CEOs' Political Ideology, Social Capital and Corporate Tax Avoidance
Bibliographic record
Abstract
ABSTRACT Building on institutional theory, we explore the interaction between social capital and CEO political ideology on corporate tax avoidance. Using CEOs' political donations to identify their political ideology, we find that firms led by Republican CEOs tend to have lower (higher) effective tax rates when located in communities with lower (higher) social capital, indicating a higher (lower) propensity for tax avoidance, compared to firms led by non‐Republican CEOs. Our findings support the U.S. Internal Revenue Service's (IRS) view that tax compliance behaviour is inherently a sociopolitical construct. Our results suggest that tax policymakers and other regulators should pay more attention to social capital at the community level to foster ethical corporate behaviour in relation to tax compliance. Overall, we provide the tax authorities with useful insights into corporate tax compliance, which are applicable to both U.S. and international settings, particularly in regions with distinct political and social norms.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".