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Record W4385804407 · doi:10.3386/w31543

Managing an Energy Shock: Fiscal and Monetary Policy

2023· report· en· W4385804407 on OpenAlexaff
Adrien Auclert, Hugo Monnery, Matthew Rognlie, Ludwig Straub

Bibliographic record

VenueNational Bureau of Economic Research · 2023
Typereport
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsBank of Canada
FundersNational Science Foundation
KeywordsShock (circulatory)Monetary economicsMonetary policyFiscal policyEconomicsMacroeconomicsBusinessFinancial systemInternal medicineMedicine

Abstract

fetched live from OpenAlex

This paper studies the macroeconomic effects of energy price shocks in energy-importing economies using a heterogeneous-agent New Keynesian model. When MPCs are realistically large and the elasticity of substitution between energy and domestic goods is realistically low, increases in energy prices depress real incomes and cause a recession, even if the central bank does not tighten monetary policy. Imported energy inflation can spill over to wage inflation through a wage-price spiral, but this does not mitigate the decline in real wages. Monetary tightening has limited effect on imported inflation when done in isolation, but can be powerful when done in coordination with other energy importers by lowering world energy demand. Fiscal policy, especially energy price subsidies, can isolate individual energy importers from the shock, but it has large negative externalities on other economies.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.900
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.243
GPT teacher head0.498
Teacher spread0.254 · 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
GenreOther

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

Citations28
Published2023
Admission routes1
Has abstractyes

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