Are Firm Markups Boosting Inflation? A Post-Keynesian Institutionalist Approach to Markup Inflation in Select Industrialized Countries
Bibliographic record
Abstract
Starting in 2021, the current inflation process has spurred plenty of discussion in academic and policy circles. This paper studies the relationship between firms’ markups and inflation during the 2021–22 inflation surge in several industrialized countries. It begins by explaining markup inflation and its critics in the context of the current debate over the sources of inflation. Then it reviews the characteristics of markup inflation within the post-Keynesian theory of markup pricing and complementing it with the Institutionalist approach to inflation that distinguishes between basic inflationary pressures and propagation mechanisms. The second part assesses markup inflation for several industrialized countries using descriptive statistics and conventional econometrics. The main contribution falls in empirically estimating markups considering the contribution of material cost and controlling for changes in capacity utilization over time. It concludes that there is some evidence pointing at markup inflation and, importantly, the existence of markup inflation leads to rejecting any wage-price spiral.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".