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Record W2922091594 · doi:10.34989/san-2016-14

A Primer on Neo-Fisherian Economics

2021· article· en· W2922091594 on OpenAlexaff
Robert Amano, Thomas J. Carter, Rhys R. Mendes

Bibliographic record

VenueStaff Analytical Notes · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsBank of Canada
Fundersnot available
KeywordsEconomicsHumanitiesInflation (cosmology)Political sciencePhilosophyPhysics

Abstract

fetched live from OpenAlex

Conventional models imply that central banks aiming to raise inflation should lower nominal rates and thus stimulate aggregate demand. However, several economists have recently challenged this conventional wisdom in favour of an alternative “neo-Fisherian’’ view under which higher nominal rates might in fact lead to higher inflation. In this note, we show that a simple New Keynesian model can indeed deliver a neo-Fisherian link from higher nominal rates to higher inflation. However, the conditions under which this link emerges include a configuration of fiscal and monetary policy, which departs substantially from the configuration normally assumed in the New Keynesian literature. In particular, this configuration involves a commitment that the central bank will not respond too aggressively if inflation is off target, in the sense that policy will be set in a manner inconsistent with the Taylor principle. Active use of inflation to manage real government debt would also be needed. We identify significant challenges associated with both these conditions and argue that they militate against policies that aim to exploit the neo-Fisherian mechanism.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.293
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.043
GPT teacher head0.234
Teacher spread0.190 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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