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Record W2900303813 · doi:10.1111/manc.12495

Consumption response to aggregate shocks and the role of leverage

2024· article· en· W2900303813 on OpenAlex
Agnes Kovacs, May Rostom, Philip Bunn

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueManchester School · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
FundersInternational Association for Applied EconometricsUniversity of Ottawa
KeywordsLeverage (statistics)Financial crisisSurvey data collectionMonetary economicsConsumption (sociology)EconomicsAsset (computer security)Demand shockBusinessMacroeconomics

Abstract

fetched live from OpenAlex

Abstract This paper investigates the relationship between mortgage leverage and consumption around the 2008 financial crisis. Using data from the UK's Family Expenditure Survey and Wealth and Asset Survey, we first show that high‐leveraged households made larger cuts to consumption following the financial crisis, and this was largely driven by young households. Second, using a life‐cycle framework, we qualitatively evaluate four possible channels that could explain the observed positive relationship between consumption and leverage: income, uncertainty, credit supply and house price channels. Our key finding is that credit supply tightening is the main driver of the empirical co‐movement between pre‐crisis leverage and consumption growth after 2008.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.017
GPT teacher head0.211
Teacher spread0.194 · 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