Trump's "Big-League" Tax Reform: Assessing the Impact of Corporate Tax Changes
Bibliographic record
Abstract
This Article reviews and assesses corporate tax reforms advocated by President Donald Trump during his presidential campaign and signed into law since taking office (the Tax Cuts and Jobs Act of 2017), in light of economic theory and the Modigliani-Miller Irrelevance Theorem. The Article argues that companies will adapt policies in light of new taxation measures, thereby impacting the effectiveness of reform. In support of this conclusion, the Article surveys two empirical studies—one in relation to the repatriation efforts of President Bush’s Homeland Investment Act and another in relation to unexpected changes to the taxation of Canadian income trusts—to highlight how reform measures can lead to unanticipated results. The Article then applies the principles of these studies, the general economic theories, and the Modigliani-Miller Irrelevance Theorem to cast uncertainty on the net effect of Trump’s tax reforms. Next, the Article reviews the constitutionality of a “border adjustment tax.” This tax was proposed during the election campaign, but was ultimately jettisoned in the final tax reform bill. Specifically, it analyzes whether such a policy is constitutional or whether it is an unconstitutional direct tax, not apportioned between the States that does not qualify as income under the Sixteenth Amendment. The Article shows that such a constitutional challenge is a difficult undertaking given the substantive arguments in favor of constitutionality, the rarity of judicial intervention in overturning tax laws, and the wide discretion of Congress to levy taxes on income. Finally, the Article concludes by considering the role of economic analysis on constitutional challenges to tax legislation and provides an overview of the arguments, both for and against, utilizing economic analysis in this regard. The conclusion includes a review of the various cases and defining principles (emphasizing the decisions of Judge Richard Posner) where economic analysis has been used in the statutory interpretation of tax laws.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".