Changes in Central Bank Procedures During the Subprime Crisis and Their Repercussions on Monetary Theory
Bibliographic record
Abstract
The subprime financial crisis has forced several central banks to take extraordinary measures and to modify some of their operational procedures. These changes have made the deficiencies and lack of realism of mainstream monetary theory even clearer, as can be seen in undergraduate textbooks as well as in most macroeconomic models. They have forced monetary authorities to publicly reject some of the assumptions and key features of mainstream monetary theory, fearing that, on that mistaken basis, actors in the financial markets would misrepresent and misjudge the consequences of the actions taken by the monetary authorities. These changes in operational procedures also have some implications for heterodox monetary theory, in particular for post-Keynesian theory. My objective in this article is to analyze the implications of these changes in operational procedures for an understanding of monetary theory. I take the evolution of the operating procedures of the federal Reserve since august 2007 as an exemplar. The U.S. case is particularly interesting, both because it was at the center of the financial crisis and because the U.S. monetary system and its federal funds rate market are the main sources of theorizing in monetary economics.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".