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Record W6946396865 · doi:10.34989/swp-2022-34

How Do People View Price and Wage Inflation?

2022· article· en· W6946396865 on OpenAlexaffabout

Bibliographic record

VenueEconstor (Econstor) · 2022
Typearticle
Languageen
FieldMedicine
TopicBiological and pharmacological studies of plants
Canadian institutionsBank of Canada
Fundersnot available
KeywordsInflation (cosmology)WageWage growthPrice settingWage shareReal interest rateEfficiency wage

Abstract

fetched live from OpenAlex

This paper examines novel household-level data from the Canadian Survey of Consumer Expectations (CSCE) from 2014Q4 to 2022Q1 to understand households’ expectations about price and wage inflation, their respective links to views about labour market conditions, and their subsequent impact on households’ outlook for real spending growth. We find, consistent with recent research, that households associate higher expected price inflation with worse labour market conditions. In contrast, higher expected wage growth is linked to better labour market outcomes—an avenue not previously explored—and consistent with standard macroeconomic models. These differing supply-side and demand-side views of price inflation and wage inflation are reflected in households’ spending outlook: expected real spending is negatively linked to inflation expectations but positively linked to expected wage inflation. Finally, the link between households’ inflation expectations and wage growth expectations is weak, suggesting limited pass-through from consumers’ inflation expectations into their expected wage gains, and thus a lower likelihood of entering a wage-price spiral.

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 score0.250
Threshold uncertainty score0.497

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
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 head0.023
GPT teacher head0.260
Teacher spread0.238 · 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

Citations3
Published2022
Admission routes2
Has abstractyes

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