The Effect of Capital Budgeting Decisions on Profitability: Selected Companies from Developed and Developing Countries
Bibliographic record
Abstract
The purpose of this study is to determine the impact of capital budgeting decisions on the profitability of listed companies in Germany, Canada, Jordan, and Egypt. Study population is 64 listed companies. The main independent variable is capital expenditure as measured by natural logarithm of fixed assets. In addition to this variable, study has leverage, liquidity and age of the company as control variables. As for dependent variable, profitability is used measured by return on assets. Secondary data was collected for a period of 9 years on an annual basis. The study employed a descriptive panel data analysis with OLS regression and random regression as robustness to analyze the association between the variables. Eviews 10 was used for analyzing the secondary data. ANOVA results show that the F statistic was significant at 5% level with a p=0.000. Therefore, the model was fit to explain the relationship between the selected variables. The study finds that capital expenditure affects financial performance significantly and positively in both developed and developing countries. In addition to this, control variables are also found to be significant and have signs as expected. However, the study also finds that, the magnitude of the impact of capital expenditure on performance is higher in developed countries relative to developing countries. This relatively lower impact may be explained by the fact that firms in developing economies have not adapted proper and effective project appraisal means for capital budgeting decision making. Based on the findings, the study puts forward some recommendations. Keywords: Capital Budgeting, Profitability, Capital Expenditure
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".