A CONDITIONAL MARKOV REGIME SWITCHING MODEL TO STUDY MARGINS: APPLICATION TO THE FRENCH FUEL RETAIL MARKETS
Bibliographic record
Abstract
This paper uses a regime-switching model that is built on mean-reverting and local volatility processes combined with two Markov regime-switching processes to understand the market structure of the French fuel retail market over the period 1990-2013. The volatility structure of these models depends on a first exogenous Markov chain, whereas the drift structure depends on a conditional Markov chain with respect to the first one. Our model allows us to identify mean reverting and switches in the volatility regimes of the margins. In the standard model of cartel coordination, volatility can increase competition. We find that cartelization is even stronger in phases of high volatility. Our best explanation is that consumers consider volatility in prices to be a change in market structure and are therefore less likely to search for lower-priced retailers, thus increasing the market power of the oligopoly. Our findings provide a better understanding of the behavior of oligopolies.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".