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Record W4293238637 · doi:10.3390/economies10050101

Money Supply and Inflation after COVID-19

2022· article· en· W4293238637 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEconomies · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsInflation (cosmology)Vector autoregressionShock (circulatory)Coronavirus disease 2019 (COVID-19)Monetary economicsMonetary policyUnemploymentCore inflationConsumption (sociology)Personal consumption expenditures price indexQuarter (Canadian coin)Supply shockIndex (typography)Core (optical fiber)MacroeconomicsInflation targetingConsumer confidence indexMedicine

Abstract

fetched live from OpenAlex

The core personal consumption expenditure (PCE) price index, the Federal Reserve’s preferred inflation gauge, rose to 5.2 percent on January 2022, which is the highest rate of increase since 40 years ago. Our estimates show that the annualized quarterly core PCE prices could reach 5.45% in the second quarter of 2022 and are as high as 8.57% in a longer time horizon unless corrected with restrictive monetary policies. Thus, the inflation shock since COVID-19 is not transitory, but it is persistent. As economists expect the Federal Reserve to tighten the money supply in March 2022, the insufficient policy responses may be attributed to a failure to incorporate a unique macroeconomic shock to unemployment during the pandemic. We propose a modified vector autoregression (VAR) model to examine structural shocks after COVID-19, and our proposed model performs well in forecasting future price levels in times of a pandemic.

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.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0120.001

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 head0.048
GPT teacher head0.223
Teacher spread0.174 · 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