Government Deficit Spending and Inflation: Alain Parguez and the Post-Keynesians
Bibliographic record
Abstract
This article briefly recounts this author’s personal experience with Alain Parguez and sketches some of his important contributions over four decades. It then tackles the contemporary policy controversy concerning net public spending and inflation, which is once again contentious in today’s inflationary environment. Alain Parguez’s viewpoint was diametrically opposed to the Hayekian position that deficit spending is inevitably inflationary; the latter presumed positive relation between deficits and inflation being questioned by simple empirical evidence available from Western industrial countries. In his writings, instead, Parguez defended a strong Keynesian position on the productive role of public spending. Outside of interest payments on the public debt, he considered public spending broadly in the nature of public investment unassociated with any predictable inflationary consequences, except perhaps in a fully-employed economy. “Good” public budgetary deficits generate much-needed physical productive capital but also essential human/social capital via government transfers. This view is contrasted with the views of two other celebrated post-Keynesian/circuitist writers, Augusto Graziani and Hyman Minsky, who despite important common features of their analyses vis-à-vis those of Parguez, held a somewhat different view of the inflationary impact of deficit spending.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".