The Costs of Product Repositioning: The Case of Format Switching in the Commercial Radio Industry
Bibliographic record
Abstract
This paper applies recently-developed methods for estimating dynamic games to estimate the size of costs incurred by radio stations when they change formats (i.e., their positioning in a horizontally-di¤erentiated products industry). The size of repositioning costs potentially a¤ects how markets respond to demand and supply shocks and whether “supply-side substitution ” can plausibly constrain market power created by mergers. The paper estimates a rich model of listener demand allowing for the endogeneity of station formats by exploiting timing assumptions similar to those used in the productivity literature. Preliminary estimates indicate that repositioning costs are quite large, and primarily come from the resources that stations have to spend to …nd new listeners and advertisers. I would like to thank Jerry Hausman, Igal Hendel, Aviv Nevo, Amil Petrin and participants at seminars at Duke, Northwestern, Chicago, Yale and the Canadian Summer Industrial Organization Conference at Kelowna. I would like
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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 | 0.020 |
| 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 | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".