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Record W2319945177 · doi:10.18267/j.polek.1029

Demand For Cash in Circulation in the Czech Republic In 2002-2014 and Its Changes During the Financial Crisis

2015· article· en· W2319945177 on OpenAlexaboutno aff
Pavel Řežábek

Bibliographic record

VenuePolitická ekonomie · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Fiscal Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCurrencyCirculation (fluid dynamics)EconomicsCashMonetary economicsInterest rateFinancial crisisPaymentQuarter (Canadian coin)BusinessInternational economicsFinanceMacroeconomics

Abstract

fetched live from OpenAlex

The demand for cash in the Czech Republic is characterized since the establishment of the Czech currency in 1993 by a steady upward trend that has been disrupted by several non-standard episodes. One of the episodes was a substantial surge in Czech currency holdings after the outbreak of the financial crisis in late 2008. Results based on a model of currency demand show that the increase in currency in circulation in the last quarter of 2008 cannot be explained by common variables, which include retail sales, interest rate, innovation in payment systems, and tourism. Separate models of currency demand for small and large denominations revealed significant differences in terms of sensitivity to different variables. While small-value banknotes are mainly driven by domestic transactions, payment system innovations and tourism, the demand for large-value banknotes depends more on a short-term interest rate. Increased currency demand had to be explicitly modeled only in case of high-denomination banknotes and was best explained by the confidence indicator.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.070
GPT teacher head0.241
Teacher spread0.172 · 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 designObservational
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

Citations1
Published2015
Admission routes1
Has abstractyes

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