Sellers' Inflation and Distributive Conflict: Lessons from the Post-COVID Recovery
Bibliographic record
Abstract
The paper offers a post-Keynesian explanation of the soaring inflation experienced during the post-COVID recovery, coherent both at the microeconomic and macroeconomic levels. The microeconomic argument is rooted on the premise that price-making firms consider both their costs and their desired share of profits when setting prices. To defend profit margins in the aftermath of the pandemic, the initial cost-push shock was passed to consumers through higher prices; in a second phase, some firms, particularly in more highly concentrated and systemically significant sectors, benefited from the post-pandemic permissive pricing environment to increase their price mark-ups, leading to temporary profit-fueled inflation following the cost-push shock. This microeconomic explanation is compatible with the macroeconomic notion of a stable inflation barrier. For a given quantity of real output, it is shown that if profit earners defend their share of income following a cost-push, this will produce a one-time price increase, with inflation becoming more persistent if the target adapts endogenously — i.e., if the aggregate mark-up changes. The paper contrasts the notion of a wage-price spiral with that of a profit-price sink, arguing that sellers' inflation is a real — albeit temporary phenomenon.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".