MétaCan
Menu
← Back to cohort
Record W7111589226

Demand or Supply? Price Adjustment Heterogeneity during the COVID-19 Pandemic

2024· article· en· W7111589226 on OpenAlexaboutno aff

Bibliographic record

VenueRePEc: Research Papers in Economics · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
FundersDeutsche Bundesbank
KeywordsInflation (cosmology)Economic shortageSupply and demandPandemicSupply shockQuarter (Canadian coin)Survey data collectionGermanExcess supply
DOInot available

Abstract

fetched live from OpenAlex

We study price-setting behavior and subjective perceptions in German firm-level survey data to infer the relative importance of supply and demand during the COVID-19 pandemic. Demand shortages dominate at the onset of the pandemic. A reported negative impact of COVID-19 on current business is associated with a rise in the probability to decrease prices up to 10 percentage points in this episode. Supply forces gain in importance during the ensuing sudden surge in inflation and firms perceive goods supply shortages as most restrictive. Firms adversely affected during the early inflation decline show no higher probability of price increases. Journal: International Journal of Central Banking

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)0.001
metaresearch head score (Gemma)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.093
GPT teacher head0.351
Teacher spread0.258 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueRePEc: Research Papers in Economics→Same topicCOVID-19 Pandemic Impacts→French-language works237,207→