Generalized Solow-Neutral Technical Progress and Postwar Economic Growth
Bibliographic record
Abstract
Using revised, updated, and consistent annual post-World War II data from the G-7 countries developed by us, we econometrically estimate and test alternative explanations of the structure of economic growth in a model with three inputs tangible capital, labor, and human capital which permits the identification of the magnitudes of and biases in both returns to scale and technical progress. We find: 1. Technical progress is simultaneously purely tangible capital and human capital augmenting, that is, generalized Solow-neutral.' This finding provides an alternative explanation of the slow pace of convergence in real GDP per capita: the benefits from technical progress depend directly on the levels of tangible and human capital; countries with higher levels of capital realize higher rates of technical progress.2. Technical progress has been capital, not labor, saving and thus is not a cause of systemic structural unemployment. 3. Technical progress accounts for more than 50 percent of the economic growth of the G-7 countries except Canada. Tangible capital input is next most important; together with technical progress, they account for three quarters or more of the growth of real output in the G-7 countries, except Canada. 4. The most important source of the growth slowdown since the mid-1970's decline in the rate of capital (both tangible and human)-augmenting technical progress.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; both teacher heads agree on what is shown here.
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".