Monetary Rules When Economic Behaviour Changes
Bibliographic record
Abstract
This paper examines the implications of changes in economic behaviour for simple inflation-forecast–based monetary rules of the type currently used at two inflation-targeting central banks. Three types of changes in economic behaviour are considered, changes that are motivated by developments in monetary and fiscal policy in the 1990s: changes in monetary policy credibility, changes in the slope of the Phillips curve, and changes in the degree of income stabilization from automatic fiscal transfers. Analysis is conducted using stochastic simulations of a model of the Canadian economy. Two questions are posed: First, what are the implications of these types of changes in economic behaviour for the stochastic properties of the economy? Second, how are efficient inflation-forecast–based rules affected by these changes in behaviour? Perhaps the most interesting results are with respect to credibility. When monetary credibility increases, the central bank can attain more stable output and inflation. But increasing credibility is a double-edged sword. To reap its benefits, the central bank must, in general, adjust its reaction function. If it does not, volatility can increase.
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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 | 0.025 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".