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Record W3022743865 · doi:10.3386/w21599

Inflation, Output, and Markup Dynamics with Forward-Looking Wage and Price Setters

2015· preprint· en· W3022743865 on OpenAlexaff
Louis Phaneuf, Eric Sims, Jean Gardy Víctor

Bibliographic record

VenueNational Bureau of Economic Research · 2015
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsMarkup languageInflation (cosmology)EconomicsWageMonetary economicsDynamics (music)EconometricsKeynesian economicsMacroeconomicsLabour economicsComputer scienceXMLWorld Wide Web

Abstract

fetched live from OpenAlex

We formulate a medium-scale DSGE model that emphasizes a strong interplay between a roundabout production structure and a working capital channel that requires firms to borrow funds to finance the costs of all their variable inputs and not just the wage bill.Despite an absence of backward-looking price and wage indexation, our model is able to account for (i) a persistent and hump-shaped response of inflation to a monetary policy shock, (ii) a large and persistent response of output to a monetary policy shock, (iii) a mild "price puzzle," (iv) a procyclical price markup conditional on a monetary shock, (v) non-inertial responses of inflation to non-monetary shocks, and (vi) a negative unconditional autocorrelation of the first difference of inflation that is consistent with the data.A medium-scale model relying on backward indexation of wages and prices to past inflation fails along several of these dimensions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.283
GPT teacher head0.396
Teacher spread0.112 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueNational Bureau of Economic Research→Same topicMonetary Policy and Economic Impact→French-language works237,207→