Does Accounting Measurement Influence Market Efficiency? A Laboratory Market Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Using laboratory markets where accounting regimes can be directly compared with equivalent economic parameters, we test whether and how two different accounting measurement bases—historical cost (HC) and mark-to-market (MTM)—influence trader perceptions and asset mispricing. Our results show that traders perceive otherwise equivalent assets differently by regime, consistent with accounting regimes imposing differential information processing costs. In the MTM regime, traders integrate market price information to a greater extent and integrate asset fundamental information to a lesser extent. We also observe that traders in the MTM regime express prospective preferences for information about future market prices, but in HC prefer information about future dividends. These individual-level effects correspond with greater market-level mispricing/bubbles under MTM. Our results suggest that accounting regimes can, on their own, contribute to price bubbles and their subsequent collapse. Data Availability: Data are available on request.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.002 |
| 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 it