An empirical study on the influence of oil reserves and other key performance measures on corporate performance of Canadian oil and gas companies
Bibliographic record
Abstract
This empirical study examines the influence of proved and probable reserves on corporate performance of Canadian oil and gas companies .The disclosure is considered value-relevant if the change in proved and probable oil reserves disclosure accounts for relative changes in common stock prices.This study is motivated by the fact that the Securities Exchange Commission (SEC) does not require oil and gas companies to disclose probable reserves.The paper addresses two research questions: ( 1) Is the disclosure of information regarding changes in proved and probable reserves value-relevant to the share price of oil and gas producers?(2) Are the current SEC standards on disclosure of oil and gas reserve quantities adequate for equity investors (probable reserves not disclosed)?The annual reports of 30 oil and gas companies were used to gather the data for each of the years 2002 , 2003 , and 2004.A cross-sectional model methodology was used and the results indicate that changes in proved and probable reserves are positively and significantly related to abnormal returns .In addition , proved and probable reserves are jointly more significant than earnings of a company when explaining abnormal returns of oil and gas companies in Canada .The study also concludes by recommending that the SEC make it mandatory for publicly traded oil and gas companies to disclose probable oil reserves information.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".