Could unemployment go back to the post‐war heyday?
Bibliographic record
Abstract
▀ The current ‘low’ rate of unemployment looks less impressive when compared with the 2–3% rates averaged in the 1950s and 1960s. But both then and now share a common driver of low joblessness – pay growth falling unusually short of productivity gains. While the chances of this continuing look stretching, a return to genuine full employment is not completely implausible. ▀ Why was unemployment so low in the early post‐war period? Given the current uncertainty over how far joblessness can sustainably drop and how this affects monetary policy, our analysis provides useful insights for the situation today. ▀ Several explanations have been mooted. A political commitment to full employment is one, although aspiration alone cannot provide a cause. And demand management using fiscal policy is hard to square with the period's modest budget deficits. Meanwhile, booming post‐war investment and trade and shortages of labour fail to explain why low joblessness did not quickly trigger rapid rises in pay and inflation. ▀ The cause of very low unemployment appears to have sat with wage restraint relative to productivity gains. Unlike most of the last 70 years, real pay growth consistently fell short of productivity rises in the 1950s and part of the 1960s, cutting the cost of workers and ensuring a low ‘equilibrium’ rate of unemployment. ▀ This explanation has parallels with the present day. Since 2010, productivity growth has outstripped real pay rises to an extent not seen since the 1950s. We do not expect this pattern to continue – our forecasts show real pay running slightly ahead of productivity growth over the next five years. But if the factors holding back pay were to persist, alongside a catch‐up in UK productivity, a return to a 1950s/60s‐style jobless rate is possible, if the MPC did not take fright at further declines in unemployment.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".