Unfinished Business in the Macroeconomics of Low Inflation:
Bibliographic record
Abstract
Research Grant SES 04-17871 for invaluable financial support. The retirement of George Perry and Bill Brainard gives us an opportunity to say publicly what we have often said privately: Brookings Papers is an important national institution. It is important because it has set the right tone for US macro policy. George and Bill are both Keynesians, not just in the narrow tradition of IS-LM models with Phillips Curves, but also in their broader methodological approach to macroeconomics. Brookings Papers has always reflected their view that macroeconomics should be a pragmatic and judicious mixture of theory and common sense informed by statistical analysis. That of course reflects the methodology of Keynes, throughout his life, and especially in The General Theory. We think that US macro policy has benefited enormously from being based on such a balanced pragmatic-empirical approach. If we doubt the benefits of such an approach to macroeconomics we need only look to the North—to Canada—where doctrinaire use of an extreme form of natural rate theory in the 1990's led them to push inflation too low resulting in an unusual unemployment gap relative to the United States. This is just one example where a more empirical, more nuanced, macroeconomics—such as presented for the last thirty years in Brookings Papers—has
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.100 | 0.034 |
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".