Convergence in a neo-Kaleckian model with endogenous technical progress and autonomous demand growth*
Bibliographic record
Abstract
This paper introduces technical progress along the lines of the Kaldor–Verdoorn law within a neo-Kaleckian model of growth and distribution that incorporates the Sraffian supermultiplier mechanism. The key features of the model include the interactive effects of endogenous technical progress, the non-capacity-creating demand component that grows at an exogenous rate and, in its long-run version, a Harrodian adjustment mechanism. It turns out that, whereas the model converges towards the normal rate of capacity utilization, the main tenets of the Keynesian model are still valid in the long run as well as in the short run in the sense that all of the average rates of accumulation, capacity utilization, and technical progress are lower during the traverse after the propensity to save or the share of profits goes up. The conditions under which the productivity regime can be wage-led are examined, and the possible effects of an exogenous technical shift are also discussed.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".