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Animal Spirits, Persistent Unemployment, and the Belief Function

2013· book-chapter· en· W3141633590 on OpenAlexaboutno aff
Roger E. A. Farmer

Bibliographic record

VenuePrinceton University Press eBooks · 2013
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsOddsUnemploymentAnimal spiritsKeynesian economicsNew Keynesian economicsMonetary policyQuarter (Canadian coin)Phillips curveFunction (biology)EconometricsMacroeconomicsMonetary economicsLogistic regressionPsychologyMathematicsStatistics

Abstract

fetched live from OpenAlex

This chapter examines the persistence of unemployment by drawing from John Maynard Keynes' two central ideas. The first idea is that any unemployment rate can persist as an equilibrium. The second is that the unemployment rate that prevails is determined by animal spirits. The chapter introduces a three-equation monetary model termed “Farmer monetary model,” which replaces the New Keynesian Phillips curve with a belief function that describes how agents form expectations of future nominal income. The chapter builds and estimates the Farmer monetary model using U.S. data for the period from the first quarter of 1952 to the fourth quarter of 2007. It compares the Farmer monetary model to a New Keynesian model by computing the posterior odds ratio. It shows that the posterior odds favor the Farmer monetary model and concludes by discussing the implications of this finding for fiscal and monetary policy.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.035
GPT teacher head0.166
Teacher spread0.131 · 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 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

Citations15
Published2013
Admission routes1
Has abstractyes

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