Is the Fisher effect asymmetric? Cointegration analysis and expectations measurement
Bibliographic record
Abstract
Abstract Using U.S. post‐war data, we investigate whether the interest rate response to inflation known as the Fisher effect could be asymmetric. The asymmetry considered is that the long‐run change in the interest rate is larger when inflation rises than when it falls. The possibility follows from behavioural hypotheses about the relationship of inflation expectations to actual inflation. Using an asymmetric cointegration approach, we find asymmetric cointegration in the Fisher effect for the post‐war period through 1979, but not subsequently. We then find that starting in 1980, a breakdown developed in the relationship between inflation expectations from surveys and actual recent inflation rates, a breakdown not accounted for by asymmetry. If the survey results approximate true expectations, then econometric testing using actual recent inflation to compute expected inflation will suffer from mismeasurement, which could explain the finding of no cointegrating Fisher effect post‐1979. The paper accounts for breakpoints and uses bootstrapping to conservatively estimate statistical significance.
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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 | 0.007 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".