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Record W20741669 · doi:10.1093/jeea/jvad029

Limited Nominal Indexation of Optimal Financial Contracts

2023· article· en· W20741669 on OpenAlexaffabout
Césaire Meh, Vincenzo Quadrini, Yaz Terajima

Bibliographic record

VenueJournal of the European Economic Association · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsBank of CanadaGovernment of Canada
FundersUniversity of TokyoTechnische Universität MünchenPrinceton University
KeywordsIndexationEconomicsVolatility (finance)Monetary economicsInflation (cosmology)Nominal interest rateShock (circulatory)EconometricsMonetary policyReal interest rate

Abstract

fetched live from OpenAlex

Abstract When financial contracts are not fully enforceable and firms observe their own nominal sales before the observation of the aggregate nominal price, the optimal financial contract is not fully indexed to inflation. Because of the limited nominal indexation, which is endogenous in the model, unanticipated inflation affects aggregate investment and future economic activity. The macroeconomic volatility induced by price uncertainty, however, is not monotone: It first increases and then decreases with nominal price uncertainty. We also show that the degree of nominal indexation declines with real idiosyncratic volatility and the impact of an inflation shock decreases with nominal indexation. Using firm-level data from Canada, we find that both predictions are supported by the data.

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)0.006
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.058
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.040
GPT teacher head0.210
Teacher spread0.170 · 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 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

Citations2
Published2023
Admission routes2
Has abstractyes

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