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Record W4388048814 · doi:10.1515/bejm-2022-0114

Optimal Monetary Policy with Government-Provided Unemployment Benefits

2023· article· en· W4388048814 on OpenAlexaff
Mehrab Kiarsi

Bibliographic record

VenueThe B E Journal of Macroeconomics · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsEconomicsUnemploymentNew Keynesian economicsImperfect competitionVolatility (finance)Inflation (cosmology)Context (archaeology)Monetary policySubsidyPhillips curveMarket powerMonetary economicsMicroeconomicsMacroeconomicsEconometricsMonopoly

Abstract

fetched live from OpenAlex

Abstract This paper considers a standard New Keynesian model with matching frictions and explores the impact of modeling the opportunity cost of employment as government unemployment transfers. The findings reveal that under such circumstances, maintaining full price stability at all times ceases to be optimal. This outcome persists even when production subsidies are introduced to address inefficiencies caused by imperfect competition in product and factor markets, and when wages are fully flexible and the Hosios condition holds. For a realistic calibration of the opportunity cost, the Ramsey-optimal policy necessitates a positive inflation rate with high volatility. The degree of inflation volatility required increases with the magnitude of unemployment transfers. Consequently, committing to an inflation targeting regime proves to be highly costly in this context. Additionally, the study demonstrates that the optimal inflation variability decreases with workers’ bargaining power. This is because higher workers’ bargaining power leads to reduced labor market fluctuations, thereby lowering the need for large inflation adjustments.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.045
GPT teacher head0.224
Teacher spread0.179 · 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 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
Published2023
Admission routes1
Has abstractyes

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