those with greater leverage and reduced institutional ownership, and regulated and consumer-focused industries, particularly pre-COVID-19. The detrimental impact of board gender diversity on firm performance is transmitted via corporate social responsibility and firm innovation instead of board independence or CEO duality. Notably, the two-stage least squares estimation addresses potential endogeneity, employing an equal opportunity policy as an instrumental variable. Moreover, the robustness of our results is affirmed via the substitution of return on equity for return on assets as an indicator of firm performance. Lastly, our analysis does not reveal a U-shaped nonlinear relationship between board gender diversity and corporate performance. As Japan progressively promotes women’s participation in corporate governance, this research bears significant implications for corporate leaders, investors, and policymakers in Japan.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".