Analyzing profitability ratios of leading global public oil and gas corporations
Bibliographic record
Abstract
Subject. The article discusses the key profitability metrics of the largest public companies in the oil and gas (O&G) industry from 2006 to 2018. The analysis encompasses ExxonMobil, Chevron, ConocoPhillips, Occidental Petroleum, Devon Energy, Anadarko Petroleum, EOG Resources, Apache, Marathon Oil, Imperial Oil, Suncor Energy, Husky Energy, Canadian Natural Resources, Royal Dutch Shell, BP, TOTAL, Eni, Equinor (Statoil), PetroChina, Sinopec, CNOOC, Petrobras, PJSC Gazprom, PJSC Rosneft Oil Company и PJSC LUKOIL. Objectives. The study assesses key profitability metrics of leading public corporations in oil and gas, identifies key trends in their developments as part of the analyzable period. We also determine what triggered such a transformation. Methods. We employed methods of comparative and financial-economic analysis, summarized official annual reports on financial and business operations prepared by major public O&G corporations. Results. Upon the comprehensive analysis of balance sheets prepared by 25 O&G corporations, we evaluated the dynamics of key profitability indicators in the public segment of O&G industry and determined what triggered the transformation. Conclusions and Relevance. For the analyzable period, major public O&G corporations were found to have become less profitable, especially manifesting this during the global financial and sectoral crisis. Some independent U.S. corporations are facing the most difficult situation. The public segment saw their profitability indicators fall, because the growth rate of operational expenses exceeded revenue predominantly due to costs of wear and tear, depletion and depreciation. What else affected the corporations was a considerable increase in the carrying amount of non-working assets. The public segment of O&G industry was discovered to observe gradually lowering income tax burden per unit of net revenue from core operations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".