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Record W3125792619 · doi:10.1353/eca.0.0068

Interpreting the Unconventional U.S. Monetary Policy of 2007–09

2009· article· en· W3125792619 on OpenAlexfundno aff
Ricardo Reis

Bibliographic record

VenueBrookings Papers on Economic Activity · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsnot available
FundersCanadian Pulmonary Fibrosis Foundation
KeywordsMonetary policyEconomicsMonetary economicsKeynesian economics

Abstract

fetched live from OpenAlex

This paper reviews the unconventional U.S. monetary policy responses to the financial and real crises of 2007–09, dividing these responses into three groups: interest rate policy, quantitative policy, and credit policy. To interpret interest rate policy, it compares the Federal Reserve's actions with the literature on optimal policy in a liquidity trap. This comparison suggests that policy has been in the direction indicated by theory, but it has not gone far enough. To interpret quantitative policy, the paper reviews the determination of inflation under different policy regimes. The main danger for inflation from current actions is that the Federal Reserve may lose its policy independence; a beneficial side effect of the crisis is that the Friedman rule can be implemented by paying interest on reserves. To interpret credit policy, the paper presents a new model of capital market imperfections with different financial institutions and roles for securitization, leveraging, and mark-to-market accounting. The model suggests that providing credit to traders in securities markets is a more effective response than extending credit to the originators of loans.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.229
Teacher spread0.216 · 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 designObservational
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

Citations33
Published2009
Admission routes1
Has abstractyes

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