Real wages and the origins of modern economic growth in Germany, 16th to 19th centuries
Bibliographic record
Abstract
The study develops a real wage series for Germany c. 1500-1850 and analyzes its relationship with population size. From 1690 data density allows the estimation of a structural time series model of this relationship. The major results are the following: First, there was a strong negative relationship between population and the real wage until the middle of the seventeenth century. The dramatic rise of material welfare during the Thirty Years' War was thus entirely due to the war-related population loss. Second, the relationship between the real wage and population size was weaker in the eighteenth than in the sixteenth century; the fall of the marginal product of labor was less pronounced, and the beginning of the eighteenth century saw a marked increase of labour demand. Third, labor productivity underwent a strong positive shock during the late 1810s and early 1820s, and continued to rise at a weaker pace during the following decades. This growth was only temporarily interrupted by negative shocks during the late 1840s and early 1850s. Results two and three suggest the onset of sustained economic growth well before the beginnings of industrialization, which set in during the third quarter of the nineteenth century.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".