Regulating Gender Diversity: Evidence from California Senate Bill 826
Bibliographic record
Abstract
Do gender diversity quotas enhance firm value? This broad question has sparked significant debate because, whereas diversity is generally thought to improve board functioning, prior research in international settings suggests mandating diversity may have adverse consequences if it moves firms away from market equilibrium. Exploiting the political events leading up to the passage of California Senate Bill (SB) 826 as an exogenous shock to assess the market implications of board gender composition, we document either significantly positive or insignificant two-day abnormal returns for California firms across a variety of model specifications. Importantly, this finding contradicts the strong claims of contemporary studies of SB 826 that the California mandate was value-destructive. We reconcile these findings by providing critical evidence that contemporaneous results lack robustness to alternative model specifications and provide an incomplete picture by failing to comprehensively examine a broader set of event dates or account for mixed messaging on the final event date. We also provide some evidence of significant negative abnormal returns to litigation milestones that threaten to overturn SB 826 with the magnitude increasing in the size of board gender deficits. Finally, we provide evidence that there is no observable decline in newly appointed female director quality following the implementation of SB 826 relative to either preregulation or male director appointments. Collectively, our results suggest nonnegative (if not positive) consequences to California firms arising from SB 826 and directly counter assertions that mandated gender diversity is detrimental to firm value. This paper was accepted by Brian Bushee, accounting. Funding: The authors gratefully acknowledge research funding from Brigham Young University and the University of Toronto. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4825 .
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".