Innovation and Corporate Tax Planning: The Distinct Effects of Patents and R&D*
Bibliographic record
Abstract
ABSTRACT Using a large US sample, we find a significant and positive relation between patents and corporate tax planning, and the effect is incremental to the effect of R&D on tax planning. We employ a quasi‐natural experiment based on staggered industry‐level innovation shocks to identify the positive causal effect of patents on corporate tax planning. We also find that patents are not associated with tax planning for domestic firms, but their association with tax planning is concentrated in multinational firms, which have the ability to shift domestic income to low‐tax countries. Moreover, we find that the identified effect mainly exists in the post–check‐the‐box (CTB) rule period when shifting income among affiliates becomes more flexible and convenient. Finally, we use two income‐shifting models and find that patents, rather than R&D, facilitate tax planning through an income‐shifting channel. Overall, our results suggest that R&D and patents facilitate firms' tax planning in distinct ways: R&D facilitates tax planning as intended through tax credits and deductions, whereas patents are used by taxpayers to avoid taxes aggressively through income shifting.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".