Returns to scale: concept, estimation and analysis of Japan's turbulent 1964-88 economy
Bibliographic record
Abstract
Abstract There is policy interest in factoring productivity growth into technical progress and returns to scale components. Our approach uses exact index number methods to reduce the parameters that must be estimated, and allows us to exploit the cross-sectional dimension of plant-level panel data. We show that the same equation can also be used to estimate ‘Harberger’ scale economies and technical progress indicators that require fewer assumptions. Estimates of the elasticity of scale for Japanese establishments in three major industries over 1964–88 are presented. Our study spans the high growth era of the 1960s, two oil shocks, and other exogenous shocks. Il y a intérêt en politique publique à identifier les composantes de la croissance de la productivité attribuables au progrès technique et aux rendements à l’échelle. L’approche utilise les méthodes des nombres indices exacts pour réduire les paramètres qui doivent êtres estimés, et pouvoir exploiter la dimension transversale des données de panel au niveau de l’établissement. On montre que la même équation peut être utilisée pour estimer les indicateurs d’économies d’échelle et de progrès technique à la Harberger (lesquels nécessitent un plus petit nombre de postulats). On présente des évaluations de l’élasticité d’échelle pour des établissements japonais dans trois industries importantes entre 1964 et 1988.L’étude couvre la période de forte croissance des années 1960, celle des deux chocs pétroliers et d’autres chocs exogènes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".