The role of the hierarchical theory in explaining the capital structure of the firms based on enterprise life cycle model
Bibliographic record
Abstract
Capital structure is a controversial issue in the field of corporate finance. There are several studies to find a way to determine the optimal capital structure to minimize the cost of capital and maximize the corporate value. In fact, capital structure is a combination of firms' liabilities and capital to meet long term assets. This paper investigates the role of the hierarchical theory in explaining the capital structure of the firms based on enterprise life cycle model on selected firms listed on Tehran Stock Exchange (TSE) using three methods of net equities, net liabilities and retained earnings. The study uses Park and Chen's ( The effect of accounting conservatism and life-cycle stages on firm valuation. Journal of Applied Business Research (JABR), 22(3), 75-92.] to categorize the life cycle of 81 randomly selected firms from TSE over the period 2007-2012. The results indicate that the hierarchical theory represents the growing firms better than the matured firms do. The results also show that firms were more willing to reduce their dividend per share for financing their projects.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".