Destination-Based Taxation in the House Republican Blueprint
Bibliographic record
Abstract
The House Republican Task Force on Tax Reform released its Blueprint for tax reform in June 2016, at the center of which is a destination-based cash-flow tax (DBCFT) to replace the current federal income tax on corporations. The House GOP Blueprint represents the first time that the DBCFT has been promoted by political leaders. Initial commentators have stressed the capacity of such a tax (if adopted in the U.S.) to reduce U.S. companies’ incentives for international tax planning and profit shifting, and to allow the U.S. to “leapfrog to the front of the pack” in its tax competitiveness. This essay discusses three key issues for understanding the DBCFT. First, I argue that we should not see the “perennial question” concerning border adjustments required by the tax as being about WTO-compatibility. Instead, the question should be whether we truly understand the DCFT’s potential impact on trade, aside from WTO legal concerns. In reality, key questions about the DBCFT’s distortionary trade effects have not been answered. Second, I examine how the loss carry-forward aspect of the Blueprint interacts with border adjustments, and argue that it creates a first-order implementation issue. Third, I show that the extension of destination-based taxation to non-corporate entities simultaneously (i) is necessary, (ii) produces no efficiency gains relative to the status quo, and (iii) renders pass-through taxation obsolete. The implementation issues for the DBCFT I highlight would not arise if the U.S. were to adopt a VAT instead. I conclude by comparing the DBCFT with the VAT in respect of the issue of progressivity, and considering how other countries would respond to a U.S. DBCFT.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".