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Record W4295969602 · doi:10.1080/09538259.2022.2105016

Lucas and Tobin: Debating the New Classical Challenge to Keynesian Economics

2022· article· en· W4295969602 on OpenAlexaff
Robert W. Dimand

Bibliographic record

VenueReview of Political Economy · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsBrock University
Fundersnot available
KeywordsEconomicsKeynesian economicsLucas critiqueNew Keynesian economicsTobin's qMacroeconomicsWageMilestoneAsset (computer security)Neoclassical economicsMonetary policyLabour economics

Abstract

fetched live from OpenAlex

The future Nobel laureates Robert Lucas and James Tobin debated the New Classical challenge to the microeconomic foundations and empirical validity of Keynesian economics, with Lucas singling Tobin out as an interlocutor among Keynesian economists who took the New Classical challenge seriously. Their intellectual exchanges began with Tobin, ‘The Wage-Price Mechanism: Overview of the Conference’ (1972), and Lucas, ‘Econometric Testing of the Natural Rate Hypothesis’ (1972), both in Otto Eckstein, ed., The Econometrics of Price Determination Conference (1972). That conference was a milestone in confronting alternative macroeconomic methodologies with each other, but has received relatively little attention in the literature, most notably from Stanley Fischer (in JMCB Supplement, 2007), who characterized ‘that volume as representative of the best thinking of the time on the Phillips curve.’ This paper examines the debate between Lucas and Tobin that began with their contributions to that conference and that reached a climax with Tobin’s Yrjö Jahnsson Lectures (Asset Accumulation and Economic Activity, 1980) and Lucas’s Journal of Economic Literature review article on those lectures.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.999

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.260
Teacher spread0.227 · 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 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

Citations2
Published2022
Admission routes1
Has abstractyes

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