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Record W2181518493 · doi:10.3386/w21779

Working through the Distribution: Money in the Short and Long Run

2015· report· en· W2181518493 on OpenAlexafffund
Guillaume Rocheteau, Pierre-Olivier Weill, Tsz-Nga Wong

Bibliographic record

VenueNational Bureau of Economic Research · 2015
Typereport
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsBank of CanadaWilfrid Laurier University
FundersSimon Fraser University
KeywordsDistribution (mathematics)EconomicsMathematics

Abstract

fetched live from OpenAlex

We construct a tractable model of monetary exchange with search and bargaining that features a nondegenerate distribution of money holdings in which one can study the short-run and long-run effects of changes in the money supply. While money is neutral in the long run, a one-time money injection in a centralized market with flexible prices generates an increase in aggregate real balances in the short run, a decrease in the rate of return of money, and a redistribution of consumption levels across agents. The price level in the short run varies in a non-monotonic fashion with the size of the money injection, e.g., small injections can lead to short-run deflation while large injections generate inflation. We extend our model to include employment risk and show that repeated money injections can raise output and welfare when unemployment is high.

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.

How this classification was reachedexpand

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)0.019
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.516
GPT teacher head0.475
Teacher spread0.041 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2015
Admission routes2
Has abstractyes

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