On durable goods markets with entry and adverse selection
Bibliographic record
Abstract
Abstract. We investigate the nature of trading and sorting induced by the dynamic price mechanism in a competitive durable good market with adverse selection and exogenous entry of traders over time. The model is a dynamic version of Akerlof (1970) . Identical cohorts of durable goods, whose quality is known only to potential sellers, enter the market over time. We show that there exists a cyclical equilibrium where all goods are traded within a finite number of periods after entry. Market failure is reflected in the length of waiting time before trade. The model also provides an explanation of market fluctuations. JEL classification: D82 A propos des marchés de biens durables quand il y a entrée de nouveaux commerçants et sélection adverse. Les auteurs analysent la nature du commerce et du triage engendrés par le mécanisme dynamique des prix dans un marché concurrentiel de biens durables quand il y a sélection adverse et entrée exogène de nouveaux commerçants dans le temps. Ce modèle est une version dynamique du modèle d’ Akerlof (1970) . Des cohortes identiques de biens durables, dont la qualité est connue seulement des vendeurs potentiels, arrivent sur le marché dans le temps. Il semble qu’il y ait plus de commerce actif que ce qui est prévu par un modèle statique. En particulier, on montre qu’il existe un équilibre cyclique où tous les biens sont transigés à l’intérieur d’un nombre fini de périodes après leur arrivage et que, à chaque phase du cycle, l’éventail de qualité des biens transigés s’accroît. Les commerçants qui transigent des produits de plus haute qualité attendent plus longtemps et l’imperfection du marché se traduit par la longueur de temps d’attente avant la transaction. Le modèle fournit aussi une explication des fluctuations du marché.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".