MétaCan
Menu
Back to cohort
Record W2238903494 · doi:10.1017/s1365100512000466

ENDOGENOUSLY SEGMENTED ASSET MARKET IN AN INVENTORY-THEORETIC MODEL OF MONEY DEMAND

2012· article· en· W2238903494 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMacroeconomic Dynamics · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsBank of Canada
Fundersnot available
KeywordsEconomicsMonetary economicsMarket liquidityInflation (cosmology)Endogenous moneyMonetary policyAsset (computer security)Market segmentationEconometricsMoney marketVelocity of moneyMicroeconomics

Abstract

fetched live from OpenAlex

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. In contrast to exogenous segmentation models in the literature, the timing of money transfers is endogenous. As a result, the model endogenizes the degree of market segmentation as well as the magnitudes of liquidity effects, price sluggishness, and the variability of velocity. I first show that the endogenous segmentation model can generate the positive long-run relationship between money growth and velocity observed in the data, which the exogenous segmentation model fails to capture. I also show that the short-run effects of money shocks on prices, inflation, and nominal interest rates are not robust.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.836
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.025
GPT teacher head0.220
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it