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Record W4414400294 · doi:10.1016/j.econlet.2025.112629

Expectations of inflation, wages and spending: Evidence from a consumer survey

2025· article· en· W4414400294 on OpenAlexaffabout
Monica Jain, Olena Kostyshyna, Xu Zhang

Bibliographic record

VenueEconomics Letters · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsBank of CanadaWilfrid Laurier University
Fundersnot available
KeywordsInflation (cosmology)WageWage growthSurvey data collectionRelative pricePrice levelConsumer price index (South Africa)

Abstract

fetched live from OpenAlex

• Higher expected price inflation is associated with lower expected household spending. • Conversely, higher expected wage growth is linked to higher expected spending. • These relationships became stronger during the high-inflation period. • Higher expected inflation is linked to postponing purchases and cutting back spending. Using household-level data from the Canadian Survey of Consumer Expectations over 2014Q4– 2022Q3, we provide insight into the formation of expectations for inflation, wage and spending growth. The literature has documented that households associate higher expected price inflation with worse economic conditions, but that higher expected wage inflation is linked to better economic outcomes. Our paper finds that these views extend to households’ spending decisions: higher expected price inflation is also associated with lower expected household spending, while higher expected wage growth is linked to higher expected spending. These relationships became stronger during the high-inflation period.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.594
Threshold uncertainty score0.817

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.025
GPT teacher head0.240
Teacher spread0.215 · 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
Published2025
Admission routes2
Has abstractyes

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