The Spurious Relation between Inflation Uncertainty and Stock Returns: Evidence from the U.S.
Bibliographic record
Abstract
The purpose of this paper is to reconsider the empirical evidence on the relation between inflation, inflation uncertainty, and stock returns. Two unprecedented proxies for inflation uncertainty are used. First, the power of inflation and inflation uncertainty to explain stock returns is compared. Both variables are separately negatively related to stock returns. However, when both are included together in the regressions, the inflation variable becomes redundant, meaning that its coefficient becomes statistically insignificantly different from zero. This means that inflation uncertainty dominates and supplants the effect of inflation. Second, this paper provides strong evidence that inflation uncertainty itself becomes redundant, and fails to explain stock returns, when two fundamental variables are included in the regressions. The two fundamental variables are the change in the cost of equity, and the growth rate of earnings. The first variable is roughly measured by the change in the baa and in the aaa corporate bond yields, while the second one is taken to be the rate of change of industrial production. The main conclusion of the paper is that both inflation and inflation uncertainty are not significantly related to stock returns when the two aforementioned fundamental variables are accounted for.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".