Understanding credit-money: Lavoie and Seccareccia’s contribution to monetary theory
Bibliographic record
Abstract
Marc Lavoie and Mario Seccareccia, who spent pretty much their entire academic careers together at the University of Ottawa, have made the most of this twist of fate. Their fruitful collaboration over four decades has yielded a rich body of work whose strategic significance for the progress of Post-Keynesian economic theory deserves much commentary and debate. This is especially true, it seems, when it comes to their work on matters of money. How economists view this crucial institution and relate it to the rest of the economy inevitably shapes very much how they specifically come to understand the modus operandi of our capitalist market system. Standard neoclassical economics has a very peculiar view of money as an exogenous stock variable separated from the so-called ‘real’ sphere of exchange and production with regard to which the quantity of money in circulation is supposed to be neutral. While there may be instances where variations of the money supply or its velocity may affect the nation’s output and employment levels as those move towards their long-term equilibrium position following instances of temporary deviation, such impact is at best short-lived, if it exists at all. In the long run, money is but a ‘veil’ devoid of any lasting effect on those real-economy variables. The Austrian economist Friedrich Hayek (1931) has referred to this characterization as the neutrality of money. All that money may hence influence in the long run are ‘nominal’ (i.e. money-determined) variables such as prices, wages, or the exchange rate. If we want these variables to be reasonably stable, we have to have a central bank committed to follow the classical ‘Quantity Rule’ of slow and steady money-supply growth. Derived from Irving Fisher’s (1911) Equation of Exchange M.V 5 P.Q, the rule states that the central bank should let the money supply M grow at the rate at which the gross national product Q expands naturally (based on increases in labor supply and productivity) to provide for a stable price level P. We assume here a constant (or at least predictably stable) velocity of money V, justified by arguing that its reciprocal, the money ‘demand’ as the percentage of income the public wants to hold in the form of cash to pay for daily transactions, reflects a routinized spending pattern.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".