Analysis of the Determinants of Capital Structure: Evidence from Unlisted Agro-Based Firms in Nigeria 2005-2010
Why this work is in the frame
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Bibliographic record
Abstract
The study furthers evidence of capital structure theories in developing countries by investigating the determinants of capital structure of a sample of 60 unquoted agro-based firms in Nigeria. Data collected through a multi-stage random sampling for the period 2005-2010 were analyzed using the Ordinary Least Square (OLS) regression and descriptive statistics. The result revealed that only growth and educational level of firms’ owners were significant determinants of both long and short-term debt ratios. While asset structure, age of firms, gender of owners and export status impacted significantly on long–term debt ratios, only business risk, size and profitability of firms were major determinants of short-term debt ratio for the firms under investigation. This, therefore, informed the need to pursue policies that would encourage asset accumulation, promote exportation, address gender inequality and reduce business risk as policy measures.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it