Endogenously Segmented Asset Market in an Inventory Theoretic Model of Money Demand
Bibliographic record
Abstract
This paper studies the effects of monetary policy in an inventory theoretic model of money demand. In this model, agents keep inventories of money, despite the fact that money is dominated in rate of return by interest bearing assets, because they must pay a fixed cost to transfer funds between the asset market and the goods market. Unlike the exogenous segmentation models in the literature, the timings of money transfers are endogenous. By allowing agents to choose the timings of money transfers, the model endogenizes the degree of market segmentation as well as the magnitude of liquidity effects, price sluggishness and variability of velocity. First, I show that the endogenous segmentation model can generate the positive long run relationship between money growth and velocity in the data which the exogenous segmentation model fails to capture. Second, I show that the short run effects of money shocks in an exogenous segmentation model (such as the linear inflation response to money shock, the liquidity effect and the sluggish price adjustment) are not robust. In an endogenous segmentation model, the equilibrium response to money shocks is non-linear and non-monotonic. Moreover, for large money shocks, there is no liquidity effect and no sluggish price adjustment.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".