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Record W6996398444

The role of U.S. subprime mortgage-backed assets in propagating the crisis: Contagion or interdependence?

2015· article· en· W6996398444 on OpenAlexaff

Bibliographic record

VenueResearch Portal (Queen's University Belfast) · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsQueen's University
Fundersnot available
KeywordsMarket liquidityFinancial crisisAsset (computer security)InterdependenceFinancial contagionFinancial marketSubprime mortgage crisisQuality (philosophy)Liquidity crisis
DOInot available

Abstract

fetched live from OpenAlex

Though relatively small, the subprime mortgage-backed securities market is often identified as the source of the crisis that swept through the U.S. financial system from 2007 onwards. We investigate if its role in the propagation of the crisis was due to contagion or interdependence. Using a Markov-switching VAR with time-varying transition probabilities, we analyse the transmission of shocks across the financial system. We find little evidence of asset correlation changes between normal and crisis regimes and those that do occur are predominantly associated with liquidity variables. Otherwise, relationships are stable across market conditions, implying that the U.S. financial crisis was due to cross-market interdependencies rather than contagion. There is limited evidence that the deteriorating quality of the underlying assets can explain the transition from ‘normal’ market conditions to a high-volatility regime, although this is not consistent across model specifications.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.039
GPT teacher head0.278
Teacher spread0.239 · 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 designSimulation or modeling
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
Published2015
Admission routes1
Has abstractyes

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