Services trade costs in the United States: A simulation based on the OECD Services Trade Restrictiveness Index
Bibliographic record
Abstract
While services account for almost 80% of GDP in the United States and a growing share of global trade, regulatory barriers to services trade around the world are still high. Using a hypothetical liberalisation scenario, this paper assesses the potential reduction of trade costs that could be achieved in 17 US services sectors. The analysis relies on the OECD Services Trade Restrictiveness Index (STRI) which records barriers to services trade in 46 economies. The illustrative scenario assumes a 50% reduction in the gap between the current STRI score of the United States and the score of the least restrictive country in each sector. The results highlight the economic benefits of aligning US services regulation with global best practice. The average reduction in trade costs across the 17 sectors analysed would amount to 9.7 percentage points, with a quarter of the sectors experiencing reductions larger than 14.1 percentage points and another quarter experiencing reductions smaller than 5.3 percentage points.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".