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Record W2794248160 · doi:10.5430/ijfr.v9n2p64

Financial Constraints and Financial Crises: The Case of Portuguese Listed Companies

2018· article· en· W2794248160 on OpenAlexvenueno aff
Luı́sa Pereira, Armando Silva, Sónia Silva

Bibliographic record

VenueInternational Journal of Financial Research · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsFinancePanel dataCash flowFinancial crisisBusinessFinancial ratioDividendIndex (typography)Sample (material)Financial analysisPortugueseInvestment (military)Financial systemEconomicsEconometrics

Abstract

fetched live from OpenAlex

The purpose of this study is to analyze the degree of financial constraints faced by the companies included on the Portuguese Stock General Index when accessing to external financing, especially after the beginning and during the most recent financial crisis that affected the world financial markets from 2007. According to this aim, a longitudinal database is collected from the SABI database and was analyzed under panel data methodology. The final sample is panel data of 430 firm-year observations, related to 43 companies, during the period 2006-2015.In line with previous literature, our results provide evidence that the payout ratio is an efficient measure of the degree of financial constraints; companies that pay out less (or no) dividends display higher sensitivity of the investment to the cash flow. Moreover, we also found that the investment sensitivity to cash flow intensifies immediately after and during the most recent financial crisis.

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)0.007
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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.078
GPT teacher head0.355
Teacher spread0.277 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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