Understanding the productivity slowdown The importance of entry and exit of workers
Why this work is in the frame
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Bibliographic record
Abstract
Many OECD countries have experienced a slowdown in measured labour productivity from 2005 and onwards. Norway is no exception in this respect. Most countries use a simple aggregate of hours worked when measuring labour productivity. One way to improve measurement of labour services is to control for worker characteristics. A theoretical rationale for doing so is given by Diewert and Lippe (2010). We generalise previous analyses by allowing for exit and entry of workers when measuring labour services using Norwegian microdata. We find that the bias from using hours worked compared to a labour index capturing various compositional effects can be substantial and systematic over time. In the case of Norway the bias explains about a quarter of the productivity slowdown after 2005.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it