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Record W2117062780 · doi:10.2202/1534-6013.1313

Inflation, Prices, and Information in Competitive Search

2006· preprint· en· W2117062780 on OpenAlexaff
Miquel Faig, Belén Jerez

Bibliographic record

VenueContributions in Macroeconomics · 2006
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEconomicsInefficiencyMonetary economicsInflation (cosmology)MicroeconomicsMarket liquidity

Abstract

fetched live from OpenAlex

Abstract We study the effects of inflation in a competitive search model where each buyer's utility is private information, and money is essential. The equilibrium is efficient at the Friedman rule, but inflation creates an inefficiency in the terms of trade. Buyers experience a preference shock after they are matched with a seller, and thus they have a precautionary motive for holding money. Sellers, who compete to attract buyers, post non-linear price schedules. As inflation rises, sellers post relatively flat price schedules, which reduce the need for precautionary balances. These price schedules induce buyers with a low desire to consume to purchase inefficiently high quantities because of the low marginal cost of purchasing goods. In contrast, buyers with a high desire to consume purchase inefficiently low quantities as they face binding liquidity constraints. The model fits historical US data on velocity and interest rates.

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 categoriesMeta-epidemiology (narrow)
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 score0.289
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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

Citations15
Published2006
Admission routes1
Has abstractyes

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