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Record W3023236827 · doi:10.1111/iere.12225

SCREENING AS A UNIFIED THEORY OF DELINQUENCY, RENEGOTIATION, AND BANKRUPTCY

2017· article· en· W3023236827 on OpenAlexaff
Natalia Kovrijnykh, Igor Livshits

Bibliographic record

VenueInternational Economic Review · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsBank of CanadaWestern University
Fundersnot available
KeywordsBankruptcyJuvenile delinquencyRestructuringEconomicsEndowmentAdverse selectionEconomic interventionismGovernment (linguistics)ForeclosurePrivate information retrievalMonetary economicsMicroeconomicsFinanceComputer securityCriminology

Abstract

fetched live from OpenAlex

We propose a parsimonious model with adverse selection where delinquency, renegotiation, and bankruptcy all occur in equilibrium as a result of a simple screening mechanism. A borrower has private information about her endowment, and a lender uses random contracts to screen different types of borrowers. In equilibrium, some borrowers choose not to repay and thus become delinquent. The lender renegotiates with some delinquent borrowers. In the absence of renegotiation, delinquency leads to bankruptcy. Applied to mortgage restructuring, our mechanism generates amplification of house‐price shocks through foreclosure spillovers. We also show that government intervention aimed at limiting foreclosures may have unintended consequences.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.838
Threshold uncertainty score0.999

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 science0.0010.000
Research integrity0.0000.000
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 head0.056
GPT teacher head0.286
Teacher spread0.229 · 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 designTheoretical or conceptual
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

Citations6
Published2017
Admission routes1
Has abstractyes

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