Controlling Shareholders' Tax Incentives and Classification Shifting*
Bibliographic record
Abstract
ABSTRACT Although prior studies provide evidence on the financial reporting incentives to inflate core earnings through classification shifting (e.g., shifting core expenses to income‐decreasing noncore items), few examine the tax‐related incentive to report lower core earnings through classification shifting. We examine the effect of controlling shareholders' tax incentives on firms' classification shifting using the introduction of a tax law in Korea that imposes a gift tax on controlling shareholders based on firms' reported core earnings. This tax law creates incentives for managers to report lower core earnings through classification shifting, even though doing so would incur significant financial reporting costs. Using a difference‐in‐differences research design, we find that firms with controlling shareholders subject to the gift tax exhibit a significant decline in classification shifting in the post‐tax period, while those not subject to the tax do not. We also predict and find that the extent to which managers reduce classification shifting decreases with financial reporting costs and increases with the tax benefits. Overall, our results indicate that firms forgo financial reporting benefits associated with reporting higher core earnings for the tax savings of their controlling shareholders.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".