Inventories, Markups, and Real Rigidities in Menu Cost Models
Bibliographic record
Abstract
Real rigidities that limit the responsiveness of real marginal cost to output are a key ingredient of sticky price models necessary to account for the dynamics of output and inflation. We argue here, in the spirit of We study a menu cost economy in which firms hold inventories in order to avoid stockouts and to economize on fixed ordering costs. We find that, for low rates of depreciation similar to those in the data, inventories are highly sensitive to changes in the cost of holding and acquiring them over the cycle. This implies that the model requires an elasticity of real marginal cost to output approximately equal to the inverse of the elasticity of intertemporal substitution in order to account for the countercyclical inventory-to-sales ratio in the data. Stronger real rigidities lower the cost of acquiring and holding inventories during booms and counterfactually predict a procyclical inventory-to-sales ratio.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".