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Record W2488356686 · doi:10.5539/ijef.v8n8p95

Finance and R&D Investment: A Panel Study of Italian Manufacturing Firms

2016· article· en· W2488356686 on OpenAlexvenueno aff
Marianna Succurro, Giuseppina Damiana Costanzo

Bibliographic record

VenueInternational Journal of Economics and Finance · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsnot available
Fundersnot available
KeywordsCash flowFinanceInvestment (military)DebtPanel dataEconomicsCorporate financeBusinessExternal financingMonetary economicsR&D intensityEconometrics

Abstract

fetched live from OpenAlex

<p>The purpose of this study is to examine the role of different sources of finance on R&D investment decisions in Italian manufacturing firms. Accounting data, taken from the Aida database, are collected over the 2006-2013 years. The empirical evidence shows that the availability of external financing primarily affects the decision to engage in R&D activity rather than R&D intensity. Internal cash flow, on the contrary, does affect both the likelihood of whether firms will undertake any R&D and the size of R&D spending. This impact is strongly significant for financially weaker firms, SMEs and high-tech firms. Due to greater asymmetric information problems, small innovative firms mainly rely on cash-flow to finance innovative projects. Since bank loans and other forms of debt are not well suited for R&D-intensive activities, our study would contribute to the debate whether it might be socially desirable to incentivize alternative small business financing options, still limited in Italy.</p>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.050
GPT teacher head0.233
Teacher spread0.184 · 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.

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

Citations5
Published2016
Admission routes1
Has abstractyes

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