The Law of One Price and Its Violation: An Update on Empirical Advances
Bibliographic record
Abstract
A monetary policy aiming to achieve some desirable macroeconomic objectives may be ineffective to some degree when the highly warranted Law of One Price (LOP) operation is violated. This essentialises identification of the potential barriers to price convergence in different contexts to maximize effectiveness of the monetary policies. With this end in view this study carries out a comprehensive review of the existing literature regarding the LOP and the half-life of the price convergence. The existing empirical evidences find that the prices tend to converge in most cases, and the barriers to and the speed of the price convergence depend on the specific contexts. Moreover, by using major Australian city-level daily petrol prices (an essential commodity) over a long period (2004-2020) and by employing unit root tests, this study estimates the half-life of the petrol prices across those cities. The findings are consistent with those of some existing studies.
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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 | 0.014 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.008 | 0.017 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.008 | 0.016 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".