Dynamic Spatial Competition Between Multi‐Store Retailers
Why this work is in the frame
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Bibliographic record
Abstract
We propose a dynamic model of an oligopoly industry characterized by spatial competition between multi‐store retailers. Firms compete in prices and decide where to open or close stores depending on demand and cost conditions, the number of competitors at different locations, and on location‐specific private‐information shocks. The model distinguishes multiple forces in the spatial configuration of store networks, such as cannibalization of revenue between stores of the same retail chain, economies of density, competition, consumer transportation costs, or positive demand spillovers from other stores. We develop an algorithm to approximate a Markov Perfect Equilibrium in our model, and propose a procedure for the estimation of the parameters of the model using panel data on number of stores, prices, and quantities at multiple geographic locations within a city. We also present a numerical example to illustrate the model and algorithm.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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