A Quarter of a Century Progress Report on the Services Sector Productivity Statistics. A Europe-United States Perspective
Bibliographic record
Abstract
The deterioration in 1995 of Europe productivity performance relative to the U.S. coincided with the ‘renaissance’ of the U.S. statistical system, which has been upgraded in many important respects. With these efforts, there is now a consensus in the economics profession that the U.S. statistical system has set a new frontier in official statistics. This paper raises the natural question whether the European statistical system was ‘left at the station’ while its U.S. counterpart ‘departed,’ making it possible for measurement differences to become the primary suspect of the existing productivity gap. Our retrospective examination at the development of the services sector productivity statistics in both Europe and the U.S. suggests the presence of a circumstantial evidence in support of measurement differences. The evidence based on a ‘structured guess’ suggests that the upgrade in the U.S. services sector statistics translated into enhancements of two kinds in the post-1995 period—a considerable reduction in the contribution of industries that traditionally dampened the aggregate productivity trend combined with a higher contribution of those that generally lifted it. This contrasts markedly with Europe where the contribution of these two sources remained unchanged in the meantime, reflecting important gaps in terms of scope of the service producer price index program and the timing of its implementation.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".