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Record W2214437451 · doi:10.6000/1929-7092.2015.04.20

Economic Growth and Financial Instability: The Ideas of Hayek and Keynes

2015· article· en· W2214437451 on OpenAlexvenueno aff
Noemí Levy Orlik

Bibliographic record

VenueJournal of Reviews on Global Economics · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsKeynesian economicsInstabilityEconomic stabilityNeoclassical economicsMacroeconomicsMonetary economicsPhysics

Abstract

fetched live from OpenAlex

Complex monetary systems in capitalist economies, whose financial markets can cause financial instabilities and economic downturns is an accepted argument by both John M. Keynes and Friedrich A. Hayek, disagreeing in terms of the factors generating financial instability, the mechanism in which financial variables affect the real sector, and more importantly how to generate economic growth.In this paper we discuss Hayek and the Austrian monetary school innovative ideas in terms of money in capitalist economies (i.e., liquidity provisions and credit devaluations) from where the monetarism and later the New Classical framework developed; and revise Keynes and Post Keynesian views that recognized the full effects of money in productions arguing that debts precede money, which is non neutral, thereby can expand economic activity but also unfold financial instability.We concentrate in the dissenting views over financial instability and argue that the main way to overcome economic activity is through expansive fiscal policies, opposing wages cuts, along financial market regulation.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.422
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.248
Teacher spread0.205 · 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.

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

Citations4
Published2015
Admission routes1
Has abstractyes

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