Private and Public Consumption Expenditure Substitutability: Bayesian Estimates for the G7 Countries
Why this work is in the frame
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Bibliographic record
Abstract
The degree of substitution between private and public per capita consumption for the G7 countries is estimated over the period 1960 to 1996. Special attention is given to isolating both long-run and short-run substitution effects. Inferences are produced using a Bayesian methodology, with a Jeffreys prior being used to offset an identification problem in the likelihood function. The marginal posterior densities of interest are estimated via a hybrid of Markov chain Monte Carlo algorithms. The empirical results indicate that for the US, Germany, France and Italy, private and public consumption expenditure are substitutes in the short-run, but complements in the long-run. The opposite result occurs for the UK, whilst Japan and Canada exhibit no significant short-run or long-run relationships.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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