AN ANALYSIS OF PRICE-BASED TESTS OF ANTITRUST MARKET DELINEATION
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Bibliographic record
Abstract
There are well-known theoretical concerns regarding the use of price correlations to determine antitrust markets. However, this has not deterred their use or the application of Granger causality, stationarity, and cointegration tests in the determination of antitrust markets. In this paper, we explore the empirical performance of these various tests. In particular, we want to know whether these tests are capable of generating the correct inference both when two products are in the same relevant market and when they are not. Our results imply that, in the absence of common shocks, simple price correlations may be capable of providing reliable evidence on market delineation. However, in samples sizes similar to those currently available, the performance of other commonly employed price-based tests suggests that they provide little economically meaningful information to antitrust practitioners.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it