Factors That Determine Capital Structure in Building Material and Construction Listed Firms: Egypt Case
Bibliographic record
Abstract
The main aim of this study is to investigate the factors that affect the capital structure of the Egyptian firms for building materials and construction sector and to analyze capital structures and whether optimal capital structure exists or not. A number of relevant theories of capital structure are reviewed, namely; the trade-off, pecking order and agency theories, in order to initiate some testable propositions concerning these factors that determine the capital structure of the building materials and construction Egyptian firms. This exploration is performed using panel data procedures for a sample of 18 firms listed on the Egyptian Stock Exchange during the period from 2003 thru 2012. The results recommended that profitability is negatively related to debt ratios (LTDR, TDR); whereas firm tangibility is positively linked to the debt ratios. Size, Non-debt taxes shields, liquidity and growth opportunities do not appear to be significantly related to the debt ratios. The findings of this study are consistent with the predictions of the trade-off theory, pecking order theory, and agency theory which show that capital structure models derived from these theories provide some help in understanding the financing behavior of Egyptian firms for building materials and construction sector. This study provided some groundwork to explore the factors that determine the capital structure of Egyptian firms for building materials and construction sector upon which a more detailed study could be based. Furthermore, findings should assist corporate managers to optimize their capital structure decisions. To the best of the authors’ knowledge, this study considers from the pioneering studies that explore the factors that determine the capital structure of the Egyptian building materials and construction firms by using the most recent available data. Moreover, this study to a certain extent goes to confirm the similarity of factors that affect the capital structure decisions in both developing and developed countries.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".