Bibliographic record
Abstract
Empirical support for the long-run Fisher effect, a hypothesis that a permanent change in inflation leads to an equal change in the nominal interest rate, has been hard to come by. This paper provides a plausible explanation of why past studies have been unable to find support for the long-run Fisher effect. This paper argues that the necessary permanent change to the inflation rate following a monetary shock has not occurred in the industrialized countries of Australia, Austria, Belgium, Canada, Denmark, France, Germany, Greece, Ireland, Italy, Japan, the Netherlands, Norway, Sweden, Switzerland, the United Kingdom, and the United States. Instead, this paper shows that inflation in these countries follows a mean-reverting, fractionally integrated, long-memory process, not the nonstationary inflation process that is integrated of order one or larger found in previous studies of the Fisher effect. Applying a bivariate maximum likelihood estimator to a fractionally integrated model of inflation and the nominal interest rate, the inflation rate in all seventeen countries is found to be a highly persistent, fractionally integrated process with a positive differencing parameter significantly less than one. Hence, in the long run, inflation in these countries will be unaffected by a monetary shock, and a test of the long-run Fisher effect will be invalid and uninformative as to the truthfulness of the long-run Fisher effect hypothesis.
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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 | 0.044 | 0.242 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.003 | 0.014 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 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".