Lucas and Tobin: Debating the New Classical Challenge to Keynesian Economics
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.006 | 0.014 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".