The impact of inventory risk on market prices under competition
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Firms often must procure inventory/capacity before knowing what the demand will be, so there is a potential for a mismatch between inventory and demand, the “inventory risk.” We show that, because of inventory risk, an increase in the number of competitors can lead to an increasing trend in market prices. Furthermore, we show that, ceteris paribus, because of how inventory risk impacts competitive behavior, firms may prefer to incur inventory risk rather than to avoid it. To illustrate the robustness of our results, we establish these findings using three complementary methodologies: (i) using data from a classroom experiment, (ii) using a quantal response equilibrium simulation to capture realistic irrationalities in managerial decisions under competition, and (iii) using a fully rational Nash equilibrium model to capture the impact of the competition per se. That all three methods lead to identical qualitative findings reinforces the main message of our paper: Inventory risk reverses the standard intuition for how an increase in the number of competitors impacts prices.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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