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Record W3124351306 · doi:10.3386/w25220

An Heterogeneous-Agent New-Monetarist Model with an Application to Unemployment

2018· preprint· en· W3124351306 on OpenAlexaff
Guillaume Rocheteau, Pierre-Olivier Weill, Tsz-Nga Wong

Bibliographic record

VenueNational Bureau of Economic Research · 2018
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsUnemploymentMonetarismEconomicsKeynesian economicsComputer scienceMacroeconomicsMonetary policy

Abstract

fetched live from OpenAlex

We develop a New Monetarist model with expenditure and unemployment risks that generates equilibria with non-degenerate distribution of money holdings. Distributional effects can overturn key insights of the model with degenerate distributions, e.g., the value of money depends on the income distribution; a one-time money injection raises aggregate real balances in the short runprice adjustments look sluggish; anticipated inflation can raise output and welfare; there can be a long-run trade-o between inflation and unemployment. Distributional effects also generate a quantitatively significant aggregate demand channel through which transfers financed with money creation can raise employment, and productivity shocks are amplified.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.273
GPT teacher head0.438
Teacher spread0.165 · 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.

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

Citations5
Published2018
Admission routes1
Has abstractyes

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