Distributional Regimes in the US — The Pasinetti Index and the Monetary Policy Effects on Income Distribution
Bibliographic record
Abstract
Policymakers and mainstream economists have expressed concerns over the distributional impacts of monetary policy following the emergence of so-called Unconventional Monetary Policies after the subprime crisis. This topic, however, is not new for post-Keynesianism. This paper focuses on the post-Keynesian idea of the Pasinetti Index. After an incursion into the history of this idea, the paper presents an econometric analysis of the relationship between the index, functional income distribution, and aggregate demand for the US from 1968 to 2022, using a threshold vector autoregressive model. The results indicate that the US economy has experienced different distributive regimes associated with changes in monetary policy. As a result, the economy has shifted from the Keynesian era to a more uncertain period, in which monetary policy is employed to protect the income and wealth of rentiers. Moreover, the work also shows that switches to a rentier-biased regime are highly detrimental to aggregate demand and functional income distribution.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".