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Record W3081590049 · doi:10.5539/ijef.v12n9p95

Finance and Development in Italy, 1870-1913

2020· article· en· W3081590049 on OpenAlexvenueno aff
Andrea Incerpi, Barbara Pistoresi, Alberto Rinaldi

Bibliographic record

VenueInternational Journal of Economics and Finance · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicItaly: Economic History and Contemporary Issues
Canadian institutionsnot available
Fundersnot available
KeywordsIntermediationFinancial intermediaryEconomicsIdentification (biology)Investment (military)Capital (architecture)Foreign direct investmentForeign capitalFinanceFinancial systemBusinessMacroeconomicsPolitical scienceGeography

Abstract

fetched live from OpenAlex

This paper analyses the impact of different sources of financing (foreign capital, migrants’ remittances, and domestic banks intermediation) on Italy’s economic development between 1861 and the World War I. Existing literature has analysed the role of these channels of financial intermediation separately, while this paper for the first time considers them in conjunction. Using IRF from a Cholesky identification structure of a VAR model and relying on an original dataset that combines the most recent series of several financial and economic aggregates, this paper shows that investment in Italy was fuelled by a plurality of sources of funding. A crucial role was played by national saving mobilized by domestic banks and also remittances had a significant impact. Our evidence is instead weaker for foreign capital.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.205
Teacher spread0.169 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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Same venueInternational Journal of Economics and FinanceSame topicItaly: Economic History and Contemporary IssuesFrench-language works237,207