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Record W3155763278 · doi:10.26509/frbc-ec-202111

Expected Post-Pandemic Consumption and Scarred Expectations from COVID-19

2021· article· en· W3155763278 on OpenAlexaff
Edward S. Knotek, Michael McMain, Raphael Schoenle, Alexander Dietrich, Kristian Ove R. Myrseth, Michael Weber

Bibliographic record

VenueEconomic Commentary (Federal Reserve Bank of Cleveland) · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsYork University
Fundersnot available
KeywordsPandemicPessimismCoronavirus disease 2019 (COVID-19)Consumption (sociology)Demographic economics2019-20 coronavirus outbreakEconomicsDevelopment economicsBusinessPsychologyEconomic growthPublic economicsMedicineSociologyOutbreak

Abstract

fetched live from OpenAlex

The COVID-19 vaccination drive raises questions about the trajectory of the economic recovery and the pandemic’s impact on consumers’ longer-term behaviors. In this Commentary, we examine the evolution of consumers’ expectations for their post-crisis spending on services that have been dramatically curtailed by the pandemic: visiting restaurants, bars, and hotels, using public transportation, and attending crowded events. We document a U-shaped pattern of expected future use of these services, with growing pessimism in summer 2020 that had largely reversed by fall 2020—for most groups. More recently, higher-income individuals have indicated that they expect to sharply increase their use of these services compared with their pre-pandemic behaviors, but there has been a notable scarring of expectations among older Americans.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.077
GPT teacher head0.308
Teacher spread0.230 · 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 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

Citations2
Published2021
Admission routes1
Has abstractyes

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