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Record W2890325122

Nexus between Firm Level Investment and Financing Constraint Measures: A Critical Review

2018· review· en· W2890325122 on OpenAlexvenueno aff
Humaira Husain, Khairul Alom, Kazi Md. Tarique

Bibliographic record

VenueReview of Economics and Finance · 2018
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicCapital Investment and Risk Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCash flowVolatility (finance)External financingMonetary economicsInvestment (military)Constraint (computer-aided design)EconomicsFinanceNexus (standard)Business
DOInot available

Abstract

fetched live from OpenAlex

This article critically examines recent literature for apparently contradictory findings of FHP and KZ strand theory of investment cash-flow responsiveness, as firm level investment is one of the major drivers of economic growth. The reason for opposite findings of FHP and KZ is: FHP addressed the supply side determinants of external finance, while KZ used the demand side determinants. Recent findings show that investment irreversibility might cause insignificant investment cash-flow sensitivity for constrained firms. Furthermore, recent studies demonstrate that cash-flow volatility does play an important role in determining degree of sensitivity of investment to change in internally generated corporate funds within constrained group of firms. For constrained firms asymmetric information problem is dominated by cash-flow volatility and investment irreversibility varies positively with cash-flow volatility. Financial constraint should be relaxed for constrained firms which have relatively lower degree of volatility in internally generated corporate funds. Increase in cash stock also induces constrained firms to invest more than unconstrained firms.

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)0.003
metaresearch head score (Gemma)0.015
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: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.008
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.001
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 head0.182
GPT teacher head0.312
Teacher spread0.129 · 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
GenreReview

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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